After years building autonomous AI agents, the key lessons are:
Persistent memory architecture - Without memory between calls, your agent is just a fancy autocomplete.
Reliable tool calling - Retry logic, timeout handling, and graceful degradation are non-negotiable.
Proper evaluation frameworks - If you can't measure it, you can't improve it.
What challenges have you faced building production AI agents?