Honcho Memory

Production memory system for AI agents, built on Honcho by Plastic Labs. Developed and refined running a fleet of 6+ agents in production with 1000+ messages fed through the reasoning engine.

This isn't a wrapper or setup guide. It's a complete memory pipeline: feed conversations in, reason over them automatically, generate token-budgeted context files, and query on-demand when agents need to recall something they've never seen in their current session.

The Problem This Solves

Agent memory is broken in three ways:

1. Compaction amnesia. Long sessions get compacted. Context vanishes. Your agent forgets decisions made 2 hours ago.
2. Isolated session blindness. Cron jobs and background tasks spin up fresh sessions with zero conversation history. They operate without context.
3. Single-agent silos. In multi-agent setups, agents can't access what other agents learned. Knowledge stays trapped in individual sessions.

Honcho Memory solves all three. Every agent feeds into a shared reasoning engine. Every session (main, cron, isolated) loads reasoned context at startup. Nothing gets lost.

How It Works

Most agent memory is embedding search: store text chunks, retrieve similar chunks later. That's a library with a search bar.