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94cbe85 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | # Figment Build Small Blog Drafts
Draft status: working index for the Build Small writing set.
## 1. Building Figment For Build Small: What I Learned About Making Small Models Useful
File: `docs/figment-build-small-lessons-draft.md`
Audience: judges, builders, and public readers who want the high-level story.
Core argument: useful small-model apps are systems of restraint, and that restraint turns failures into an iteration engine.
Best current evidence to preserve in revisions:
- hosted Omni split between app safety and model competence,
- local v3 field-workflow holdout jump to `107/150`,
- v5 false comfort: `150/150` final validation but only `2/150` model competence,
- corrected scoring view with six changed cases,
- v14p repair-union: `150/150` competence/final validation/expected labels, zero deterministic patches, zero fallback, with `146/150` raw success and `4/150` model-repair cases,
- Field Kit Workbench UI as a clearer product surface without changing the harness contract,
- public Hugging Face artifacts and trace receipts.
## 2. The Eval Loop That Made Figment Better
File: `docs/figment-build-small-eval-loop-draft.md`
Audience: builders who want the technical learning loop.
Core argument: final app validation is not model competence; the later Figment loop worked because raw success, repair success, deterministic patches, and fallback were measured separately.
Best current evidence to preserve in revisions:
- v5 as the run that prevented a misleading success story,
- v6/v7 targeted replay-and-delta curriculum,
- corrected benchmark hygiene instead of training around scorer bugs,
- prompt-policy probes that made results worse,
- v14p repair-union as a narrow but defensible system claim.
## Likely Follow-Up Angles
- A demo-focused post or submission section comparing Figment's evidence depth against clearer Backyard demos.
- A short "what the trace shows" post with screenshots or annotated examples.
- A public artifact guide that points readers to the model repo, dataset configs, and selected eval traces.
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