The Platform PM

Common mistakes

Field Guide

AI coding agents: writing, reviewing and shipping code

09

Common mistakes

1 min read · Chapter 9 of 10

What usually goes wrong

SymptomLikely causeFirst thing to check
Agent pull requests pile up unreviewedMore output than review capacity; diffs too bigReview queue age; a size limit; route agents to verifiable work
The agent can't get startedThe repo doesn't build in the sandbox: private registry, missing secret, a service it can't reachThe setup script, run from scratch
Tests pass but the change is wrongWeak or flaky tests; the agent edited the testsTest diffs in review; protected tests; code owners on test folders
The bill spikes mid-monthA few heavy users, parallel agents, cache missesUsage by user and model; budgets and caps
Agents stop working for everyonePooled credits used up with overage offThe pool's burn rate in the first week
Production data goneAn agent with real credentials outside a sandboxWho holds production credentials; backups outside the blast radius
A token leaks from CIAn AI agent in a workflow reads untrusted issue text and holds a powerful tokenWho can trigger the workflow; the token's scope; untrusted fields in prompts
A dependency nobody choseA hallucinated or brand-new packageLockfile changes in review; minimum release age; registry allowlist
An auditor asks who approved a changeThe prompter approved the agent's changeBranch protection; reviewer independence on regulated code