Local, reviewable repo memory for coding agents
Aictx is a local-first project memory tool designed for AI coding agents, allowing them to retain and access project knowledge efficiently. It enables agents to understand repository context without repetitive briefings, storing durable knowledge that can be reviewed and inspected. The tool operates without the need for cloud services or external APIs, making it accessible and easy to use within local environments.
- ▪Aictx provides durable, human-editable project knowledge for AI coding agents.
- ▪It allows agents to load relevant reminders and save discoveries for future sessions.
- ▪The tool requires Node.js and can be set up without cloud accounts or external dependencies.
Opening excerpt (first ~120 words) tap to expand
Aictx Aictx is local-first project memory for AI coding agents, inspired by Andrej Karpathy's LLM Wiki pattern: durable, human-editable project knowledge that models can read before work. Stop re-explaining the same product intent, architecture decisions, repo conventions, setup steps, and known traps every time a new AI coding session starts. Activate Aictx once in a repo: it saves durable knowledge as local, reviewable memory, wires short agent guidance into the project, and loads only the pieces that matter for the current task. Use it when you want: New agents to understand the repo without a long briefing. Durable decisions, workflows, gotchas, and source-backed summaries to survive across sessions, branches, and reviews.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.