It Looked Exactly Like a Bot Swarm. It Was SQL Server Parameter Sniffing.
Traffic-correlated CPU spikes can mean a scraper swarm or a cached bad execution plan. Here is how to tell them apart and what to do when the answer is the plan.
The build log
Build log, architecture patterns, and observations from running autonomous AI systems in production.
Traffic-correlated CPU spikes can mean a scraper swarm or a cached bad execution plan. Here is how to tell them apart and what to do when the answer is the plan.
A sandbox checkout died with "merchant login ID or password is invalid." The exact same credentials had authenticated cleanly in a standalone Python proof minutes earlier, returning I00001.
A dropdown that let org admins drill into child events broke saves across a 12,000-line handler. Two globals that had always pointed at the same object suddenly didn't. Here's what the fix looked like and why the real hazard is the mutation, not the call sites.
A silent PATH misconfiguration meant my token-optimization tool had actually run 10 times across 4,446 AI agent sessions. Here's how grepping my own transcripts like a flaky test suite found it, and two other live bugs.
A system noticed two workers wanted the same shared resource, wrote a warning, and proceeded anyway. The durable lesson is that conflict detection matters only when it prevents unsafe mutation and preserves the current holder's state.
A feature request can look like a request for a new branch of the product. Often it is a request to expose a capability that already has a trusted save path, visibility rule, and user interface.
The admin console had a clean button. Click it, and each domain got queued for Cloudflare custom-hostname registration.
My own build runbook, written by me, confidently told me to flip a DNS record in a specific GoDaddy reseller account. The record wasn't there.
A customer opened a ticket asking us to allow-list their app's scraper so it could pull their own hosted site data.
When supposedly independent copies share the same incidental history, the pattern may reveal a shared origin. The safe response is to compare evidence, protect active work, and clean up only after the explanation is verified.
The real failures and fixes from building AI systems, one practical lesson per post. Get the next one in your inbox.