The Missing Layer After Launch - Raphael Kalandadze, Wandero AI
Jul 5, 2026 · 19:33
Raphael Kalandadze, CTO of Wandero AI, argues that shipping an AI agent is the easiest part and the real work begins post-launch, requiring a closed-loop monitoring system built with agents themselves. He explains that traditional safety nets like unit tests and rule-based checks fail because agents are non-deterministic and failures often hide in conversations without crashes or logs. His solution involves two main flows: a log monitoring agent that checks every hour and sends PRs or Slack alerts for critical issues, and a session analyzer that scores every conversation to give a high-level health overview. A computer-use agent simulates customers to catch UI problems. Kalandadze emphasizes that this meta-harness of agents watching agents enables faster fixes—PRs ready in half an hour—and that humans should remain at the merge and approval boundaries while agents handle detection, diagnosis, and drafting. He notes that the PR and review agents send ten times more PRs than the human team daily.
