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Production evidence for the age of AI-written code.

Guides

Monitoring AI agents that run on serverless functions

An agent run on serverless is a chain of short invocations, each with its own time limit. Here is what to watch at every link, with three small experiments to show where the signal gets lost.

Andrew Babo6 min read

Guides

How to send production errors to an LLM safely

Error events hold secrets, personal data and text users typed. We sent one with a hidden instruction to four models 72 times; pasted raw, one model obeyed every time and once said to turn off auth.

Andrew Babo6 min read

Engineering

How to evaluate an AI debugging tool: run its fixes

Every failing fix in our test said it was fixed, came with a passing test and rated itself 92 to 100. Only running the customers' input showed which still crashed. A protocol for your own bugs.

Andrew Babo5 min read

Engineering

AI agent observability: the failures that still return 200

We ran a support agent 60 times with seeded failures. Every failed refund returned HTTP 200 and reached no error tracker. Only the trace showed it, and customers heard the truth in 13 of 30 failures.

Andrew Babo4 min read

Engineering

Observability MCP gives an agent access, not a diagnosis

We gave three AI models an error tracker over MCP and one question. All found the right issue. Only some found the cause, and with a write tool most resolved a bug that was still live.

Andrew Babo7 min read

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