Often after 4 or 5 interactions, the AI will forget everything and start from scratch. This is very suboptimal.
#Warp lately has very short memory
deft lion
prisma quarryBOT
Hi @deft lion. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:
Warp's AI memory limitations are a known issue and are primarily due to the context window size of the underlying AI models. As conversations get longer, earlier parts of the conversation are discarded to stay within the model's context window (about 128K tokens). This means that after several interactions—especially if your queries or the AI's responses are lengthy—the AI may "forget" earlier parts of the conversation and start responding as if from scratch. This is not a bug, but a technical limitation of how context is managed in Warp's Agent Mode. For best results, it's recommended to start a new conversation for distinct tasks, as long conversations can also increase latency and further exacerbate context loss. You can manually start a new conversation or a follow-up as needed using keyboard shortcuts, as described in the documentation Agent Conversations.
Additionally, there are user reports and open issues about the AI losing memory or context after a few interactions, which aligns with your experience. The Warp team is aware of these limitations and is actively working on improvements, but for now, context truncation is expected behavior in long or complex sessions. If you need to preserve important information, consider breaking your workflow into shorter, more focused conversations or manually re-providing context as needed.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
dense apex
Hi @deft lion, I'm Suraj, an engineer on the team. Thanks for the feedback and sorry for the suboptimal experience you're seeing.
Can you clarify "interaction"? Are you referring to prompts, actions suggested by the agent, or different topics?
ebon bluff
Hey there this sounds similar to something I'm experiencing. I found an issue on github as well (https://github.com/warpdotdev/Warp/issues/7708) and chimed in and tried to help the dev who was looking into it. But I have no idea whether this is being taken seriously by the team, or even if they are actually aware of it at all.
Nothing long or complex about the conversations I'm talking about. Sporadic random total context loss.
latent night
I have seen similar things as well. Or pull some random piece of a previous project. into current tasks. Sometimes forcing me to restate the request all over to make sure
autumn star
Here's a general suggestion that I have been using very successfully for several months: have documentation in your codebase, and not just the warp.md file. Use warp to create the documentation and to keep it up to date. Add rules as needed to make sure it behaves.
Examples of documentation I have in my codebase: roadmap, coding standards, development workflow, testing standards, observability (logging & alerting) standards, architecture, design standards, deployment instructions, setup instructions (e.g. database, email system, authentication system, etc.). Use markdown (*.md) files.
If you want to get a little fancier, put your roadmap in something like Linear, and your other documentation in something like Notion (or locally in Obsidian, like me), and set up MCP servers to connect to those sources. Warp will charge you integration credits (which is stupid, IMHO, for local resources). But, having documentation configured and telling Warp to use it will let you get a lot more done, more quickly, and with much less churn.