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Schema Harness Achieves ~99% on Arc‑AGI‑3 Public
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Overview
Schema enables frontier models to function like physicists by allowing them to write executable programs for game mechanisms, test these programs against reality, and plan within them. This method has achieved approximately 99% accuracy on the ARC-AGI-3 public benchmark.
Summary from schema-harness.github.io.
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schema-harness.github.io
Schema Harness Achieves ~99% on Arc‑AGI‑3 Public
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Community reactions
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Hacker News · schema-harness.github.io
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Based on 5 sampled comments from this thread. Analyzed 2026-07-17.
- Praise: Achieving ~99% on Arc-AGI-3 in under six months is a major milestone, showcasing rapid advancements in frontier AI capabilities.
- Praise: The idea that models could eventually self-engineer tools indicates a future where AI becomes more autonomous and efficient in problem-solving.
- Praise: Improvements in harness engineering could lead to dramatic extensions in AI capabilities, which is exciting for the future of AI applications.
- Concern: Skeptics argue that relying on models to create custom harnesses from scratch is wasteful and inefficient, raising concerns about practicality and costs.
- Concern: Some commenters believe that the current measures of success might be misleading, as the harness might not reflect true advancements in AI intelligence.
- Concern: There's a worry that using a simulator to achieve high scores could be seen as 'cheating' rather than a genuine reflection of AI capabilities.