AI Agents Control Tower

Observability layer that catches silent AI agent failures

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September 2, 2026 Building AI Agents Control Tower: the observability layer the AI stack diagrams forget

Every "Modern AI Stack" diagram I see has boxes for LLMs, frameworks, vector DBs, evaluation - and nothing for "is this thing still working right now, in production, at 2am." Evaluation tells you if an agent passed a test before launch. Nothing tells you if it's silently broken after launch.

AI Agents Control Tower watches live agent traffic and catches the failures that don't throw errors: a tool call that returns empty instead of raising an exception, a loop that keeps burning tokens without making progress, an agent that quietly stops doing its job while still returning HTTP 200. It's the layer between "deployed" and "actually working."

Solo founder, self-funded, live in production since June. Dogfooding it on my own agents daily, which is how most of the detection patterns actually got built - from watching my own stuff break first.

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Agent frameworks make it trivially easy to ship something that looks like it works. What they don't do is tell you when it silently doesn't - a tool call that returns empty, a loop that burns budget without progress, an