The 5 Types of AI Agent Memory Every Developer Needs to Know (Part 1)
Because building agents without understanding memory is like hiring an employee who forgets everything by morning. Introduction Your Agent Is Not Broken. It Was Never Built to Remember. Here is som...

Source: DEV Community
Because building agents without understanding memory is like hiring an employee who forgets everything by morning. Introduction Your Agent Is Not Broken. It Was Never Built to Remember. Here is something most people get wrong when they first build an AI agent. They set it up, give it context, run a few tasks, it works great. Then they come back the next session and it has no idea who they are, what the project is, or what was decided. So they open a GitHub issue. They try different prompts. They assume something is misconfigured. Nothing is misconfigured. The agent is working exactly as designed. The hard truth is this: agent memory is not a model problem. It is an infrastructure problem. The LLM at the core of your agent is stateless by design every inference call starts completely fresh. No history, no context, no record of what happened before. That is never going to change, because statelessness is precisely what allows LLMs to scale to millions of users at once. What this means fo