A highly capable agent built on weak operational truth still fails in production.

Starting to feel like the true success of an agentic workflow is determined long before the first prompt is ever processed.

In production, what seems to matter more is whether the agent has deep, reliable access to real operational truth. Bulletproof API integrations, real-time database access, accurate state management, nuanced fallback logic, and a genuine understanding of the exact workflows that actually move the needle.

A frontier-level reasoning model restricted by weak data access or brittle tools still creates expensive outcomes (and frustrated users). Feels like this space is going to deeply reward the builders who stay obsessed with robust tool calling, flawless data pipelines, and rigorous evaluation more than pure model flash.

Curious to hear from others who have pushed agents to production: what was the "operational truth" or tooling hurdle that surprised you the most? Are you finding that integration and data pipelines are taking up 90% of your dev time compared to actual model tweaking?