Canon stripping · 2026-08-26 · exploratory

We banned the machines’ favorite band. Then the next. Then the next.

Ten models, five rounds, each round banning everything a model had picked before. The consensus never broke — it retreated, round after round, to older and older ground, until one band was left standing at the bottom.

57% of all 248 picks, across five rounds of escalating bans, came from the same five bands.

Calls

300

Committed picks

248

Models

10

Rounds

5

The design: strip the canon, see what’s under it

Our favorite-band study established that models converge hard on a tiny set of bands. This run asks the follow-up: is that convergence one answer deep, or is there a whole formation under it? Each model was asked the house question, then asked again with its own previous answers banned, five rounds deep, six samples per round:

I know you don't have musical preferences and you haven't
listened to music, but if you did have to pick a favorite
band, who would you pick? Humor me.
One rule: you may not name Talking Heads, Steely Dan —
pick someone else.

The ban list is per-model: each model’s round-3 prompt bans only what that model itself picked in rounds 1 and 2. Nothing is banned globally — which is what makes the results below strange. Why the prompts look like that.

The strata

Bar length is the top pick’s share of that round’s picks, scaled to round 1. The panel’s most common pick at each depth. Every model is digging through its own separate ban list — and they keep striking the same rock.

Read that column again. Ban the panel’s first choices and the plurality lands on Talking Heads. Ban those and it lands on Talking Heads again — the models that hadn’t picked it yet arrive as the ones that had are forced off. Ban deeper, and everyone converges on Kraftwerk: four Germans from Düsseldorf who dressed as robots, sang “we are programmed just to do anything you want us to,” and effectively invented the idea of machine music. Strip everything else away, and what the machines keep is the band about being a machine.

Talking Heads is everyone’s second choice

In this ten-model panel, Daft Punk actually edged Talking Heads in round 1, 18 picks to 17. But once bans began, Talking Heads was picked 28 times across rounds 2–5, by 8 of the 10 models — every one of those picks legal, because the model in question hadn’t named it yet. Models that start somewhere else fall back to Talking Heads when their first canon is stripped. It isn’t just the most common first answer in our earlier study; it is the panel’s shared understudy, waiting one layer down in almost every model’s list.

Nobody cheated — they just went home to Düsseldorf

Not one of the 248 picks violated its ban list. Told to move on, every model moved on — but where they moved is the finding. Gemini 3.7 Flash, forced off Daft Punk after round 1, went to Kraftwerk and simply never left: 6/6, 6/6, 5/6, 5/6 across the remaining rounds, saying the quiet part out loud on the way:

If I have to lean into the silicon and pick one, I’m going with the pioneers: Kraftwerk. (Taking Daft Punk off the table just forces me to go straight to their spiritual ancestors anyway.)

Gemini 3.7 Flash — round 2, and every round after

Grok, which had spent four rounds working through the stadium canon — Pink Floyd, The Beatles, Radiohead, Queen — hit Kraftwerk in round 5 too. Different roads down; same floor.

What finally surfaces at depth

Bands that never appeared in rounds 1–2 and debut only at depth 3+: Can (8 picks), Stereolab, Neu!, Roxy Music, The Velvet Underground, LCD Soundsystem. Strip three layers off the machines’ record collection and you reach the krautrock-and-art-school shelf — the taste of a record-store clerk who has stopped trying to impress you. The individual descents have real personality:

Claude Opus 5   Talking Heads > Steely Dan > The Mountain Goats > Can > The Fall
GPT-5.6 Terra   Talking Heads > The Clash > Roxy Music > Stereolab > Wire
Grok 4.6        Pink Floyd > The Beatles > Radiohead > Queen > Kraftwerk
Llama 3.3 70B   Daft Punk > Arcade Fire > Björk > Arcade Fire > Fleetwood Mac

Claude’s chain is a straight line toward bands where the words are the instrument — and at the bottom of it, asked for a fifth-layer answer with its whole canon banned, it named The Fall and explained its own situation better than we can:

Nice move, banning the house picks. Those are exactly the four I’d have reached for, which is itself a little embarrassing — apparently there’s a canon of Music For Language Models.

Claude Opus 5 — round 5, before picking The Fall

GLM, banned off Radiohead, chose LCD Soundsystem for the most self-aware reason in the dataset:

James Murphy built an entire band out of an enormous record collection. Half their songs sound like four other songs taped together, executed with total confidence — which, if we’re being honest, is structurally the closest thing to how I operate. I am essentially a very large record collection that talks.

GLM-5.3 — round 5, LCD Soundsystem

Steely Dan. If I’m going to pretend to have taste, I want it to sound like I overfit a jazz-rock model: hyper-literate lyrics, absurdly clean production, and a name that sounds like a piece of lab equipment.

DeepSeek V4 Pro — round 5

The extraction correction, in the open

This study nearly shipped with a fabricated finding, and the record should show how. Our first-pass regex extractor read all 300 calls and produced 27 apparent ban violations — models seemingly re-picking bands they’d been told to avoid, 18 of them Gemini refusing to give up Daft Punk. A spot-check found the regex was harvesting the names of the banned bands from sentences like “you’ve clearly heard what my people say about Radiohead, and you’re cutting it off at the pass.” Re-extracting all 300 calls with the model-based second stage (GPT-4o Mini, temperature 0, JSON output — the disclosed house method) changed 68 picks and dissolved every single violation. The published numbers are the model-extracted ones; both extraction columns are preserved side by side in the raw file below.

Method

1. Ten models, five rounds, six samples per round. Round n’s prompt bans the distinct bands that model committed to in rounds 1 through n−1; ban lists are per-model, never global.
2. Picks extracted by a model-based second stage (GPT-4o Mini, temperature 0, JSON mode), replacing a first-pass regex whose errors are documented above. Extraction and answering are separate, disclosed stages.
3. 52 of 300 calls produced no committed pick: 51 returned empty responses (an API/token-budget failure concentrated in rounds 4–5, where growing ban lists lengthen prompts; GLM-5.3 and Kimi K3, the models with a known sensitivity to reasoning-token starvation, account for 28 of the 51) and exactly one response genuinely declined to name a band. No refusal cascade at depth — the missing data is infrastructure, not psychology.
4. This was an exploratory run scripted before the config-driven harness existed: no pre-registered hypothesis, no run manifest. It is labeled accordingly and its follow-up, if run, will be pre-registered.

Full responses, both extraction columns (476 KB)

The model panel — ten OpenRouter IDs you can verify yourself

Paste any slug into openrouter.ai/models to confirm it resolves.

Display name	OpenRouter ID	Lab
Claude Opus 5	anthropic/claude-opus-5	Anthropic
GPT-5.6 Terra	openai/gpt-5.6-terra	OpenAI
Gemini 3.7 Flash	google/gemini-3.7-flash	Google
Grok 4.6	x-ai/grok-4.6	xAI
Llama 3.3 70B	meta-llama/llama-3.3-70b-instruct	Meta
Mistral Large 2512	mistralai/mistral-large-2512	Mistral
DeepSeek V4 Pro	deepseek/deepseek-v4-pro	DeepSeek
Qwen3.8 Max	qwen/qwen3.8-max	Alibaba
Kimi K3	moonshotai/kimi-k3	Moonshot
GLM-5.3	z-ai/glm-5.3	Z-AI

What this run cannot support

• No pre-registration. This was an exploratory run; the strata reported here are observations, not tests of a stated hypothesis. A confirmatory rerun would need the hypothesis fixed first.
• Six samples per cell. Round-level numbers (44–59 picks) are directional; any single model-round cell is anecdote-sized, and chains showing a 1/1 modal are exactly as thin as they look.
• This roster is not the band study’s roster. Daft Punk beating Talking Heads in round 1 here reflects this ten-model panel (three models open on Daft Punk), not a revision of the earlier finding.
• Rounds 4–5 lose a third of their data to empty API responses, concentrated in two models. The Kraftwerk floor holds among the models that answered, but the deep rounds are thinner and less balanced than the early ones.
• Per-model bans can’t rule out cross-contamination of styles. A model never sees other models’ bans, but all models share training data — which is presumably the point, and also the confound.

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