Your Claude Forgets Everything. Anthropic's Fix? Let It Dream.

A developer built an open-source kit, claude-memory-kit, that implements a persistent memory and background "dreaming" workflow for Claude Code agents, based on a talk by Lamis, a member of Anthropic's applied AI team, at AI DevCon. The approach uses a notes file for simple cases and a separate batch process that reviews past session transcripts, including tool calls, and proposes memory changes for human approval. The kit adds versioning, conflict checks and permissions without requiring servers, a database or API keys.

You spend ten minutes telling Claude how your project works. You close the chat. The next day you open a new one, and it asks you the same questions again. I used to think this was just how AI works. Then I watched a talk by Lamis , a member of technical staff on Anthropic's applied AI team, at AI DevCon. She explained why this happens and how Anthropic fixes it for agents running in production. This post is my plain English version of her talk. All the ideas are hers. I only simplified them and added how I plan to use them every day. Watch the full talk here: The honest disclaimer: The results she mentions better accuracy, lower cost come from Anthropic's own production systems. I have not measured them myself, so treat the numbers as her claims, not mine. A new model is smarter, but it does not know your codebase, your team, or how you like things done. That knowledge is called context. Better models do not replace it. Good context multiplies whatever intelligence the model already has. And without memory, your agent never gets better at a task the second time. It makes the same mistake again, because every new chat starts empty. Anthropic's rule through all of this is: do the simple thing that works. Here is the path they took: One agent with a notes file works great. A whole fleet of agents does not, unless you add guardrails. Her examples: Here is the part I found most interesting. While an agent works, it only sees its own chat. It cannot notice a pattern across many chats. It also has to split its energy between doing your task and taking notes for the future. So Anthropic added a second process called dreaming . It runs in the background, in a batch, with its own budget. It reads many past session transcripts including the tool calls, not only the messages , compares them with the memory store, and proposes changes. Her school example makes it easy. A head teacher marks everyone's exams and notices every student got the same geography question wrong. The topic is missing from the lesson plan, so the teacher adds it. Or everyone answered in radians instead of degrees. The calculator setting is wrong, so the teacher fixes the instructions. For agents, that is the same as spotting a tool that keeps failing, or a company-wide habit you do not like. The output is a list of proposed changes, with example transcripts and how common the problem is. A human then accepts or rejects each one. If you use Claude every day: If you build with Claude Code or agents: If you want a ready made version, she pointed to Anthropic's memory and dreaming API in Claude Managed Agents, which has versioning and hashing built in. It is still early and she said so herself: this is an open area of research. But the simple parts work today, and you can start this afternoon. I did not want this to stay as theory, so I turned her ideas into a small open source kit. It has two skills, a starter memory folder, and a safety script that adds the versioning, the conflict check and the permissions she talked about. No servers, no database, no API keys. Repo: https://github.com/Emmanuellsensai/claude-memory-kit https://github.com/Emmanuellsensai/claude-memory-kit Step 1. Install it Claude Code . On Windows PowerShell: git clone https://github.com/Emmanuellsensai/claude-memory-kit.git cd claude-memory-kit .\install.ps1 -AppendClaudeMd On Mac, Linux or Git Bash: git clone https://github.com/Emmanuellsensai/claude-memory-kit.git cd claude-memory-kit ./install.sh --claude-md That copies the skills into your Claude folder, creates a memory folder, and adds a short note to your CLAUDE.md so Claude follows the memory habit on every task. Step 2. Check it works. Open a new Claude Code session and ask: "What does your memory-keeper skill do?" Step 3. Teach it something. Say: "Remember that I like short answers with the result first." Claude should save a note and tell you in one line. You can see the note in the memory folder. Step 4. Dream once a week. Just say "dream". Claude reads your last week of sessions, finds the mistakes that keep repeating, and writes proposals. You accept or reject each one. Nothing changes without you. No terminal? The repo has a claude.ai route in docs/SETUP.md that uses Skills and a Project. The honest part: this kit is a community project built from her talk. It is not an official Anthropic tool, and I have not measured the accuracy or cost gains myself. Use it as a good starting point, then adjust the notes to fit how you work. All credit goes to Lamis and the Anthropic team for sharing this. If this helped you, drop a comment with how you handle memory in your own Claude setup, and share it with someone who keeps re-explaining things to their AI. Follow me for more practical developer and AI workflow tips.