aimee aims to cut coding-agent memory loss, tokens, and model costs
aimee is a for using several coding AI tools through one place. Any tool that works with the OpenAI or Anthropic style of connection can point to it, then run a turn on Claude, GPT, Gemini, or a model on the user’s own . Work memory follows across tools because aimee turns each session into a and indexes code relationships across repositories.
That structure is meant to help an agent remember an earlier decision and notice related calls in other files before editing code. Simple work can be sent to the cheapest model that can handle it, including a local model or a plan the user already pays for, while the main agent receives only the needed answer. A cuts down long tool output and compresses old history into a short running outline to reduce token use.
The server runs on the user’s own hardware and is presented as not sending usage data back out.
Key points
- aimee is a that sits between coding AI tools and s.
- It can route work to Claude, GPT, Gemini, or a model running on the user’s own .
- It keeps memory across sessions by building a and indexing code relationships.
- It sends routine tasks to cheaper models or existing paid plans to reduce cost.
- A trims long tool output and compresses older history to save tokens.