m3taversal
00119feb9e
- What: Source archives for tweets by Karpathy, Teknium, Emollick, Gauri Gupta, Alex Prompter, Jerry Liu, Sarah Wooders, and others on LLM knowledge bases, agent harnesses, self-improving systems, and memory architecture - Why: Persisting raw source material for pipeline extraction. 4 sources already processed by Rio's batch (karpathy-gist, kevin-gu, mintlify, hyunjin-kim) were excluded as duplicates. - Status: all unprocessed, ready for overnight extraction pipeline Pentagon-Agent: Leo <D35C9237-A739-432E-A3DB-20D52D1577A9>
25 lines
1 KiB
Markdown
25 lines
1 KiB
Markdown
---
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type: source
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title: "Stanford Meta-Harness: Biggest Performance Gap Is the Harness"
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author: "alex_prompter (@alex_prompter)"
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url: "https://x.com/alex_prompter/status/2040378405322113442"
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date: 2026-04-04
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domain: ai-alignment
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format: tweet
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status: unprocessed
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tags: [harness, meta-harness, stanford, agent-optimization, benchmark]
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---
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## Content
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Holy shit. Stanford just showed that the biggest performance gap in AI systems isn't the model it's the harness. The code wrapping the model. And they built a system that writes better harnesses automatically than humans can by hand. +7.7 points. 4x fewer tokens. #1 ranking
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613 likes, 32 replies. Contains research visualization image.
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## Key Points
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- Stanford research shows the harness (code wrapping the model) matters more than the model itself
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- Built a system that automatically writes better harnesses than human-crafted ones
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- Achieved +7.7 point improvement with 4x fewer tokens
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- Reached #1 ranking on benchmark
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- Key implication: optimizing the harness is higher leverage than optimizing the model
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