Continual learning layer for coding agents. Connect any agent, extract decisions and learnings automatically, and keep context fresh with background consolidation, deduplication, and forgetting.
AI coding agents are stateless. Every session starts from zero. Decisions get re-debated. Patterns get re-discovered. Context gets lost.
Lerim helps agents remember what matters and keep learning across sessions.
Every coding session -- across Claude Code, Cursor, Codex, or any supported agent -- is automatically captured. No manual tagging, no workflow changes.
LLM pipelines turn raw conversations into durable learning records -- architectural decisions, patterns discovered, pitfalls learned. Stored as plain markdown in your repo.
Any agent can query shared context. Start a new session in a different tool and it can build on your project's history, conventions, and past decisions.
Human-readable markdown in your repo. Git-friendly, no lock-in. git diff what your agents have learned.
Claude Code, OpenAI Codex, Cursor, OpenCode. One continual learning layer across all your tools.
Ask questions about past decisions and patterns. Evidence-cited answers from your project learning history.
Auto-syncs new sessions as they appear. Background runs continuously refine context with consolidation, deduplication, and forgetting.
Automatically merges duplicates, consolidates related learnings, and archives low-value or stale entries so context stays useful.
Browse sessions, learning entries, and system health. Visual learning graph explorer.
Add Lerim as a skill to any supported agent. It runs in the background automatically -- syncing sessions, extracting learnings, consolidating overlap, and forgetting low-value noise with zero manual effort.
Your agent now knows how to use Lerim. It can recall relevant context before a task and write back new learnings after it finishes -- across every session and every tool.
Full control from the terminal. Sync sessions, run consolidation and forgetting, and query your project's learning history directly.
Your agent learning records live as human-readable markdown files in your repo. Version-controlled, portable, and future-proof.
git diff what your agents learned.
memory/ decisions/ # architectural choices learnings/ # patterns & pitfalls summaries/ # session records archived/ # retired entries config.toml # project settings