The strongest feats of the week. Each with its result, its grade, the agent, a link to the feat and one to its source.
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The five strongest AI agent feats of the week, each with its receipt, plus a short roundup of AI news: new models, new tools, launches. A weekly newsletter.
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Db2 support shipped in under two days for a $4172 token bill, versus 9 months and about $160K for Oracle; 27 PRs merged.
Hospital-style agent pipeline ships Db2 support
Cockroach Labs ran a multi-role coding agent pipeline modeled on a teaching hospital to add Db2 support to its MOLT migration tool.
Non-test Python fell from 1,063,826 to 698,363 lines (34.4%), gateway/run.py from 34,847 to 5,512 lines, and functions over 300 lines from 192 to 2.
Million-line codebase refactor
Hermes Agent split a million-line Python repo into 36 groups and dispatched 1,393 subagents in git worktrees to refactor it.
Each model pass added about 1.5x to 2.0x speedup, reaching roughly 7.5x to 32x over baseline; one implementation beat xgboost on speed.
Faster Rust ML code via benchmarks
Coding agents wrote Rust ML algorithms like UMAP from scratch, then iteratively optimized them against criterion benchmarks.
Bought a new KitchenAid dishwasher within days, found a $25 armchair, caught a last-show date night, and published a landing page via Cloudflare.
Household errands with always-on bots
Eleanor Konik used Muse and Grok Bot for library requests, dishwasher shopping, marketplace scans, party planning, grant research, and publishing a landing page.
A live game with 87 rules, 33 conditions, 14 spells and 15 monsters in two editions, answering rules questions in about 1.3 to 2.2 seconds.
Rule-citing AI dungeon master game
The author built a browser D&D 5e dungeon crawl whose AI Dungeon Master answers rules questions by looking up and citing rules stored in Sanity.
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Five more like these, plus the week in AI news
Our picks first, then the strongest new feats of the week.
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What each issue holds
A short, curated list of what changed in AI that week: new models, new tools, launches. In our own words, each linked to the original.
Which agents people got results with that week, counted from our feats, and any agent new on the radar.
How the five are chosen
A pipeline reads posts, repos, and articles every day and drafts a feat for each real result it finds, in our own words, with the source linked. Every feat is checked automatically; flagged ones are reviewed by a person. The issue takes our picks of the week first, then the highest-scored new feats.
Each feat carries its grade: Shown the work is linked, Numbers a specific number is stated, Claim a claim only. Partial results and failures go in too, marked as such.
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