Passation: Resume interrupted AI coding sessions seamlessly
Passation is a passive Python script that generates a handoff document when a Claude Code or Codex CLI session is interrupted by usage limits. It captures the current state, unfinished tasks, and plans so a new agent can continue without losing context. This solves the problem of coding sessions dying mid-task and the risk of switching agents.
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Coder: CLI tool to delegate coding tasks to background LLM agents
Coder is a CLI/plugin that lets developers dispatch coding tasks to background agents powered by Claude CLI or Codex CLI. It keeps the main session context clean and distributes workload across existing subscriptions. Built entirely with Claude Code, it is free and open source.
ChatGPT Work: persistent AI agent for complex tasks
ChatGPT Work is an OpenAI tool that performs ongoing, complex tasks autonomously, persisting for hours or days. It uses LLMs to plan and execute multi-step workflows, solving the problem of AI agents that stop after a few minutes. Aimed at professionals needing long-running automated assistance.
Developer reports AI coding agent with persistent memory across cold reboots
A developer on Reddit reports that their AI coding agent retained full context—including decisions, boundaries, and past mistakes—across a complete PC shutdown and fresh terminal session. The agent continued mid-thought without re-explanation or warm-up, suggesting a breakthrough in long-term memory persistence for coding assistants.
Developer open-sources agent-instructions repo to curb AI coding agent degradation
A developer frustrated by AI coding agents losing context and hallucinating after about 10 minutes created a set of rules to keep them on track. The rules, shared as an open-source GitHub repo, aim to reduce the need for constant reminders and prevent infinite loops. The project has gained attention from other developers facing similar issues.
Ditto: mine your own LLM coding sessions into a file for your agent
Ditto extracts only the user's typed messages from local Claude Code and Codex session logs, stripping tool output and assistant replies, and compiles them into a file that an AI agent can read first. It solves the problem of losing personal work patterns and context across many coding sessions, giving the agent a honest record of how the user actually works.

