AI-Driven Observability for Trustworthy Agents

Four stages that catch 200 OK responses that are wrong, unsafe, or expensive

AI-Driven Observability for Trustworthy Agents Four stages that catch 200 OK responses that are wrong, unsafe, or expensive 01 / Observability lifecycle 02 / Caught by evaluation 03 / Outcomes Observe · OTel spans + traces · Observability lifecycle · capture 01 Observe OTel spans + traces capture Evaluate · judge + safety/cost · Observability lifecycle · score 02 Evaluate judge + safety/cost score Detect · silent failures · Observability lifecycle · 200 OK? 03 Detect silent failures 200 OK? Improve · close the loop · Observability lifecycle · trust 04 Improve close the loop trust Flagged · wrong / unsafe / costly · Caught by evaluation · caught Flagged wrong / unsafe / costly caught feedback Legend active state waiting terminal success failure / exit

Beyond 200 OK

  • • A successful HTTP status says nothing about answer quality
  • • LLM-as-judge scores correctness the transport layer cannot see
  • • Safety and cost metrics flag unsafe or expensive runs

Trust Is a Loop

  • • Detection turns silent failures into visible incidents
  • • Flagged runs drive concrete improvements
  • • Feedback re-instruments the next round, raising the floor

Lifecycle diagram • Built with Archify • Create yours ↗ • Hover to trace • R route • Click to focus • +/− zoom • M radar • T theme • E export