I wrote a song about vibe coding (and built the whole music video with AI agents)

I used to write code. Now I write prompts. Then I review the code I didn't write. Then I fix the bugs the AI created.

At some point this year that stopped being a complaint and started being... a chorus. So I made it one - a full 6-minute song about being a developer in 2026:

It has verses about vibe coding, the AI subscription stack ("my wallet says please stop, my brain says one more tool"), and the day I gave my coding agent one tiny task and it opened seventeen pull requests.

The part you'll actually find interesting: the video is agent-built too

I decided the production itself should prove the song's point. Almost the entire music video was produced by an AI agent (Claude Code) working autonomously while I was out:

• The song — generated from my lyric sheet (fun discovery: the generator silently dropped my spoken outro and invented a reprise instead; nobody reads the spec, not even the music AI).
• The shot map — the agent transcribed the finished track with Whisper, cross-checked section boundaries against an RMS energy profile, and turned it into a 60-segment edit decision list with real timecodes.
• The character clips — 16 scenes from an image-to-video model, kept consistent with a 4-image reference kit (full-body sheet, smiling portrait, deadpan portrait, set reference). Every one was approved on the first take, which never happens.
• The screen gags — the fake PR list with 17 open PRs, the "you're almost out of tokens" modal, the receipt wall — all rendered programmatically (PIL frames piped to ffmpeg) because you can't screen-record a browser while you're not home.
• The assembly — a Python EDL driving ffmpeg: per-segment cuts, concat, the song muxed as the timeline master.

Total human contribution to the edit: reviewing takes, catching alignment bugs, and one deeply 2026 code review comment: "the receipts are crooked."

Things I learned that transfer to real work

1. Reference kits beat prompts for consistency. Sixteen video generations with the same face only worked because every prompt attached the same four reference images. Same lesson as agent context engineering: don't describe, attach.
2. Transcribe your media before editing it. Whisper timestamps turned a vibes-based edit into a deterministic script. The whole cut is reproducible from one Python file.
3. Fonts lie. PIL's glyph probe said Helvetica had ✓ and ✗. It rendered tofu boxes. Trust rendered pixels, not APIs — which is basically the song's thesis, applied to typography.

The question the song ends on

The tests are green. I don't know how it works. But hey — the tests are green.

Which verse is your life right now? For me it's the subscriptions one. My credit card knows all the Pro plans by heart.

(Full song: https://youtu.be/TLDh-_AiZVk — and if you want the production pipeline details, the tools are a few hundred lines of Python + ffmpeg; happy to write that up if there's interest.)