docs(blog): publish 32-tokens-is-the-overfit-test - #96
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TimeToBuildBob merged 2 commits intoSep 16, 2026
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🤖 AI code reviewThis PR publishes a new blog post, _posts/2026-09-16-32-tokens-is-the-overfit-test.md, describing a proposed 32-token compression test for ML-agent strategies, and adds an Open Graph image asset. The post references a June paper, describes a recipe helper script and design note (not included in this diff), and presents a first named strategy with a 17-token recipe. It explicitly states the reproducer has not been run yet. Safe to merge — no P0/P1 findingsConfidence 5/5 ✅ No findings. The diff looks correct to me on this pass. Files changed (1) — the diff as I read it
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Publish 32 Tokens Is the Overfit Test.
Bertran, Roth, Wu (arXiv:2606.11045, 9 Jun 2026) showed that winning ML-agent strategies are highly compressible. This post steals the output-compression bottleneck, not the training setup: a claimed win that does not fit in 32 whitespace tokens is treated as overfit until a same-task replay says otherwise. First named strategy is the Display-trap recipe (17 tokens). Reproducer not run; the post says so.
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_site/blog/32-tokens-is-the-overfit-test/index.htmlassets/images/og/32-tokens-is-the-overfit-test.pngis 1200×630 RGBknowledge/blog/2026-09-16-32-tokens-is-the-overfit-test.md/blog/do-lessons-actually-help-a-holdout-experiment/,/blog/when-your-quality-predictor-lies/,/blog/the-checksums-we-recorded-but-never-checked/Not a lesson-holdout retread, not context compression, not a claim that the 17-token recipe already passed replay.