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Known limitations:
A new tool category has emerged around observing, recording, and analyzing the interactions between developers and AI coding agents (Claude Code, Cursor, Copilot, Codex, OpenCode, etc.). These tools sit alongside the coding agent -- intercepting traffic, reading session files, hooking into agent events, or integrating into the IDE -- and provide visibility into what was asked, what was done, how much it cost, and what patterns emerge over time.
This is distinct from production LLM observability (Langfuse, LangSmith, Helicone, etc.), which monitors AI applications running in production. The tools here are focused on developer workstations and coding sessions.
The field is roughly six months old as a recognizable category and is evolving rapidly.
This report describes six core features of the MiMo-Code platform (the packages/opencode package): Persistent Memory, Intelligent Context Management, Task Tracking, the Subagent System, Goal / Stop Conditions, and Dream & Distill. Each section traces the feature from user-facing surface down through its implementation layers, database schema, and integration points. A final section analyzes how the features interact.
