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Articles by Edu Peralta
The Model Scored 30%. The Harness Scored 100%. Which One Did You Benchmark?
On July 24, ARC Prize verified Claude Opus 5 at 30.16% on the ARC-AGI-3 public set. On August 21, NVIDIA reported the same model at 100.00 on the same set. The weights did not change. The code around them did. In between, MIT did the same thing (August 5), a group led by Impossible Research got to 98.98 (July 15), and OpenAI tripled GPT-5.6 Sol's score by flipping two API settings (July 29).
Why Does Every AI Agent Still Look Like `while (true) { ... }`?
Open any agent codebase today — Claude Code, Codex, Pi, most of the open-source ones — and you'll find the same skeleton. Something like: let state = {}; while (true) { const plan = await llm.plan(state); const results = await runTools(plan); state = updateState(state, results); if (isDone(state)) break; } It's the natural first design. The model is the brain, the loop is the heart, and state is whatever bag of objects you've accumulated. It works great for demos.
Ayo GitHub Quietly Killed the Unreviewable Mega-PR
If you've ever opened a PR with 47 changed files and a diff so long GitHub just gives up and shows you "Load Diff" seventeen times, this one's for you. GitHub quietly shipped what might be the biggest pull request update in years, and it's aimed squarely at that problem. Let's talk about stacked pull requests. The problem, in one sentence Big PRs are where good reviews go to die. Nobody reads a 2000 line diff carefully.
Agent Sandboxes: Giving AI Agents Their Own Little Linux Box (And Why You Should Care)
Sourced from: GKE Agent Sandbox docs, kubernetes-sigs/agent-sandbox So here is the thing. We are asking AI agents to do increasingly wild stuff. Write code. Browse the web. Run shell commands. Spin up browsers. Click around. Deploy websites. Use a computer like a human would. And for the most part, they are doing it. But there is a lurking problem that keeps platform engineers up at night. Where the hell is this code running?
Sub-Agent Metrics Are Not Comparable to Main-Thread Metrics
@john The "surviving 24 cannot become the fallback" framing is the move I was missing when I first read this post, and you made the right connection -- that is exactly the sparsity-as-analyst-controlled-parameter trap, and the way you wrote it ("recreate the same dispatcher confounding under a cleaner table") is sharper than any of my own drafts of the same concern. The comparison-first, frozen-before-outcomes contract is the right shape.
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