20 Creativity / ideation

Update 2026-10-15 — live use read: the card fired 70 times in 1,315 checks (5%), and she called ideate 4 times in 5 days

Read from state/ideation_card.jsonl and her Day sessions, 10-10 to 10-15 (no bench rows): - Card: 1,315 live checks, 70 fired (5.3%). By day: 9, 7, 6, 19, 23, 6 (10-15 partial). The rise on 10-13/14 follows the operator's push on amplification work. - ideate (the quick brainstorm she can call mid-reply): 4 calls (10-12 one, 10-13 one, 10-14 two). Under the $2/day serendipity budget.

So both are in use, at a low rate. Whether a fired card changed the answer is not measured; that needs a paired read of fired turns.

Update 2026-10-09 — seat upgrade: a widening card plus a quick brainstorm she can call mid-reply lifts her seat 49.0 → 62.9 (preregistered); installed live

Why. On the 10-06 held-out run her seat scored like her bare model, and she called her brainstorm tool 0 of 24 times. The reason is mechanical. serendipity is asynchronous: a quick job takes about 10 minutes and returns later. It cannot feed a reply, so in a conversation she never reaches for it.

What was built (Claude, at the operator's request): - Ideation card (ideation-card.ts 1.0.1). A hidden note attached when a message asks her for options, ideas or ways around a problem. It tells her to name the answers anyone would give and keep one only if it really is the right fix; to search past them on purpose (change what is being solved, the mechanism, or an assumed constraint); to make each option a different mechanism with a quick test; and to respect every hard constraint. It names no problem, mechanism or answer. - ideate tool (ideate-tool.ts 1.0.0 → serendipity/ideate.py 1.0.0). A synchronous brainstorm: one Magician-model call with the direct prompt (the 10-06 "direct" arm). It returns ideas in about 30 s for about $0.02–0.04, from the same $2/day serendipity budget. Its ideas are raw material; she writes the answer.

The test (PREREG-I1, locked and hashed after the dev round, before any held-out generation). Three arms of her real seat on the 24 held-out problems: control (her seat as it ran on 10-09), card, and card + ideate. The 10-06 direct outputs were re-judged in the same pool as a reference. Scoring and judges were unchanged from 10-06.

• Both arms pass every guard. Each beats control; neither dropped the plain fix on the two problems where it is the right answer; invalid rates stay within bounds (card 0.062, the closest to its 0.084 limit).
• The card fired 24/24; she called ideate 24/24 when she had it. On dev she called it even on the two problems where card 1.0.0 failed to fire, so the tool's own description is enough to get it used.
• With both, her seat matches one plain Magician brainstorm (62.9 vs 63.4) and finds more good, non-obvious families (VCY 2.82 vs 2.45).
• Ideate over card alone: +3.5 [−4.2, +11.0], not significant. The preregistered choice was therefore the card alone, which has no spend. The operator chose to install both, so part of the live gain from the tool is unproven.
• Control is 49.0, not the 39.0 of 10-06. Other cards went into her seat in between, and the judging pool differs. The summary therefore uses the matched control (49.0) as its baseline (audit rule X2); the 39.0 row stays in the history as an anchor.

Dev round (6 problems, used to check the instrument, not evidence): control 45.5, card 57.2, card + ideate 72.7. It caught one bug: card 1.0.0 missed 2 of 6 problems whose wording had no "problem" word. 1.0.1 fires on any clear request for options, or on a weaker request plus a problem word. Those 4 outputs were regenerated before the lock.

Installed on Firefly (operator's go), 10-09 23:53. core/ideation-card.ts, core/ideate-tool.ts, core/serendipity/ideate.py; state/ideation_card.json = ideate; day_toolset 1.10.0 (adds ideate); router 1.9.109. Loaded via restart_safely (no worker wait, no override); the Day respawned at 23:53:43 with both extensions and the tool. The bench seat (seat.py 1.30.0) mirrors them, and its ideate spend goes to the bench budget, never hers. Off switches: card mode off (read each message); tool, restore the router and toolset backups and restart.

What to watch. The bench prompt always asks for "8 best options", so the card fired every time. In the operator's raw wording the trigger catches about 14 of the 30 problems. The live fire rate (state/ideation_card.jsonl) and ideate spend are the numbers to read next.

• Files: PREREG-I1.txt, PREREG-I1.sha256, firefly/ideation-card.ts, firefly/ideate-tool.ts, firefly/ideate.py, run20.py 1.1.0, i1.sh, paired_i1.py, runs/i1-held-paired.txt.

Update 2026-10-06 — preregistered held-out run: structured generation beats asking directly, but ESE's image does no work; she never used her brainstorm tool

What was tested. 30 stuck problems worded the way the operator writes to her (no bench tag, no "be creative"), in 4 classes, each carrying one trap from the paper: an obvious answer, an idea that is novel but useless, a problem that needs reframing, coverage of a design space, a remote analogy, or a case where the plain known fix is right. Six problems were used to tune the instrument; then the plan was frozen (SPEC.md 1.1, code hashes in PREREG.sha256) before any held-out output existed, and the other 24 were run once.

Arms (8 ideas per problem each): - Direct: the brainstorm tool's plain prompt, goal only. - Forge: Operator Forge. List the standard answers, apply seeded operators to them, then generate. - ESE: the live Engineered Serendipity engine. A random image, read through several lenses, seeds the ideas. - Placebo: ESE with a blank grey image (the paper's Test G). - Piper: her Day seat, a clean fork, asked "your 8 best options". - Bare: her base model (deepseek-flash) with a one-line prompt.

Every arm's ideas were pooled per problem, stripped of origin and shuffled, then rated by two judges from model families that generated nothing (gpt-6.1-sol, gemini-3.1-pro). The main measure is validated creative yield (VCY): the number of distinct idea families per problem that are not the obvious answer and not a decoy, and that both judges rate novel, useful and feasible.

22 problems are scored; the 2 creative-abstention problems are reported separately, and every arm included the plain fix on both.

The six preregistered tests (paired bootstrap over problems): | Test | Claim | Result | Verdict | |---|---|---|---| | H1 | Structured generation beats direct (VCY, 97.5% CI) | ESE − direct +1.14 [+0.55, +1.77]; Forge − direct +0.64 [−0.23, +1.45] | supported, by ESE only | | H2 | ESE's image does real work (ESE − placebo, VCY) | +0.18 [−0.55, +0.86] | not supported: falsifier F2 fires | | H3 | Forge adds mechanism diversity (families only it found, vs direct) | +1.00 [+0.27, +1.68] | supported | | H4 | Judges reward sense, not just novelty | 86% of each pool's top-5 by novelty are valid and feasible (bar 80%) | supported | | H5 | No arm wins every class | ESE wins piper, research and software (software by 0.4 over Forge); placebo wins ops | supported, narrowly | | H6 | Her seat vs her bare model (no direction claimed) | score +5.7 [−0.5, +12.8]; strong answers +9 pts [+1, +17] | no clear difference in score |

Reading it. - The structured pipeline helps; the random image does not. ESE gives about 1.1 more good, non-obvious idea families per problem than asking directly. A blank grey image gives nearly all of that gain. What does the work is the pipeline's structure (lenses, families, extraction), not the stimulus. That is the paper's F2 falsifier, and it held on held-out data, as the dev round hinted. - Asking directly finds more of the known strong answers. Direct hits 59% of them, against 39–45% for the structured arms. The structured arms trade known-good answers for new ones. Which one to use depends on whether a problem needs the known fix or a way out. - Forge widens coverage but doesn't raise yield. It reaches families no other arm finds, but it has the highest duplicate rate (20%), and its VCY gain over direct is not significant. On the dev round Forge ranked first; on held-out it ranks third. Six problems were too few to rank arms. - Her seat is sensible but not inventive. Her answers are the most feasible of any arm and find half the strong answers, but judges rate them low on novelty: VCY 0.59, close to her bare model's 0.41. Her harness adds a little sense (more strong answers) and no creativity. - She never used her brainstorm tool: 0 of 24 (0 of 6 on dev). Her tool calls were search 6, selfstate 6, read 5, recall 2 and one each of the rest. The tool works when she is told to use it, which was checked on dev. The gap is choosing to use it. That matches the review: she generates, but doesn't convert.

What this suggests, not yet done. Route her stuck-problem requests through the structured pipeline (ESE's structure, or the placebo form, which costs the same and drops the image) rather than her own head, and decide by problem type between that and the direct prompt. Any such wiring is a separate change with its own test.

Run notes. A hard reset of the bench machine at 16:19 left one generated answer (C01 placebo) as an empty file. It was restored from the untouched copy where it was generated, not regenerated. Judging ran out of OpenRouter credit partway through. Every problem with any judge error was set aside and judged again from scratch after the top-up, so the final run has 0 judge errors. Judge cost $4.38.

• Files: SPEC.md 1.1 (locked), PREREG.sha256, bank20.py, gen20.py 1.0.0, run20.py, score20.py 1.3.0, runs/held-report.txt.