Interview Question: How to Evaluate AI Agents
verrsane · x · 2026-07-14
This thread summarizes an interview discussion on AI agent evaluation and system design. The author asked candidates how they evaluate agents: which libraries/frameworks they use, and their understanding of reinforcement learning, environments, and evaluation systems.
The core challenge is scalability: when expanding from 3-5 agents to 3,000, manual inspection of traces and results becomes impossible. Automated, scalable evaluation systems must be established, potentially even using agents to evaluate other agents.
The second question focused on replicating products like Notion using today's tech. The emphasis isn't on knowing how to use Codex or Claude Code, but rather on the ability to deeply integrate these tools into product engineering to solve real business problems.
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