Operations | Monitoring | ITSM | DevOps | Cloud

It's 2:47 AM. PagerDuty fires. You open a Slack alert and see: p99 latency spike on checkout-service. You SSH into the host, check dashboards in four tabs, grep logs for the last 20 minutes, and eventually find a slow query introduced in a deploy six hours ago. It took 34 minutes. You resolved it, w Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.

For those of us using tools like Claude Code, Codex, or Gemini, we already know they’re powerful. They can write code, refactor functions, open PRs, even run commands. For a lot of developers, they’re already part of the daily workflow. But once you zoom out beyond the individual developer, the biggest problem isn’t productivity. It’s control. AI coding tools are powerful, but they introduce a new, unpredictable cost layer that most teams don’t fully understand.

Documentation search is often the last thing devs think about, until someone posts publicly that they couldn't find a basic answer, or your support queue fills up with things that are genuinely in the docs. We decided to get ahead of that. This is the story of how we went from a minimal keyword-only search on our docs to a conversational Ask AI experience.

AI coding agents are fast. They generate functions, refactor modules, and wire up boilerplate faster than any human. What they don’t do by default is enforce the conventions a specific team has agreed on: the lint rules, the review patterns that senior engineers flag on every PR. A generated diff looks clean until someone runs CI or reads it carefully.