Building AI Agents That Actually Work in Production

Most enterprises are deploying AI agents without establishing foundational infrastructure and governance, creating systems that impress in demos but fail catastrophically in production. The cost extends beyond technical failures—misguided agents erode customer trust, expose organizations to compliance risks, and accumulate unmaintainable technical debt at accelerating rates. Success requires disciplined foundational decisions around tool contracts, observability, and human oversight before scaling, not after.