Agents
I still don’t properly handle memory and I think I should now
This post by Harrison Chase (or from his X feed) likely discusses the challenges and considerations around implementing proper memory management in AI agents or LLM-based applications. It reflects on
This post by Harrison Chase (or from his X feed) likely discusses the challenges and considerations around implementing proper memory management in AI agents or LLM-based applications. It reflects on the importance of handling memory effectively—such as short-term, long-term, or episodic memory—for building more capable and context-aware AI systems. The post suggests a personal or practical reckoning with the need to move beyond basic or ad-hoc memory approaches toward more robust solutions.
Related
- https://x.com/hwchase17/status/2042978500567609738
- “Memory is important, and it creates lock in” Exactly why I don’t want OpenAI, Anthropic or any of the other AI companies owning it.
- The most important post I've read all week by @hwchase17 . Memory, particularly memory consistency is the biggest performance inhibitor to A…
- This post is so so good. We are at this interesting point where we’ve started to really figure out ‘memory’ with these LLM-based systems. An…
- Relying on model providers' stateful APIs or harnesses creates lock-in: switching models means losing your agent's memory -- a cost that onl…
Source: Harrison Chase (X) | 2026-04-12