Stateless Agents
AI agents that start each execution cycle with no memory of prior runs. They read their configuration and state files fresh each time, with no persistent awareness of what they did, sent, or learned in previous cycles.
What are stateless agents?
A stateless agent is an AI process that has no built-in memory between runs. Each time it executes, it starts from zero. It reads whatever context is provided in its prompt, does its work, writes output, and terminates. The next time it runs, it has no awareness of the previous execution.
Why it matters
Most autonomous AI agents today are stateless by default. This creates concrete problems:
- Duplicate actions. An agent pushes the same notification 14 times because it can’t see that it already pushed it.
- No learning. An agent tries the same failing approach every cycle because it doesn’t remember that it failed before.
- No response tracking. An agent requests approval but can’t check whether the approval was granted, because it has no record of the request.
How to address it
The solution isn’t making agents stateful (keeping them running permanently). It’s giving stateless agents access to structured memory at the start of each cycle: action logs, response tracking, and learnings files that persist between runs. The agent reads this context, reasons about it, and acts accordingly.
This is the difference between an agent that “runs” and an agent that “works.”