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Why most AI agents fail in production
The gap between a demo agent and a reliable one isn't the model — it's the eval harness, the tool contracts, and the recovery loops you build around it.
March 2026 · 8 min read
[ Insights ]
Long-form essays on what actually works when AI meets enterprise reality — written by the engineers who ship it.
The gap between a demo agent and a reliable one isn't the model — it's the eval harness, the tool contracts, and the recovery loops you build around it.
Function-calling reliability collapses past roughly twelve tools. We share the routing pattern we use to scale agent toolkits past eighty.
Enterprises that win with AI sequence capability in four phases. Skipping a phase is the most common — and most expensive — mistake.
Your existing APM stack wasn't built for agents. Here's the telemetry layer we've standardized across every engagement.
Retrieval-augmented generation looks simple until your corpus crosses one million documents. We map the architectural cliffs.
Not every workflow deserves custom engineering. A framework for deciding when to license, when to fine-tune, and when to build.