AI changed how software gets built.
The tools we use after we ship haven't caught up.
Code is getting cheaper.
Production is getting harder.
That's the gap Sherwood Callaway saw after building with Cursor and Claude Code. AI had transformed how software gets built, but when something broke in production, he was back clicking through observability tools that hadn't kept pace.
Sazabi is built for AI-native engineering teams.
→ Autonomous alerts with root-cause context
→ Conversational debugging instead of endless dashboards
→ AI that learns your codebase, architecture, and past incidents
AI is making it easier than ever to build software.
Sazabi makes it just as easy to understand what's happening in production—helping engineering teams detect issues earlier, identify the root cause faster, and get back to shipping.
Observability is becoming one of the most important layers of the AI software stack.
01:08 — Building AI-native observability for fast-moving engineering teams
01:45 — Why AI made observability a much bigger problem
02:07 — "Code is basically free"
02:36 — Why architecture and product thinking are the new bottlenecks
03:09 — "Measure twice, cut once" — how Sazabi stays focused
03:35 — History major to Dev Bootcamp: turning down investment banking
05:50 — Joining Brex at employee 70 through hypergrowth to $12B
07:10 — Starting Brex's observability team — the seed of Sazabi
07:48 — What observability actually is (it started with 1960s rocket science)
09:45 — "I will leave Brex today" — the Dalton Caldwell moment
12:16 — Building one of the first production AI agents at 11x
13:33 — The Cursor vs. Datadog contrast that sparked Sazabi