# agent evaluation Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/agent-evaluation
> Markdown URL: https://aitinkerers.org/technologies/agent-evaluation.md
> Technology record last updated: 2026-07-11T19:29:07Z
> Generated: 2026-09-21T02:56:05Z

Automated, span-level evaluation to score every tool call, reasoning step, and multi-turn decision your AI agents make before they hit production.

AI agents do not fail like traditional LLMs: they make a sequence of autonomous decisions where a single bad tool call or warped reasoning step cascades into a total system failure. Evaluating only the final output is like grading a math exam by looking solely at the last number. Confident AI (the enterprise platform powering the open-source DeepEval framework) solves this by scoring the entire trajectory. It tracks and evaluates intermediate steps, tool parameters, and multi-turn trajectories using over 50 research-backed metrics. By integrating directly into your CI/CD pipeline, the platform replaces subjective vibe checks with rigorous, automated regression testing, helping teams ship reliable autonomous agents with production-grade confidence.

- Official technology site: https://www.confident-ai.com
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Testing Probabilistic Agentic Systems](https://seattle.aitinkerers.org/talks/rsvp_rAgDGYzTRs4)

Vaibhav explains why agentic systems need evaluation methods that account for probabilistic behavior, distribution shifts, and machine-speed execution. Using Face ID's COVID-era failure and examples of traditional tests missing real-world behavior, he shows how to test agents beyond deterministic pass/fail checks.

- Event context: AI Dev Tool Track — Seattle Meetup - April 13th, 2026 — 2026-04-14 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_rAgDGYzTRs4

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- [probabilistic systems](https://aitinkerers.org/technologies/probabilistic-systems) ([Markdown](https://aitinkerers.org/technologies/probabilistic-systems.md)) — 1 public demo