Operations | Monitoring | ITSM | DevOps | Cloud

A few months ago, Darragh Curran, CTO at Fin (formerly Intercom) set a public goal to double productivity and nearly tripled it instead. They did so by pulling a few levers: AI writing code at scale, building an AI-driven PR review system, leveraging as a trust mechanism, and with leadership becoming more hands-on through the transition. Charity wanted to pick Darragh’s brain on the messy bits, not just the highlight reel, so she invited him to participate in our first episode of Leading With Observability.

It started with a single log line taking up a massive amount of volume: 500 million emissions per hour. Pulling that thread led Emma and Steven into Slack's broader logging pipeline: 311 billion logs per day at 4.4M/sec peak, with no volume limits, no per-service attribution, and no feedback to the teams generating the noise.

'The runbook lost. The trace is the documentation now.' In his O11yCon 2026 closing keynote, Corey Quinn of Duckbill Group makes the case that when your primary reader is an, not a person, are the only pillar built to survive.

It started with a single log line taking up a massive amount of volume: 500 million emissions per hour. Pulling that thread led Emma and Steven into Slack's broader logging pipeline: 311 billion logs per day at 4.4M/sec peak, with no volume limits, no per-service attribution, and no feedback to the teams generating the noise.

Stripe shares lessons from building an incident investigation agent, from context-window blowups to why the final 5% still needs a human. In this O11yCon 2026 talk, they dig into what it takes to go from 'it works' to 'it works reliably,' including how pointing agents at like Honeycomb's speeds up on-call investigations.