Schema Harness Claims High Score on ARC-3
we_are_mammals · reddit · 2026-07-17
The post introduces a new harness named Schema, which claims to achieve exceptionally high scores on the ARC-AGI-3 Public set without modifying model weights. It does so by altering observation modeling, history verification, and plan execution/revision processes.
Reported results include hitting 99% with Claude Opus 4.8 and Fable 5, and 95.35% with GPT-5.6 Sol. The author details a fixed fallback rule: run the stronger configuration first, and if a level falls below a threshold, rerun it with an even stronger config, keeping the highest score per level.
Related event: Schema Harness Sparks ARC-AGI-3 Debate(14 posts)→
More from coding & agent
- Building a Secure AI Agent Gateway: Self-Hosting OAuth for Multiple SaaS Apps — Defiant_Cod_2654 · 2026-07-22
- Rowboat launches as an open-source, local-first AI coworker with memory — ycombinator · 2026-07-22
- Scoble says AI “loops” really means long-running multi-agent workspaces — Scobleizer · 2026-07-22
- Kimi Code opens a waitlist as Moonshot rolls out its coding product — Fabulous_Bonus_8981 · 2026-07-22
- Open-source runtime lets each repo define its own AI code reviewer — ibabufrik · 2026-07-22
- Indie Dev Asks: What's Actually Broken in Your AI Agent's Memory Today? — AcceptableTime7937 · 2026-07-22