AI Agents in Production

After shipping dozens of AI agents into production, here’s what actually matters when you’re building for real users.

The Reality Check

Building a demo agent is easy. Building one that works reliably for thousands of users is a completely different challenge.

Key Lessons

1. State Management is Everything

Your agent needs to remember context across conversations, handle interruptions gracefully, and maintain consistency even when things go wrong.

2. Error Handling Beats Perfect Logic

Users will ask unexpected questions. They’ll interrupt mid-conversation. They’ll test edge cases you never thought of. Robust error handling is more valuable than perfect happy-path logic.

3. Observability from Day One

If you can’t see what your agent is thinking, you can’t fix it when it breaks. Logs, traces, and metrics aren’t optional—they’re essential.

4. Human Handoff is a Feature

The best agents know when to escalate to humans. Building this handoff process is just as important as the AI logic itself.

What We Build Into Every Agent

• Conversation state management
• Graceful degradation patterns
• Comprehensive observability
• Human escalation workflows
• A/B testing infrastructure

The goal isn’t to build the smartest agent—it’s to build the most reliable one.

More details in our Foundry architecture documentation.