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title: Agentic Scaling Laws Analysis created: 2026-05-27 updated: 2026-05-27 type: concept tags: [research, whitepaper] sources: [raw/papers/agentic-scaling-laws.md]

Agentic Scaling Laws

🎯 The Core Thesis

Scaling compute during inference (test-time compute) yields similar gains to scaling training data.

💡 The Innovation

Introduces ‘Recursive Verification’ where the model generates 10 candidate paths and a separate verifier la-model selects the optimal one.

📈 Key Results

30% increase in complex math reasoning on the MATH-Hard benchmark.

🌍 Implications

Shift in training focus from just ‘more data’ to ‘better verification’ processes.

⚖️ Verdict

High Impact.