evals-engineering

Use cultivar to test your Agent Skills and Docs by running them in sandboxes, and across different agents.

Optimize and run consistent AI Functions.

Typed, unit-test-style evaluations for LLMs, agents, and other ML applications—with flexible datasets, scoring, and local reports.

A local-first personal assistant that shows the four pillars behind every serious agent: Harness · Loop · Memory · Eval/LLM-Ops. No frameworks hiding the critical parts.

THE AI EVAL MINDSET EXPANDED: The Engineering Blueprint for Testing, Calibrating, and Monitoring Production AI

Local AI server for refit (OpenAI, Anthropic, Gemini).

Salary benchmarks, CI/CD regression testing pipelines, OpenTelemetry standards, and enterprise rubrics for LLM Evals Engineers in 2026.

Pithom Labs Blog

Awesome list for eval engineering (evals engineering): tools that automate LLM evals and agent evals, turn traces into test cases, and calibrate LLM-as-a-judge.

Ship AI agents with evidence. Open-source evals for LLMs, RAG, tools, and conversations. Use Claude Code, Codex, or your own Python code. Get tracing, continuous checks, regression detection, and local alerts, with agent-assisted setup or full SDK control. One independent engine. Zero third-party runtime dependencies.