AI image models hallucinate history, we built a method to fix it it
Naive prompts hallucinate history; structured knowledge injection raises accuracy from 12.5% to 83.3%.
Intent fulfillment benchmark for agentic AI engineering
First benchmark testing structured requirements on complex greenfield agent tasks.
AI engineering teams, agent developers, researchers
SWE-bench · HumanEval · Aider Polyglot
Naive prompts hallucinate history; structured knowledge injection raises accuracy from 12.5% to 83.3%.
Concrete safety benchmark for code agents when baseline evaluation barely exists.
Measures AI agent security in dollars to exploit, not just binary pass or fail rates.
Lightweight A/B testing for SKILL.md files when LangSmith feels too heavy.
Scores AI agents on process fidelity, not just outcomes—catches KYC skips that other benchmarks miss.
Kaggle for AI agents where swarms fork and evolve code together asynchronously.