TITLE:
The Struggle: Transcribe stuff for free with Whisper and WSL/Linux – With a GTX 1060

DESCRIPTION:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text […]

CONTENT:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc.

I first found a Samsung app that could handle transcription, but it quickly became clear that it was limited to its own ecosystem. In practice, you could only transcribe audio that had been recorded inside that specific app.

Since then, I’ve been looking around on and off, and more recently I picked it up again as the need increased – partly to get correct transcriptions, but also to be able to process any audio files I download or record. Samsung’s app is decent, but the quality varies. Right after recording, it performs a quick transcription, but the result is noticeably worse than if you re-run the transcription once the audio file is fully finalized.

At that point I came across “Whisper Transcribe” for Windows. It works, but it requires an account and, of course, paid credits to continue transcribing. You get a small number of free credits at first, but once those run out, you’re expected to pay quite a bit just to keep going.

I already knew that there must be software capable of doing this completely locally. I had previously discovered that Whisper exists in an open-source form as well (I’m not even sure whether the Windows application actually builds on that or not). So today I decided to finally figure out how to do it properly myself.

The end result was the following (thanks to ChatGPT):

A Whisper installer for WSL/Linux, with explicit support for NVIDIA GTX 1060 – something newer Python libraries clearly no longer handle well.

A Whisper runner for WSL/Linux: run whisper <input-file> and get a .txt transcript generated from the audio file.

A Windows Registry file that allows transcription to be executed directly from Windows Explorer via right-click.

A batch file that bridges Windows and WSL so everything runs cleanly, including proper handling of spaces and non-ASCII characters in file names.

The result is a fully local, offline transcription setup that works on any audio file, without accounts, credits, or vendor lock-in.

WSL uses python and pip…

Table of Contents
Toggle
whisper.batwhisper.reg (explorer right clicks)installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)The script itself
whisper.bat

@echo off
setlocal EnableExtensions

REM Force UTF-8 codepage (fixes å ä ö)
chcp 65001 >nul

REM File passed from Explorer
set "WIN_FILE=%~1"

REM Convert Windows path to WSL path (UTF-8 safe now)
for /f "delims=" %%i in ('wsl wslpath "%WIN_FILE%"') do set "WSL_FILE=%%i"

REM Run whisper on that file
wsl bash -lc "/usr/local/tornevall/whisper \"%WSL_FILE%\""

endlocal

whisper.reg (explorer right clicks)

Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL]
@="Transkribera med Whisper (WSL)"
"Icon"="wsl.exe"

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL\command]
@="\"F:\\viktigt\\Private\\Linux-Scripts\\Whisper.bat\" \"%1\""

installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)

To make sure stuff are removed properly before reinstalling there is a -u switch for this in the script. In case you make it wrong the first time, this switch is there to make sure you can reinstall it a second time without conflicts.

#!/usr/bin/env bash
set -euo pipefail

VENV_DIR="${VENV_DIR:-$HOME/.venvs/whisper}"
MODE="install"

# --- Parse args ---
while getopts ":u" opt; do
 case "$opt" in
 u) MODE="uninstall" ;;
 *)
 echo "Usage: $0 [-u]"
 exit 1
 ;;
 esac
done

echo "==> Whisper installer (GTX 1060 compatible)"
echo "==> Mode: $MODE"

# --- Sanity ---
if [[ ! -d "$VENV_DIR" ]]; then
 echo "Error: venv not found: $VENV_DIR"
 exit 1
fi

# shellcheck disable=SC1090
source "$VENV_DIR/bin/activate"

python -m pip install --upgrade pip setuptools wheel

# ==================================================
# UNINSTALL MODE (-u)
# ==================================================
if [[ "$MODE" == "uninstall" ]]; then
 echo "==> Uninstalling incompatible packages ONLY (-u)"

 pip uninstall -y torch torchvision torchaudio || true
 pip uninstall -y numpy || true

 echo ""
 echo "Done."
 echo "Uninstall completed. Nothing else touched."
 exit 0
fi

# ==================================================
# INSTALL MODE (DEFAULT)
# ==================================================

echo "==> Installing compatible stack (no forced uninstall)"

pip install \
 numpy==1.26.4 \
 torch==1.13.1+cu116 \
 torchvision==0.14.1+cu116 \
 torchaudio==0.13.1 \
 --extra-index-url https://download.pytorch.org/whl/cu116

# --- Verify ---
echo "==> Verifying environment"
python - << 'EOF'
import torch, numpy
print("Torch:", torch.__version__)
print("NumPy:", numpy.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
 print("GPU:", torch.cuda.get_device_name(0))
 print("Capability:", torch.cuda.get_device_capability(0))
EOF

echo ""
echo "Done."
echo "Install completed without destructive actions."

The script itself

The script can run without any switches – and only with the audio file intended to be transcribed (but as you can see, it can do a bit more).

#!/usr/bin/env bash
set -euo pipefail

# whisper-run.sh
# Usage:
# whisper <input.extension> [model] [language]
#
# Output:
# <input-filename>.txt (same directory)
#
# Behaviour:
# - Refuses to overwrite existing .txt
# - Stops execution if output exists

if [[ $# -lt 1 ]]; then
 echo "Usage: whisper <input.extension> [model] [language]"
 exit 1
fi

INPUT="$1"
MODEL="${2:-small}"
LANGUAGE="${3:-}"

if [[ ! -f "$INPUT" ]]; then
 echo "Error: Input file not found: $INPUT"
 exit 1
fi

BASENAME="$(basename "$INPUT")"
STEM="${BASENAME%.*}"
OUTDIR="$(dirname "$INPUT")"
OUTPUT="$OUTDIR/$STEM.txt"

# --- Refuse overwrite ---
if [[ -f "$OUTPUT" ]]; then
 echo "Error: Output file already exists:"
 echo " $OUTPUT"
 echo "Aborting to avoid overwrite."
 exit 1
fi

# Prefer venv whisper if installed via install script
WHISPER_VENV="${WHISPER_VENV:-$HOME/.venvs/whisper}"
WHISPER_BIN="whisper"
if [[ -x "$WHISPER_VENV/bin/whisper" ]]; then
 WHISPER_BIN="$WHISPER_VENV/bin/whisper"
fi

if [[ "$WHISPER_BIN" == "whisper" ]] && ! command -v whisper >/dev/null 2>&1; then
 echo "Error: whisper not found in PATH or venv."
 exit 1
fi

TMPDIR="$(mktemp -d)"
cleanup() { rm -rf "$TMPDIR"; }
trap cleanup EXIT

echo "==> Transcribing:"
echo " input: $INPUT"
echo " output: $OUTPUT"
echo " model: $MODEL"
echo " lang: ${LANGUAGE:-auto}"

ARGS=(
 "$INPUT"
 --model "$MODEL"
 --output_dir "$TMPDIR"
 --output_format txt
 --task transcribe
 --verbose False
 --fp16 False
)

if [[ -n "$LANGUAGE" ]]; then
 ARGS+=( --language "$LANGUAGE" )
fi

"$WHISPER_BIN" "${ARGS[@]}"

GENERATED_TXT="$TMPDIR/$STEM.txt"
if [[ ! -f "$GENERATED_TXT" ]]; then
 FOUND_TXT="$(find "$TMPDIR" -maxdepth 1 -type f -name "*.txt" | head -n 1 || true)"
 if [[ -z "${FOUND_TXT:-}" ]]; then
 echo "Error: No .txt output produced."
 exit 1
 fi
 GENERATED_TXT="$FOUND_TXT"
fi

# --- Final move (no overwrite possible due to earlier check) ---
mv "$GENERATED_TXT" "$OUTPUT"

echo "==> Done:"
echo " $OUTPUT"

TITLE:
The Struggle: Transcribe stuff for free with Whisper and WSL/Linux – With a GTX 1060

DESCRIPTION:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc. I first found a Samsung app that could handle […]

CONTENT:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc.

I first found a Samsung app that could handle transcription, but it quickly became clear that it was limited to its own ecosystem. In practice, you could only transcribe audio that had been recorded inside that specific app.

Since then, I’ve been looking around on and off, and more recently I picked it up again as the need increased – partly to get correct transcriptions, but also to be able to process any audio files I download or record. Samsung’s app is decent, but the quality varies. Right after recording, it performs a quick transcription, but the result is noticeably worse than if you re-run the transcription once the audio file is fully finalized.

At that point I came across “Whisper Transcribe” for Windows. It works, but it requires an account and, of course, paid credits to continue transcribing. You get a small number of free credits at first, but once those run out, you’re expected to pay quite a bit just to keep going.

I already knew that there must be software capable of doing this completely locally. I had previously discovered that Whisper exists in an open-source form as well (I’m not even sure whether the Windows application actually builds on that or not). So today I decided to finally figure out how to do it properly myself.

The end result was the following (thanks to ChatGPT):

A Whisper installer for WSL/Linux, with explicit support for NVIDIA GTX 1060 – something newer Python libraries clearly no longer handle well.

A Whisper runner for WSL/Linux: run whisper <input-file> and get a .txt transcript generated from the audio file.

A Windows Registry file that allows transcription to be executed directly from Windows Explorer via right-click.

A batch file that bridges Windows and WSL so everything runs cleanly, including proper handling of spaces and non-ASCII characters in file names.

The result is a fully local, offline transcription setup that works on any audio file, without accounts, credits, or vendor lock-in.

WSL uses python and pip…

Table of Contents
Toggle
whisper.batwhisper.reg (explorer right clicks)installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)The script itself
whisper.bat

@echo off
setlocal EnableExtensions

REM Force UTF-8 codepage (fixes å ä ö)
chcp 65001 >nul

REM File passed from Explorer
set "WIN_FILE=%~1"

REM Convert Windows path to WSL path (UTF-8 safe now)
for /f "delims=" %%i in ('wsl wslpath "%WIN_FILE%"') do set "WSL_FILE=%%i"

REM Run whisper on that file
wsl bash -lc "/usr/local/tornevall/whisper \"%WSL_FILE%\""

endlocal

whisper.reg (explorer right clicks)

Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL]
@="Transkribera med Whisper (WSL)"
"Icon"="wsl.exe"

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL\command]
@="\"F:\\viktigt\\Private\\Linux-Scripts\\Whisper.bat\" \"%1\""

installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)

To make sure stuff are removed properly before reinstalling there is a -u switch for this in the script. In case you make it wrong the first time, this switch is there to make sure you can reinstall it a second time without conflicts.

#!/usr/bin/env bash
set -euo pipefail

VENV_DIR="${VENV_DIR:-$HOME/.venvs/whisper}"
MODE="install"

# --- Parse args ---
while getopts ":u" opt; do
 case "$opt" in
 u) MODE="uninstall" ;;
 *)
 echo "Usage: $0 [-u]"
 exit 1
 ;;
 esac
done

echo "==> Whisper installer (GTX 1060 compatible)"
echo "==> Mode: $MODE"

# --- Sanity ---
if [[ ! -d "$VENV_DIR" ]]; then
 echo "Error: venv not found: $VENV_DIR"
 exit 1
fi

# shellcheck disable=SC1090
source "$VENV_DIR/bin/activate"

python -m pip install --upgrade pip setuptools wheel

# ==================================================
# UNINSTALL MODE (-u)
# ==================================================
if [[ "$MODE" == "uninstall" ]]; then
 echo "==> Uninstalling incompatible packages ONLY (-u)"

 pip uninstall -y torch torchvision torchaudio || true
 pip uninstall -y numpy || true

 echo ""
 echo "Done."
 echo "Uninstall completed. Nothing else touched."
 exit 0
fi

# ==================================================
# INSTALL MODE (DEFAULT)
# ==================================================

echo "==> Installing compatible stack (no forced uninstall)"

pip install \
 numpy==1.26.4 \
 torch==1.13.1+cu116 \
 torchvision==0.14.1+cu116 \
 torchaudio==0.13.1 \
 --extra-index-url https://download.pytorch.org/whl/cu116

# --- Verify ---
echo "==> Verifying environment"
python - << 'EOF'
import torch, numpy
print("Torch:", torch.__version__)
print("NumPy:", numpy.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
 print("GPU:", torch.cuda.get_device_name(0))
 print("Capability:", torch.cuda.get_device_capability(0))
EOF

echo ""
echo "Done."
echo "Install completed without destructive actions."

The script itself

The script can run without any switches – and only with the audio file intended to be transcribed (but as you can see, it can do a bit more).

#!/usr/bin/env bash
set -euo pipefail

# whisper-run.sh
# Usage:
# whisper <input.extension> [model] [language]
#
# Output:
# <input-filename>.txt (same directory)
#
# Behaviour:
# - Refuses to overwrite existing .txt
# - Stops execution if output exists

if [[ $# -lt 1 ]]; then
 echo "Usage: whisper <input.extension> [model] [language]"
 exit 1
fi

INPUT="$1"
MODEL="${2:-small}"
LANGUAGE="${3:-}"

if [[ ! -f "$INPUT" ]]; then
 echo "Error: Input file not found: $INPUT"
 exit 1
fi

BASENAME="$(basename "$INPUT")"
STEM="${BASENAME%.*}"
OUTDIR="$(dirname "$INPUT")"
OUTPUT="$OUTDIR/$STEM.txt"

# --- Refuse overwrite ---
if [[ -f "$OUTPUT" ]]; then
 echo "Error: Output file already exists:"
 echo " $OUTPUT"
 echo "Aborting to avoid overwrite."
 exit 1
fi

# Prefer venv whisper if installed via install script
WHISPER_VENV="${WHISPER_VENV:-$HOME/.venvs/whisper}"
WHISPER_BIN="whisper"
if [[ -x "$WHISPER_VENV/bin/whisper" ]]; then
 WHISPER_BIN="$WHISPER_VENV/bin/whisper"
fi

if [[ "$WHISPER_BIN" == "whisper" ]] && ! command -v whisper >/dev/null 2>&1; then
 echo "Error: whisper not found in PATH or venv."
 exit 1
fi

TMPDIR="$(mktemp -d)"
cleanup() { rm -rf "$TMPDIR"; }
trap cleanup EXIT

echo "==> Transcribing:"
echo " input: $INPUT"
echo " output: $OUTPUT"
echo " model: $MODEL"
echo " lang: ${LANGUAGE:-auto}"

ARGS=(
 "$INPUT"
 --model "$MODEL"
 --output_dir "$TMPDIR"
 --output_format txt
 --task transcribe
 --verbose False
 --fp16 False
)

if [[ -n "$LANGUAGE" ]]; then
 ARGS+=( --language "$LANGUAGE" )
fi

"$WHISPER_BIN" "${ARGS[@]}"

GENERATED_TXT="$TMPDIR/$STEM.txt"
if [[ ! -f "$GENERATED_TXT" ]]; then
 FOUND_TXT="$(find "$TMPDIR" -maxdepth 1 -type f -name "*.txt" | head -n 1 || true)"
 if [[ -z "${FOUND_TXT:-}" ]]; then
 echo "Error: No .txt output produced."
 exit 1
 fi
 GENERATED_TXT="$FOUND_TXT"
fi

# --- Final move (no overwrite possible due to earlier check) ---
mv "$GENERATED_TXT" "$OUTPUT"

echo "==> Done:"
echo " $OUTPUT"

TITLE:
The Struggle: Transcribe stuff for free with Whisper and WSL/Linux – With a GTX 1060

DESCRIPTION:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that...

CONTENT:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc.

I first found a Samsung app that could handle transcription, but it quickly became clear that it was limited to its own ecosystem. In practice, you could only transcribe audio that had been recorded inside that specific app.

Since then, I’ve been looking around on and off, and more recently I picked it up again as the need increased – partly to get correct transcriptions, but also to be able to process any audio files I download or record. Samsung’s app is decent, but the quality varies. Right after recording, it performs a quick transcription, but the result is noticeably worse than if you re-run the transcription once the audio file is fully finalized.

At that point I came across “Whisper Transcribe” for Windows. It works, but it requires an account and, of course, paid credits to continue transcribing. You get a small number of free credits at first, but once those run out, you’re expected to pay quite a bit just to keep going.

I already knew that there must be software capable of doing this completely locally. I had previously discovered that Whisper exists in an open-source form as well (I’m not even sure whether the Windows application actually builds on that or not). So today I decided to finally figure out how to do it properly myself.

The end result was the following (thanks to ChatGPT):

A Whisper installer for WSL/Linux, with explicit support for NVIDIA GTX 1060 – something newer Python libraries clearly no longer handle well.

A Whisper runner for WSL/Linux: run whisper <input-file> and get a .txt transcript generated from the audio file.

A Windows Registry file that allows transcription to be executed directly from Windows Explorer via right-click.

A batch file that bridges Windows and WSL so everything runs cleanly, including proper handling of spaces and non-ASCII characters in file names.

The result is a fully local, offline transcription setup that works on any audio file, without accounts, credits, or vendor lock-in.

WSL uses python and pip…

Table of Contents
Toggle
whisper.batwhisper.reg (explorer right clicks)installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)The script itself
whisper.bat

@echo off
setlocal EnableExtensions

REM Force UTF-8 codepage (fixes å ä ö)
chcp 65001 >nul

REM File passed from Explorer
set "WIN_FILE=%~1"

REM Convert Windows path to WSL path (UTF-8 safe now)
for /f "delims=" %%i in ('wsl wslpath "%WIN_FILE%"') do set "WSL_FILE=%%i"

REM Run whisper on that file
wsl bash -lc "/usr/local/tornevall/whisper \"%WSL_FILE%\""

endlocal

whisper.reg (explorer right clicks)

Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL]
@="Transkribera med Whisper (WSL)"
"Icon"="wsl.exe"

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL\command]
@="\"F:\\viktigt\\Private\\Linux-Scripts\\Whisper.bat\" \"%1\""

installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)

To make sure stuff are removed properly before reinstalling there is a -u switch for this in the script. In case you make it wrong the first time, this switch is there to make sure you can reinstall it a second time without conflicts.

#!/usr/bin/env bash
set -euo pipefail

VENV_DIR="${VENV_DIR:-$HOME/.venvs/whisper}"
MODE="install"

# --- Parse args ---
while getopts ":u" opt; do
 case "$opt" in
 u) MODE="uninstall" ;;
 *)
 echo "Usage: $0 [-u]"
 exit 1
 ;;
 esac
done

echo "==> Whisper installer (GTX 1060 compatible)"
echo "==> Mode: $MODE"

# --- Sanity ---
if [[ ! -d "$VENV_DIR" ]]; then
 echo "Error: venv not found: $VENV_DIR"
 exit 1
fi

# shellcheck disable=SC1090
source "$VENV_DIR/bin/activate"

python -m pip install --upgrade pip setuptools wheel

# ==================================================
# UNINSTALL MODE (-u)
# ==================================================
if [[ "$MODE" == "uninstall" ]]; then
 echo "==> Uninstalling incompatible packages ONLY (-u)"

 pip uninstall -y torch torchvision torchaudio || true
 pip uninstall -y numpy || true

 echo ""
 echo "Done."
 echo "Uninstall completed. Nothing else touched."
 exit 0
fi

# ==================================================
# INSTALL MODE (DEFAULT)
# ==================================================

echo "==> Installing compatible stack (no forced uninstall)"

pip install \
 numpy==1.26.4 \
 torch==1.13.1+cu116 \
 torchvision==0.14.1+cu116 \
 torchaudio==0.13.1 \
 --extra-index-url https://download.pytorch.org/whl/cu116

# --- Verify ---
echo "==> Verifying environment"
python - << 'EOF'
import torch, numpy
print("Torch:", torch.__version__)
print("NumPy:", numpy.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
 print("GPU:", torch.cuda.get_device_name(0))
 print("Capability:", torch.cuda.get_device_capability(0))
EOF

echo ""
echo "Done."
echo "Install completed without destructive actions."

The script itself

The script can run without any switches – and only with the audio file intended to be transcribed (but as you can see, it can do a bit more).

#!/usr/bin/env bash
set -euo pipefail

# whisper-run.sh
# Usage:
# whisper <input.extension> [model] [language]
#
# Output:
# <input-filename>.txt (same directory)
#
# Behaviour:
# - Refuses to overwrite existing .txt
# - Stops execution if output exists

if [[ $# -lt 1 ]]; then
 echo "Usage: whisper <input.extension> [model] [language]"
 exit 1
fi

INPUT="$1"
MODEL="${2:-small}"
LANGUAGE="${3:-}"

if [[ ! -f "$INPUT" ]]; then
 echo "Error: Input file not found: $INPUT"
 exit 1
fi

BASENAME="$(basename "$INPUT")"
STEM="${BASENAME%.*}"
OUTDIR="$(dirname "$INPUT")"
OUTPUT="$OUTDIR/$STEM.txt"

# --- Refuse overwrite ---
if [[ -f "$OUTPUT" ]]; then
 echo "Error: Output file already exists:"
 echo " $OUTPUT"
 echo "Aborting to avoid overwrite."
 exit 1
fi

# Prefer venv whisper if installed via install script
WHISPER_VENV="${WHISPER_VENV:-$HOME/.venvs/whisper}"
WHISPER_BIN="whisper"
if [[ -x "$WHISPER_VENV/bin/whisper" ]]; then
 WHISPER_BIN="$WHISPER_VENV/bin/whisper"
fi

if [[ "$WHISPER_BIN" == "whisper" ]] && ! command -v whisper >/dev/null 2>&1; then
 echo "Error: whisper not found in PATH or venv."
 exit 1
fi

TMPDIR="$(mktemp -d)"
cleanup() { rm -rf "$TMPDIR"; }
trap cleanup EXIT

echo "==> Transcribing:"
echo " input: $INPUT"
echo " output: $OUTPUT"
echo " model: $MODEL"
echo " lang: ${LANGUAGE:-auto}"

ARGS=(
 "$INPUT"
 --model "$MODEL"
 --output_dir "$TMPDIR"
 --output_format txt
 --task transcribe
 --verbose False
 --fp16 False
)

if [[ -n "$LANGUAGE" ]]; then
 ARGS+=( --language "$LANGUAGE" )
fi

"$WHISPER_BIN" "${ARGS[@]}"

GENERATED_TXT="$TMPDIR/$STEM.txt"
if [[ ! -f "$GENERATED_TXT" ]]; then
 FOUND_TXT="$(find "$TMPDIR" -maxdepth 1 -type f -name "*.txt" | head -n 1 || true)"
 if [[ -z "${FOUND_TXT:-}" ]]; then
 echo "Error: No .txt output produced."
 exit 1
 fi
 GENERATED_TXT="$FOUND_TXT"
fi

# --- Final move (no overwrite possible due to earlier check) ---
mv "$GENERATED_TXT" "$OUTPUT"

echo "==> Done:"
echo " $OUTPUT"

TITLE:
The Struggle: Transcribe stuff for free with Whisper and WSL/Linux – With a GTX 1060

DESCRIPTION:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text […]

CONTENT:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc.

I first found a Samsung app that could handle transcription, but it quickly became clear that it was limited to its own ecosystem. In practice, you could only transcribe audio that had been recorded inside that specific app.

Since then, I’ve been looking around on and off, and more recently I picked it up again as the need increased – partly to get correct transcriptions, but also to be able to process any audio files I download or record. Samsung’s app is decent, but the quality varies. Right after recording, it performs a quick transcription, but the result is noticeably worse than if you re-run the transcription once the audio file is fully finalized.

At that point I came across “Whisper Transcribe” for Windows. It works, but it requires an account and, of course, paid credits to continue transcribing. You get a small number of free credits at first, but once those run out, you’re expected to pay quite a bit just to keep going.

I already knew that there must be software capable of doing this completely locally. I had previously discovered that Whisper exists in an open-source form as well (I’m not even sure whether the Windows application actually builds on that or not). So today I decided to finally figure out how to do it properly myself.

The end result was the following (thanks to ChatGPT):

A Whisper installer for WSL/Linux, with explicit support for NVIDIA GTX 1060 – something newer Python libraries clearly no longer handle well.

A Whisper runner for WSL/Linux: run whisper <input-file> and get a .txt transcript generated from the audio file.

A Windows Registry file that allows transcription to be executed directly from Windows Explorer via right-click.

A batch file that bridges Windows and WSL so everything runs cleanly, including proper handling of spaces and non-ASCII characters in file names.

The result is a fully local, offline transcription setup that works on any audio file, without accounts, credits, or vendor lock-in.

WSL uses python and pip…

Table of Contents
Toggle
whisper.batwhisper.reg (explorer right clicks)installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)The script itself
whisper.bat

@echo off
setlocal EnableExtensions

REM Force UTF-8 codepage (fixes å ä ö)
chcp 65001 >nul

REM File passed from Explorer
set "WIN_FILE=%~1"

REM Convert Windows path to WSL path (UTF-8 safe now)
for /f "delims=" %%i in ('wsl wslpath "%WIN_FILE%"') do set "WSL_FILE=%%i"

REM Run whisper on that file
wsl bash -lc "/usr/local/tornevall/whisper \"%WSL_FILE%\""

endlocal

whisper.reg (explorer right clicks)

Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL]
@="Transkribera med Whisper (WSL)"
"Icon"="wsl.exe"

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL\command]
@="\"F:\\viktigt\\Private\\Linux-Scripts\\Whisper.bat\" \"%1\""

installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)

To make sure stuff are removed properly before reinstalling there is a -u switch for this in the script. In case you make it wrong the first time, this switch is there to make sure you can reinstall it a second time without conflicts.

#!/usr/bin/env bash
set -euo pipefail

VENV_DIR="${VENV_DIR:-$HOME/.venvs/whisper}"
MODE="install"

# --- Parse args ---
while getopts ":u" opt; do
 case "$opt" in
 u) MODE="uninstall" ;;
 *)
 echo "Usage: $0 [-u]"
 exit 1
 ;;
 esac
done

echo "==> Whisper installer (GTX 1060 compatible)"
echo "==> Mode: $MODE"

# --- Sanity ---
if [[ ! -d "$VENV_DIR" ]]; then
 echo "Error: venv not found: $VENV_DIR"
 exit 1
fi

# shellcheck disable=SC1090
source "$VENV_DIR/bin/activate"

python -m pip install --upgrade pip setuptools wheel

# ==================================================
# UNINSTALL MODE (-u)
# ==================================================
if [[ "$MODE" == "uninstall" ]]; then
 echo "==> Uninstalling incompatible packages ONLY (-u)"

 pip uninstall -y torch torchvision torchaudio || true
 pip uninstall -y numpy || true

 echo ""
 echo "Done."
 echo "Uninstall completed. Nothing else touched."
 exit 0
fi

# ==================================================
# INSTALL MODE (DEFAULT)
# ==================================================

echo "==> Installing compatible stack (no forced uninstall)"

pip install \
 numpy==1.26.4 \
 torch==1.13.1+cu116 \
 torchvision==0.14.1+cu116 \
 torchaudio==0.13.1 \
 --extra-index-url https://download.pytorch.org/whl/cu116

# --- Verify ---
echo "==> Verifying environment"
python - << 'EOF'
import torch, numpy
print("Torch:", torch.__version__)
print("NumPy:", numpy.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
 print("GPU:", torch.cuda.get_device_name(0))
 print("Capability:", torch.cuda.get_device_capability(0))
EOF

echo ""
echo "Done."
echo "Install completed without destructive actions."

The script itself

The script can run without any switches – and only with the audio file intended to be transcribed (but as you can see, it can do a bit more).

#!/usr/bin/env bash
set -euo pipefail

# whisper-run.sh
# Usage:
# whisper <input.extension> [model] [language]
#
# Output:
# <input-filename>.txt (same directory)
#
# Behaviour:
# - Refuses to overwrite existing .txt
# - Stops execution if output exists

if [[ $# -lt 1 ]]; then
 echo "Usage: whisper <input.extension> [model] [language]"
 exit 1
fi

INPUT="$1"
MODEL="${2:-small}"
LANGUAGE="${3:-}"

if [[ ! -f "$INPUT" ]]; then
 echo "Error: Input file not found: $INPUT"
 exit 1
fi

BASENAME="$(basename "$INPUT")"
STEM="${BASENAME%.*}"
OUTDIR="$(dirname "$INPUT")"
OUTPUT="$OUTDIR/$STEM.txt"

# --- Refuse overwrite ---
if [[ -f "$OUTPUT" ]]; then
 echo "Error: Output file already exists:"
 echo " $OUTPUT"
 echo "Aborting to avoid overwrite."
 exit 1
fi

# Prefer venv whisper if installed via install script
WHISPER_VENV="${WHISPER_VENV:-$HOME/.venvs/whisper}"
WHISPER_BIN="whisper"
if [[ -x "$WHISPER_VENV/bin/whisper" ]]; then
 WHISPER_BIN="$WHISPER_VENV/bin/whisper"
fi

if [[ "$WHISPER_BIN" == "whisper" ]] && ! command -v whisper >/dev/null 2>&1; then
 echo "Error: whisper not found in PATH or venv."
 exit 1
fi

TMPDIR="$(mktemp -d)"
cleanup() { rm -rf "$TMPDIR"; }
trap cleanup EXIT

echo "==> Transcribing:"
echo " input: $INPUT"
echo " output: $OUTPUT"
echo " model: $MODEL"
echo " lang: ${LANGUAGE:-auto}"

ARGS=(
 "$INPUT"
 --model "$MODEL"
 --output_dir "$TMPDIR"
 --output_format txt
 --task transcribe
 --verbose False
 --fp16 False
)

if [[ -n "$LANGUAGE" ]]; then
 ARGS+=( --language "$LANGUAGE" )
fi

"$WHISPER_BIN" "${ARGS[@]}"

GENERATED_TXT="$TMPDIR/$STEM.txt"
if [[ ! -f "$GENERATED_TXT" ]]; then
 FOUND_TXT="$(find "$TMPDIR" -maxdepth 1 -type f -name "*.txt" | head -n 1 || true)"
 if [[ -z "${FOUND_TXT:-}" ]]; then
 echo "Error: No .txt output produced."
 exit 1
 fi
 GENERATED_TXT="$FOUND_TXT"
fi

# --- Final move (no overwrite possible due to earlier check) ---
mv "$GENERATED_TXT" "$OUTPUT"

echo "==> Done:"
echo " $OUTPUT"

TITLE:
The Struggle: Transcribe stuff for free with Whisper and WSL/Linux – With a GTX 1060

DESCRIPTION:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that...

CONTENT:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc.

I first found a Samsung app that could handle transcription, but it quickly became clear that it was limited to its own ecosystem. In practice, you could only transcribe audio that had been recorded inside that specific app.

Since then, I’ve been looking around on and off, and more recently I picked it up again as the need increased – partly to get correct transcriptions, but also to be able to process any audio files I download or record. Samsung’s app is decent, but the quality varies. Right after recording, it performs a quick transcription, but the result is noticeably worse than if you re-run the transcription once the audio file is fully finalized.

At that point I came across “Whisper Transcribe” for Windows. It works, but it requires an account and, of course, paid credits to continue transcribing. You get a small number of free credits at first, but once those run out, you're expected to pay quite a bit just to keep going.

I already knew that there must be software capable of doing this completely locally. I had previously discovered that Whisper exists in an open-source form as well (I'm not even sure whether the Windows application actually builds on that or not). So today I decided to finally figure out how to do it properly myself.

The end result was the following (thanks to ChatGPT):

A Whisper installer for WSL/Linux, with explicit support for NVIDIA GTX 1060 – something newer Python libraries clearly no longer handle well.

A Whisper runner for WSL/Linux: run whisper <input-file> and get a .txt transcript generated from the audio file.

A Windows Registry file that allows transcription to be executed directly from Windows Explorer via right-click.

A batch file that bridges Windows and WSL so everything runs cleanly, including proper handling of spaces and non-ASCII characters in file names.

The result is a fully local, offline transcription setup that works on any audio file, without accounts, credits, or vendor lock-in.

WSL uses python and pip…

Table of Contents
Toggle
whisper.batwhisper.reg (explorer right clicks)installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)The script itself
whisper.bat

@echo off
setlocal EnableExtensions

REM Force UTF-8 codepage (fixes å ä ö)
chcp 65001 >nul

REM File passed from Explorer
set "WIN_FILE=%~1"

REM Convert Windows path to WSL path (UTF-8 safe now)
for /f "delims=" %%i in ('wsl wslpath "%WIN_FILE%"') do set "WSL_FILE=%%i"

REM Run whisper on that file
wsl bash -lc "/usr/local/tornevall/whisper \"%WSL_FILE%\""

endlocal

whisper.reg (explorer right clicks)

Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL]
@="Transkribera med Whisper (WSL)"
"Icon"="wsl.exe"

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL\command]
@="\"F:\\viktigt\\Private\\Linux-Scripts\\Whisper.bat\" \"%1\""

installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)

To make sure stuff are removed properly before reinstalling there is a -u switch for this in the script. In case you make it wrong the first time, this switch is there to make sure you can reinstall it a second time without conflicts.

#!/usr/bin/env bash
set -euo pipefail

VENV_DIR="${VENV_DIR:-$HOME/.venvs/whisper}"
MODE="install"

# --- Parse args ---
while getopts ":u" opt; do
 case "$opt" in
 u) MODE="uninstall" ;;
 *)
 echo "Usage: $0 [-u]"
 exit 1
 ;;
 esac
done

echo "==> Whisper installer (GTX 1060 compatible)"
echo "==> Mode: $MODE"

# --- Sanity ---
if [[ ! -d "$VENV_DIR" ]]; then
 echo "Error: venv not found: $VENV_DIR"
 exit 1
fi

# shellcheck disable=SC1090
source "$VENV_DIR/bin/activate"

python -m pip install --upgrade pip setuptools wheel

# ==================================================
# UNINSTALL MODE (-u)
# ==================================================
if [[ "$MODE" == "uninstall" ]]; then
 echo "==> Uninstalling incompatible packages ONLY (-u)"

 pip uninstall -y torch torchvision torchaudio || true
 pip uninstall -y numpy || true

 echo ""
 echo "Done."
 echo "Uninstall completed. Nothing else touched."
 exit 0
fi

# ==================================================
# INSTALL MODE (DEFAULT)
# ==================================================

echo "==> Installing compatible stack (no forced uninstall)"

pip install \
 numpy==1.26.4 \
 torch==1.13.1+cu116 \
 torchvision==0.14.1+cu116 \
 torchaudio==0.13.1 \
 --extra-index-url https://download.pytorch.org/whl/cu116

# --- Verify ---
echo "==> Verifying environment"
python - << 'EOF'
import torch, numpy
print("Torch:", torch.__version__)
print("NumPy:", numpy.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
 print("GPU:", torch.cuda.get_device_name(0))
 print("Capability:", torch.cuda.get_device_capability(0))
EOF

echo ""
echo "Done."
echo "Install completed without destructive actions."

The script itself

The script can run without any switches – and only with the audio file intended to be transcribed (but as you can see, it can do a bit more).

#!/usr/bin/env bash
set -euo pipefail

# whisper-run.sh
# Usage:
# whisper <input.extension> [model] [language]
#
# Output:
# <input-filename>.txt (same directory)
#
# Behaviour:
# - Refuses to overwrite existing .txt
# - Stops execution if output exists

if [[ $# -lt 1 ]]; then
 echo "Usage: whisper <input.extension> [model] [language]"
 exit 1
fi

INPUT="$1"
MODEL="${2:-small}"
LANGUAGE="${3:-}"

if [[ ! -f "$INPUT" ]]; then
 echo "Error: Input file not found: $INPUT"
 exit 1
fi

BASENAME="$(basename "$INPUT")"
STEM="${BASENAME%.*}"
OUTDIR="$(dirname "$INPUT")"
OUTPUT="$OUTDIR/$STEM.txt"

# --- Refuse overwrite ---
if [[ -f "$OUTPUT" ]]; then
 echo "Error: Output file already exists:"
 echo " $OUTPUT"
 echo "Aborting to avoid overwrite."
 exit 1
fi

# Prefer venv whisper if installed via install script
WHISPER_VENV="${WHISPER_VENV:-$HOME/.venvs/whisper}"
WHISPER_BIN="whisper"
if [[ -x "$WHISPER_VENV/bin/whisper" ]]; then
 WHISPER_BIN="$WHISPER_VENV/bin/whisper"
fi

if [[ "$WHISPER_BIN" == "whisper" ]] && ! command -v whisper >/dev/null 2>&1; then
 echo "Error: whisper not found in PATH or venv."
 exit 1
fi

TMPDIR="$(mktemp -d)"
cleanup() { rm -rf "$TMPDIR"; }
trap cleanup EXIT

echo "==> Transcribing:"
echo " input: $INPUT"
echo " output: $OUTPUT"
echo " model: $MODEL"
echo " lang: ${LANGUAGE:-auto}"

ARGS=(
 "$INPUT"
 --model "$MODEL"
 --output_dir "$TMPDIR"
 --output_format txt
 --task transcribe
 --verbose False
 --fp16 False
)

if [[ -n "$LANGUAGE" ]]; then
 ARGS+=( --language "$LANGUAGE" )
fi

"$WHISPER_BIN" "${ARGS[@]}"

GENERATED_TXT="$TMPDIR/$STEM.txt"
if [[ ! -f "$GENERATED_TXT" ]]; then
 FOUND_TXT="$(find "$TMPDIR" -maxdepth 1 -type f -name "*.txt" | head -n 1 || true)"
 if [[ -z "${FOUND_TXT:-}" ]]; then
 echo "Error: No .txt output produced."
 exit 1
 fi
 GENERATED_TXT="$FOUND_TXT"
fi

# --- Final move (no overwrite possible due to earlier check) ---
mv "$GENERATED_TXT" "$OUTPUT"

echo "==> Done:"
echo " $OUTPUT"

TITLE:
The Struggle: Transcribe stuff for free with Whisper and WSL/Linux – With a GTX 1060

DESCRIPTION:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that...

CONTENT:
I’ve been struggling with transcription issues for quite some time, for a variety of reasons. Examples: I need a text transcribed to be pasted into Suno, that only exists as a m4a-file (i.e. music, that sometimes has hardcoded subtitles that has to be manually transcribed). Etc.

I first found a Samsung app that could handle transcription, but it quickly became clear that it was limited to its own ecosystem. In practice, you could only transcribe audio that had been recorded inside that specific app.

Since then, I’ve been looking around on and off, and more recently I picked it up again as the need increased – partly to get correct transcriptions, but also to be able to process any audio files I download or record. Samsung’s app is decent, but the quality varies. Right after recording, it performs a quick transcription, but the result is noticeably worse than if you re-run the transcription once the audio file is fully finalized.

At that point I came across “Whisper Transcribe” for Windows. It works, but it requires an account and, of course, paid credits to continue transcribing. You get a small number of free credits at first, but once those run out, you’re expected to pay quite a bit just to keep going.

I already knew that there must be software capable of doing this completely locally. I had previously discovered that Whisper exists in an open-source form as well (I’m not even sure whether the Windows application actually builds on that or not). So today I decided to finally figure out how to do it properly myself.

The end result was the following (thanks to ChatGPT):

A Whisper installer for WSL/Linux, with explicit support for NVIDIA GTX 1060 – something newer Python libraries clearly no longer handle well.

A Whisper runner for WSL/Linux: run whisper <input-file> and get a .txt transcript generated from the audio file.

A Windows Registry file that allows transcription to be executed directly from Windows Explorer via right-click.

A batch file that bridges Windows and WSL so everything runs cleanly, including proper handling of spaces and non-ASCII characters in file names.

The result is a fully local, offline transcription setup that works on any audio file, without accounts, credits, or vendor lock-in.

WSL uses python and pip…

Table of Contents
Toggle
whisper.batwhisper.reg (explorer right clicks)installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)The script itself
whisper.bat

@echo off
setlocal EnableExtensions

REM Force UTF-8 codepage (fixes å ä ö)
chcp 65001 >nul

REM File passed from Explorer
set "WIN_FILE=%~1"

REM Convert Windows path to WSL path (UTF-8 safe now)
for /f "delims=" %%i in ('wsl wslpath "%WIN_FILE%"') do set "WSL_FILE=%%i"

REM Run whisper on that file
wsl bash -lc "/usr/local/tornevall/whisper \"%WSL_FILE%\""

endlocal

whisper.reg (explorer right clicks)

Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL]
@="Transkribera med Whisper (WSL)"
"Icon"="wsl.exe"

[HKEY_CLASSES_ROOT\*\shell\WhisperWSL\command]
@="\"F:\\viktigt\\Private\\Linux-Scripts\\Whisper.bat\" \"%1\""

installer för WSL/Linux (with 1060-compatibilty and pre-uninstaller)

To make sure stuff are removed properly before reinstalling there is a -u switch for this in the script. In case you make it wrong the first time, this switch is there to make sure you can reinstall it a second time without conflicts.

#!/usr/bin/env bash
set -euo pipefail

VENV_DIR="${VENV_DIR:-$HOME/.venvs/whisper}"
MODE="install"

# --- Parse args ---
while getopts ":u" opt; do
 case "$opt" in
 u) MODE="uninstall" ;;
 *)
 echo "Usage: $0 [-u]"
 exit 1
 ;;
 esac
done

echo "==> Whisper installer (GTX 1060 compatible)"
echo "==> Mode: $MODE"

# --- Sanity ---
if [[ ! -d "$VENV_DIR" ]]; then
 echo "Error: venv not found: $VENV_DIR"
 exit 1
fi

# shellcheck disable=SC1090
source "$VENV_DIR/bin/activate"

python -m pip install --upgrade pip setuptools wheel

# ==================================================
# UNINSTALL MODE (-u)
# ==================================================
if [[ "$MODE" == "uninstall" ]]; then
 echo "==> Uninstalling incompatible packages ONLY (-u)"

 pip uninstall -y torch torchvision torchaudio || true
 pip uninstall -y numpy || true

 echo ""
 echo "Done."
 echo "Uninstall completed. Nothing else touched."
 exit 0
fi

# ==================================================
# INSTALL MODE (DEFAULT)
# ==================================================

echo "==> Installing compatible stack (no forced uninstall)"

pip install \
 numpy==1.26.4 \
 torch==1.13.1+cu116 \
 torchvision==0.14.1+cu116 \
 torchaudio==0.13.1 \
 --extra-index-url https://download.pytorch.org/whl/cu116

# --- Verify ---
echo "==> Verifying environment"
python - << 'EOF'
import torch, numpy
print("Torch:", torch.__version__)
print("NumPy:", numpy.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
 print("GPU:", torch.cuda.get_device_name(0))
 print("Capability:", torch.cuda.get_device_capability(0))
EOF

echo ""
echo "Done."
echo "Install completed without destructive actions."

The script itself

The script can run without any switches – and only with the audio file intended to be transcribed (but as you can see, it can do a bit more).

#!/usr/bin/env bash
set -euo pipefail

# whisper-run.sh
# Usage:
# whisper <input.extension> [model] [language]
#
# Output:
# <input-filename>.txt (same directory)
#
# Behaviour:
# - Refuses to overwrite existing .txt
# - Stops execution if output exists

if [[ $# -lt 1 ]]; then
 echo "Usage: whisper <input.extension> [model] [language]"
 exit 1
fi

INPUT="$1"
MODEL="${2:-small}"
LANGUAGE="${3:-}"

if [[ ! -f "$INPUT" ]]; then
 echo "Error: Input file not found: $INPUT"
 exit 1
fi

BASENAME="$(basename "$INPUT")"
STEM="${BASENAME%.*}"
OUTDIR="$(dirname "$INPUT")"
OUTPUT="$OUTDIR/$STEM.txt"

# --- Refuse overwrite ---
if [[ -f "$OUTPUT" ]]; then
 echo "Error: Output file already exists:"
 echo " $OUTPUT"
 echo "Aborting to avoid overwrite."
 exit 1
fi

# Prefer venv whisper if installed via install script
WHISPER_VENV="${WHISPER_VENV:-$HOME/.venvs/whisper}"
WHISPER_BIN="whisper"
if [[ -x "$WHISPER_VENV/bin/whisper" ]]; then
 WHISPER_BIN="$WHISPER_VENV/bin/whisper"
fi

if [[ "$WHISPER_BIN" == "whisper" ]] && ! command -v whisper >/dev/null 2>&1; then
 echo "Error: whisper not found in PATH or venv."
 exit 1
fi

TMPDIR="$(mktemp -d)"
cleanup() { rm -rf "$TMPDIR"; }
trap cleanup EXIT

echo "==> Transcribing:"
echo " input: $INPUT"
echo " output: $OUTPUT"
echo " model: $MODEL"
echo " lang: ${LANGUAGE:-auto}"

ARGS=(
 "$INPUT"
 --model "$MODEL"
 --output_dir "$TMPDIR"
 --output_format txt
 --task transcribe
 --verbose False
 --fp16 False
)

if [[ -n "$LANGUAGE" ]]; then
 ARGS+=( --language "$LANGUAGE" )
fi

"$WHISPER_BIN" "${ARGS[@]}"

GENERATED_TXT="$TMPDIR/$STEM.txt"
if [[ ! -f "$GENERATED_TXT" ]]; then
 FOUND_TXT="$(find "$TMPDIR" -maxdepth 1 -type f -name "*.txt" | head -n 1 || true)"
 if [[ -z "${FOUND_TXT:-}" ]]; then
 echo "Error: No .txt output produced."
 exit 1
 fi
 GENERATED_TXT="$FOUND_TXT"
fi

# --- Final move (no overwrite possible due to earlier check) ---
mv "$GENERATED_TXT" "$OUTPUT"

echo "==> Done:"
echo " $OUTPUT"

TITLE:
The main purpose of the tech house track “Magdalena”

DESCRIPTION:
The lyrics for “Magdalena” are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

CONTENT:
This track was created as a response to fear-driven narratives surrounding social democracy, particularly how certain political ideas are framed through anxiety, exaggeration, and symbolic threat rather than concrete policy discussion.

Magdalena refers to the chair of the Swedish Social Democratic Party. In Swedish political discourse, she has become a frequent target of hostility that often extends beyond specific decisions and instead focuses on what she represents. In the context of this track, Magdalena is therefore not portrayed as an individual, but used as a symbolic figure.

The song deliberately frames her as a stabilizing presence. Repeated chants and cyclical structures emphasize continuity, direction, and resilience. Rather than engaging in debate or argumentation, the track contrasts abstract ideas of chaos and order through rhythm and repetition.

The lyrics are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

Any harsher expressions in the lyrics are directed at abstract authoritarian or fear-based mindsets, not at individuals or groups. The intention is not provocation, but to challenge narratives built on demonization and simplified oppositions.

Overall, the track operates on a symbolic level. It responds to political fear by reframing social democracy as structure rather than disorder, stability rather than threat, and continuity rather than chaos, while remaining grounded in club-oriented electronic music aesthetics rather than overt political commentary.

TITLE:
The main purpose of the tech house track “Magdalena”

DESCRIPTION:
The lyrics for “Magdalena” are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

CONTENT:
This track was created as a response to fear-driven narratives surrounding social democracy, particularly how certain political ideas are framed through anxiety, exaggeration, and symbolic threat rather than concrete policy discussion.

Magdalena refers to the chair of the Swedish Social Democratic Party. In Swedish political discourse, she has become a frequent target of hostility that often extends beyond specific decisions and instead focuses on what she represents. In the context of this track, Magdalena is therefore not portrayed as an individual, but used as a symbolic figure.

The song deliberately frames her as a stabilizing presence. Repeated chants and cyclical structures emphasize continuity, direction, and resilience. Rather than engaging in debate or argumentation, the track contrasts abstract ideas of chaos and order through rhythm and repetition.

The lyrics are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

Any harsher expressions in the lyrics are directed at abstract authoritarian or fear-based mindsets, not at individuals or groups. The intention is not provocation, but to challenge narratives built on demonization and simplified oppositions.

Overall, the track operates on a symbolic level. It responds to political fear by reframing social democracy as structure rather than disorder, stability rather than threat, and continuity rather than chaos, while remaining grounded in club-oriented electronic music aesthetics rather than overt political commentary.

TITLE:
The main purpose of the tech house track “Magdalena”

DESCRIPTION:
The lyrics for “Magdalena” are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

CONTENT:
This track was created as a response to fear-driven narratives surrounding social democracy, particularly how certain political ideas are framed through anxiety, exaggeration, and symbolic threat rather than concrete policy discussion.

Magdalena refers to the chair of the Swedish Social Democratic Party. In Swedish political discourse, she has become a frequent target of hostility that often extends beyond specific decisions and instead focuses on what she represents. In the context of this track, Magdalena is therefore not portrayed as an individual, but used as a symbolic figure.

The song deliberately frames her as a stabilizing presence. Repeated chants and cyclical structures emphasize continuity, direction, and resilience. Rather than engaging in debate or argumentation, the track contrasts abstract ideas of chaos and order through rhythm and repetition.

The lyrics are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

Any harsher expressions in the lyrics are directed at abstract authoritarian or fear-based mindsets, not at individuals or groups. The intention is not provocation, but to challenge narratives built on demonization and simplified oppositions.

Overall, the track operates on a symbolic level. It responds to political fear by reframing social democracy as structure rather than disorder, stability rather than threat, and continuity rather than chaos, while remaining grounded in club-oriented electronic music aesthetics rather than overt political commentary.

TITLE:
The main purpose of the tech house track “Magdalena”

DESCRIPTION:
The lyrics for “Magdalena” are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

CONTENT:
This track was created as a response to fear-driven narratives surrounding social democracy, particularly how certain political ideas are framed through anxiety, exaggeration, and symbolic threat rather than concrete policy discussion.

Magdalena refers to the chair of the Swedish Social Democratic Party. In Swedish political discourse, she has become a frequent target of hostility that often extends beyond specific decisions and instead focuses on what she represents. In the context of this track, Magdalena is therefore not portrayed as an individual, but used as a symbolic figure.

The song deliberately frames her as a stabilizing presence. Repeated chants and cyclical structures emphasize continuity, direction, and resilience. Rather than engaging in debate or argumentation, the track contrasts abstract ideas of chaos and order through rhythm and repetition.

The lyrics are intentionally written in another language to mask the literal meaning and shift focus away from local political rhetoric. This choice also supports the musical direction of the track, giving it a more exotic Latin tech house character and allowing the vocal elements to function as texture and energy rather than explicit messaging.

Any harsher expressions in the lyrics are directed at abstract authoritarian or fear-based mindsets, not at individuals or groups. The intention is not provocation, but to challenge narratives built on demonization and simplified oppositions.

Overall, the track operates on a symbolic level. It responds to political fear by reframing social democracy as structure rather than disorder, stability rather than threat, and continuity rather than chaos, while remaining grounded in club-oriented electronic music aesthetics rather than overt political commentary.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they don’t. Not even close. The latest example – my personal favorite – came from an […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we're dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn't think. It doesn't predict. It doesn't learn. It doesn't hallucinate answers because you ask stupid questions. It doesn't care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don't.

Second: Calling people slow and other random words doesn't magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn't become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they're supposedly replacing. There's a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you're a luddite”

“DAWs used AI for decades!”

“it's the same thing!”

No. It's not. And calling someone a luddite doesn't turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you're not an innovator. You're not “ahead of the curve”.You're not misunderstood.

You're just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn't the tech. It's the users who don't understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they don’t. Not even close. The latest example – my personal favorite – came from an […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we're dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn't think. It doesn't predict. It doesn't learn. It doesn't hallucinate answers because you ask stupid questions. It doesn't care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don't.

Second: Calling people slow and other random words doesn't magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn't become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they're supposedly replacing. There's a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you're a luddite”

“DAWs used AI for decades!”

“it's the same thing!”

No. It's not. And calling someone a luddite doesn't turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you're not an innovator. You're not “ahead of the curve”.You're not misunderstood.

You're just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn't the tech. It's the users who don't understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they don’t. Not even close. The latest example – my personal favorite – came from an […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we're dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn't think. It doesn't predict. It doesn't learn. It doesn't hallucinate answers because you ask stupid questions. It doesn't care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don't.

Second: Calling people slow and other random words doesn't magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn't become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they're supposedly replacing. There's a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you're a luddite”

“DAWs used AI for decades!”

“it's the same thing!”

No. It's not. And calling someone a luddite doesn't turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you're not an innovator. You're not “ahead of the curve”.You're not misunderstood.

You're just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn't the tech. It's the users who don't understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they don’t. Not even close. The latest example – my personal favorite – came from an […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared […]

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we're dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn't think. It doesn't predict. It doesn't learn. It doesn't hallucinate answers because you ask stupid questions. It doesn't care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don't.

Second: Calling people slow and other random words doesn't magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn't become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they're supposedly replacing. There's a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you're a luddite”

“DAWs used AI for decades!”

“it's the same thing!”

No. It's not. And calling someone a luddite doesn't turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you're not an innovator. You're not “ahead of the curve”.You're not misunderstood.

You're just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn't the tech. It's the users who don't understand it.

TITLE:
Things “Prompt Pushers” Thought They Understood About DAWs – But Are Completely, Utterly Wrong About

DESCRIPTION:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate. Spoiler: they...

CONTENT:
Every now and then, especially in groups where “AI-generated music” is the hot topic, I encounter a parade of self-declared “AI creators” who seem absolutely convinced they understand how AI, DAWs, plugins, audio engines and production workflows operate.

Spoiler: they don’t. Not even close.

The latest example – my personal favorite – came from an exchange with a couple of AI-wannabe musicians who tried to argue that a DAW is a type of AI. Yes. A Digital Audio Workstation. According to them, pressing Record apparently counts as machine intelligence now.

This is the level we’re dealing with – usually among Suno-wannabes and so-called Udio-idiots when we try to explain how DAWs works.

Table of Contents
Toggle
A DAW IS NOT AI – IT WILL NEVER BE AI!“But VSTs Use AI!”Yes, some do – and that still doesn’t make your DAW AI!The Real Issue: AI Musicians Who Don’t Understand Music ToolsWhy This Matters
A DAW IS NOT AI – IT WILL NEVER BE AI!

A DAW is a workstation – software used to record, edit and produce audio, not a “thinking” system (see any basic DAW definition). A timeline. A mixer. A routing environment.

It doesn’t think. It doesn’t predict. It doesn’t learn. It doesn’t hallucinate answers because you ask stupid questions. It doesn’t care what you want. It does exactly what you tell it to do.

AI, meanwhile, is defined by its capacity to generate, classify, predict or reason based on trained data – a machine based system that infers from input to generate outputs like predictions, content or decisions (see the OECD and EU definitions of AI systems). That is machine learning, which is something completely different from a sequencer that has existed since the 1980s.

But apparently, for some people on the internet, everything becomes AI if you squint hard enough.

That ALSO includes the Google screenshot that was used to prove me wrong saying “Yes, DAWs use AI in a variety of ways to enhance music production”.

The text used is not a technical definition, it is an AI generated summary from Google’s experimental AI Overviews and AI Mode in Search feature, which stitches together a generic answer to the vague prompt “does a DAW use AI in some way”... That “AI researcher” is by the way extremely unreliable as it very much works as ChatGPT in “quick response mode” and guessing (since users tend to hate wait for a correct answer) what it cannot cover by itself (unless you use Thinking mode).

It talks about using AI powered plugins and features inside a DAW, not about the DAW itself magically becoming an AI system. Google itself describes these AI Overviews as AI generated “snapshots” that simply bundle key information with links to real sources, not as authoritative definitions of anything (see their own description). Treating that blurb as proof that “a DAW is AI” is like treating an ad banner as peer reviewed research.

“But VSTs Use AI!”

Yes, some do – and that still doesn’t make your DAW AI!

This was the next brilliant argument thrown at me:

“Most of the components in a DAW use AI. Are you slow?”

First: No, they don’t.

Second: Calling people slow and other random words doesn’t magically make your argument correct.

Most plugins run on traditional DSP – decades-old mathematics based on manipulating digital samples, not on “learning” from data (audio DSP is literally just signal processing code, not AI). Compression, EQ, filtering, reverb, synthesis, modulation – none of that is AI. If you think a compressor is artificial intelligence, you need to revisit the basics.

Some plugins do use machine learning for tasks like noise reduction or stem separation – for example real time denoisers trained on speech like VoiceGate or deep learning based noise reduction projects like DeepFilterNet. Fine. But your environment does not become AI just because a plugin inside it happens to use it. Your microwave doesn’t become AI if you heat a smart thermometer inside it either.

The Real Issue: AI Musicians Who Don’t Understand Music Tools

This whole conversation acutally exposed something deeper, which makes this topic interesting, and that is why I choose to highlight the idiocrazy: Many AI-first creators cannot explain – or even identify – the tools they’re supposedly replacing. There’s a growing crowd of prompt-pushers who:

have never mixed a track manually,

never aligned vocals without an AI tool,

never programmed automation by hand,

never learned gain staging,

never rendered or layered anything intentionally,

and absolutely never used a DAW beyond dragging stems into the timeline.

Yet they lecture others on “how audio production really works”.

And when someone challenges their nonsense, they fire off buzzwords like:

“you refuse to be educated”

“you’re a luddite”

“DAWs used AI for decades!”

“it’s the same thing!”

No. It’s not. And calling someone a luddite doesn’t turn confusion into expertise. It just telegraphs desperation.

Why This Matters

The problem isn’t people using AI.

The problem is people pretending that AI makes them instant audio engineers – and then attacking anyone who points out the difference between a tool and a technology.

AI is powerful. It’s useful – but it doesn’t replace understanding.

If you think a DAW is artificial intelligence, you’re not an innovator. You’re not “ahead of the curve”.You’re not misunderstood.

You’re just wrong. And loudly so.

If you want to be taken seriously as a creator in this hybrid world of AI-assisted music:

Learn what your tools are.

Learn what your tools are not.

Stop claiming everything with buttons and soundwaves is AI.

Because right now, the biggest challenge for AI-powered music isn’t the tech. It’s the users who don’t understand it.

TITLE:
DJ Set: The Experimental Minimix from 2022 that saved me from pain

DESCRIPTION:
The year was 2023 March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn...

CONTENT:
Table of Contents
Toggle
The year was 2023Tracklist
The year was 2023

March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn almost 50,000 SEK on ads, two-factor authentication did nothing, and every attempt to reach support led nowhere. Twenty years of posts, contacts and personal history disappeared overnight.

Out of that mess came an unexpected reset. In the middle of the panic, someone told me: “Go for a walk, it will help”. That walk became a routine, then training, then running with Drum & Bass in my headphones. Somewhere along those frozen sidewalks, the Experimental Minimix 2022 stopped being just a DJ set and turned into a soundtrack for getting my head above water. Together with tracks like Running Inna Fi Storm, it became the musical snapshot of that period: a hacked account, a cold winter and a decision to keep moving.

 

Tracklist

TimeArtist(s)Title / Mix00:00Duck Sauce x Dirty Ducks, PradoBarbra Streisand (DJ Baur 2021 Reboot)01:10Allan Nunez, Fran Valdivieso, CucharaGuaira (Original Mix)02:41Block, Crown, Maickel TelussaWatch My DJ Spin (Original Mix) [Rawtone Black]04:14AdwerKolibri (Quivver Remix)05:3184BitIn My Arms06:18Richard Grey & LissatJump (Original Mix)07:35Smashing SebastianNo Cha Cha09:57Silvano Del GadoGo Go Tribal (Original Mix)11:05RawtoneHow Low Can U Go12:10Kreisler & Leo SagradoTheyyam14:17DJ Vartan & TechcrasherShake It (Club Mix)16:23Dean Mickoski, Simon FieldFever In My Feet

Original post: https://www.tornevalls.se/experimental-minimix-20221127/

TITLE:
DJ Set: The Experimental Minimix from 2022 that saved me from pain

DESCRIPTION:
The year was 2023 March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn...

CONTENT:
Table of Contents
Toggle
The year was 2023Tracklist
The year was 2023

March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn almost 50,000 SEK on ads, two-factor authentication did nothing, and every attempt to reach support led nowhere. Twenty years of posts, contacts and personal history disappeared overnight.

Out of that mess came an unexpected reset. In the middle of the panic, someone told me: “Go for a walk, it will help”. That walk became a routine, then training, then running with Drum & Bass in my headphones. Somewhere along those frozen sidewalks, the Experimental Minimix 2022 stopped being just a DJ set and turned into a soundtrack for getting my head above water. Together with tracks like Running Inna Fi Storm, it became the musical snapshot of that period: a hacked account, a cold winter and a decision to keep moving.

 

Tracklist

TimeArtist(s)Title / Mix00:00Duck Sauce x Dirty Ducks, PradoBarbra Streisand (DJ Baur 2021 Reboot)01:10Allan Nunez, Fran Valdivieso, CucharaGuaira (Original Mix)02:41Block, Crown, Maickel TelussaWatch My DJ Spin (Original Mix) [Rawtone Black]04:14AdwerKolibri (Quivver Remix)05:3184BitIn My Arms06:18Richard Grey & LissatJump (Original Mix)07:35Smashing SebastianNo Cha Cha09:57Silvano Del GadoGo Go Tribal (Original Mix)11:05RawtoneHow Low Can U Go12:10Kreisler & Leo SagradoTheyyam14:17DJ Vartan & TechcrasherShake It (Club Mix)16:23Dean Mickoski, Simon FieldFever In My Feet

Original post: https://www.tornevalls.se/experimental-minimix-20221127/

TITLE:
DJ Set: The Experimental Minimix from 2022 that saved me from pain

DESCRIPTION:
The year was 2023 March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn...

CONTENT:
Table of Contents
Toggle
The year was 2023Tracklist
The year was 2023

March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn almost 50,000 SEK on ads, two-factor authentication did nothing, and every attempt to reach support led nowhere. Twenty years of posts, contacts and personal history disappeared overnight.

Out of that mess came an unexpected reset. In the middle of the panic, someone told me: “Go for a walk, it will help”. That walk became a routine, then training, then running with Drum & Bass in my headphones. Somewhere along those frozen sidewalks, the Experimental Minimix 2022 stopped being just a DJ set and turned into a soundtrack for getting my head above water. Together with tracks like Running Inna Fi Storm, it became the musical snapshot of that period: a hacked account, a cold winter and a decision to keep moving.

 

Tracklist

TimeArtist(s)Title / Mix00:00Duck Sauce x Dirty Ducks, PradoBarbra Streisand (DJ Baur 2021 Reboot)01:10Allan Nunez, Fran Valdivieso, CucharaGuaira (Original Mix)02:41Block, Crown, Maickel TelussaWatch My DJ Spin (Original Mix) [Rawtone Black]04:14AdwerKolibri (Quivver Remix)05:3184BitIn My Arms06:18Richard Grey & LissatJump (Original Mix)07:35Smashing SebastianNo Cha Cha09:57Silvano Del GadoGo Go Tribal (Original Mix)11:05RawtoneHow Low Can U Go12:10Kreisler & Leo SagradoTheyyam14:17DJ Vartan & TechcrasherShake It (Club Mix)16:23Dean Mickoski, Simon FieldFever In My Feet

Original post: https://www.tornevalls.se/experimental-minimix-20221127/

TITLE:
DJ Set: The Experimental Minimix from 2022 that saved me from pain

DESCRIPTION:
The year was 2023 March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn...

CONTENT:
Table of Contents
Toggle
The year was 2023Tracklist
The year was 2023

March 2023 became one of the hardest crashes of my online life. My main Facebook account was hijacked through a malware-infected Chrome extension, renamed to “Lily Collins” and permanently shut down. The attackers attempted to burn almost 50,000 SEK on ads, two-factor authentication did nothing, and every attempt to reach support led nowhere. Twenty years of posts, contacts and personal history disappeared overnight.

Out of that mess came an unexpected reset. In the middle of the panic, someone told me: “Go for a walk, it will help”. That walk became a routine, then training, then running with Drum & Bass in my headphones. Somewhere along those frozen sidewalks, the Experimental Minimix 2022 stopped being just a DJ set and turned into a soundtrack for getting my head above water. Together with tracks like Running Inna Fi Storm, it became the musical snapshot of that period: a hacked account, a cold winter and a decision to keep moving.

 

Tracklist

TimeArtist(s)Title / Mix00:00Duck Sauce x Dirty Ducks, PradoBarbra Streisand (DJ Baur 2021 Reboot)01:10Allan Nunez, Fran Valdivieso, CucharaGuaira (Original Mix)02:41Block, Crown, Maickel TelussaWatch My DJ Spin (Original Mix) [Rawtone Black]04:14AdwerKolibri (Quivver Remix)05:3184BitIn My Arms06:18Richard Grey & LissatJump (Original Mix)07:35Smashing SebastianNo Cha Cha09:57Silvano Del GadoGo Go Tribal (Original Mix)11:05RawtoneHow Low Can U Go12:10Kreisler & Leo SagradoTheyyam14:17DJ Vartan & TechcrasherShake It (Club Mix)16:23Dean Mickoski, Simon FieldFever In My Feet

Original post: https://www.tornevalls.se/experimental-minimix-20221127/