WhatA platform that lets AI teams systematically test, compare, and optimize the scaffolding (tool use, task decomposition, auto-critique) that surrounds foundation models for complex reasoning tasks.
SignalCommenters note that scaffold design causes huge variance in model performance and makes model comparisons murky — there is no standardized way to evaluate or optimize the harness around a model, only the model itself.
Why NowAs models converge in raw capability, the scaffold layer has become the primary differentiator in real-world performance, yet no tooling exists to systematically optimize it.
MarketAI labs, enterprise AI teams, and research groups building agentic systems; ~$2B+ spent annually on AI evaluation and MLOps tooling; current eval platforms (Braintrust, LangSmith) focus on prompts, not scaffolds.
MoatNetwork effects from a shared benchmark registry and accumulated data on which scaffold patterns work best for which task types create strong switching costs.
Epoch confirms GPT5.4 Pro solved a frontier math open problemView discussion ↗ · Article ↗ · 461 pts · March 24, 2026
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