The 5 files every production AI agent needs (and what goes wrong without them)

The 5 files every production AI agent needs (and what goes wrong without them) I've been running AI agents in production for 6+ months. Not demos — agents that fire on cron, handle real customer interactions, and ship code to live sites. The most common failure mode I see: agents that work in testing and break silently in production. Not crashing. Just quietly doing the wrong thing. The fix, almost every time, is the same: the agent has no persistent state . It's running blind. Here are the 5 files that changed this for me. 1. current-task.json — The agent's short-term memory Without this: agents start from scratch every run, re-do work, or silently skip steps they think they already did. { "task" : "email-digest" , "status" : "in_progress" , "last_updated" : "2026-03-07T14:30:00Z" , "checkpoint" : "fetched_emails" , "items_processed" : 47 , "next_action" : "summarize_batch_3" } Rule: write this file before any long operation . Check it at the start of every run. If status is in_progre