benchmarking

A blog post describing an evaluation harness for comparing agentic coding tools and prompts across realistic SWE tasks, with token-cost results and model-specific behavior notes.

LEVI is a harness-first evolutionary framework for code and prompt optimization. It focuses on reducing LLM cost with diversity-preserving search, role-aware model routing, and a proxy benchmark, and presents comparative results against several existing systems.

A Superconductor blog post showing how background coding agents were used to reproduce, diagnose, and fix a Rails memory leak using derailed_benchmarks, with a reusable Agent Skill workflow included.

A blog post from Archestra analyzing Jev on 100 real AI tool calls, with benchmark results, failure analysis, and comparisons against other models used for annotating agent traces.

A Zenodo preprint reporting a 12,160-trial black-box evaluation of GPT-5.4 outputs under two prompt conditions, with detailed token-ceiling sweeps, control/ablation trials, and hash-chained verification.