Let coding agents manage their own memory using what they do best — editing files.
A dynamic, controllable, and reversible approach to context management.
As development progresses, conversation history keeps growing and agent performance degrades.
Memory Agent performs intelligent CRUD on the memory file before each task, keeping context lean and relevant.
User submits the next development task, e.g. "Add rate limiting to the API"
1. Analyze task requirements → 2. Scan memory file → 3. Execute CRUD operations
1200 lines → 500 lines | Keep critical info, compress redundancy, delete outdated content
Uses the refined memory file as context to efficiently execute the development task
Select a task scenario to see how Memory Agent intelligently processes the memory file.
Why agent-driven CRUD outperforms traditional summarization.
"No new abstraction layers — it reuses the ability coding agents already excel at: editing files.
The agent manages its own memory using the skills it already has.
It is, in essence, an agent's self-editing."
Four key steps in the Memory Agent workflow.
The Memory Agent receives the user's next task and identifies the context and dependencies it requires.
Scans the current memory file line by line, tagging each section by relevance: high / compressible / deletable.
Create new notes | Read & keep key info | Update & compress verbose sections | Delete outdated content. The original file is automatically backed up.
Produces a refined memory file for the Coding Agent to use as efficient context. Trading token cost for context quality.