Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-agent shared state on disk. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard.

AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation

Agent harness for long-running AI coding tasks — orchestrates Claude Code & GitHub Copilot across repositories 🍩

A framework for executing long-running AI agent tasks with structured feature lists and progress tracking.

Java-native runtime for long-running AI agents with live execution control, human approvals, and audit trails.

Long-running AI agents that adapt until outcomes converge.

watches the watchers: a monitoring system for long-running Claude Code agents

Codex-derived source release for an opt-in session compact route that preserves durable handoff state across repeated compactions.

Continuity for AI agent work that outgrows one chat.

Production 3-agent harness for autonomous multi-hour software builds. Planner + Generator + Evaluator with parallel fleet execution, circuit-breaker stagnation detection, and graceful resume.

Production-ready workspace setup for long-running OpenClaw AI agents. Artifact workflow, secrets management, memory optimization, and battle-tested patterns.

Autonomous AI coding agents for long-term task execution.

Pi extension that gives coding agents persistent /goal workflows with branch-aware state, source imports, progress tools, and explicit start handoffs.

AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation

AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation

Claude Code plugin for long-running agent workflows with progress tracking, feature checklists, and git checkpoints

A Codex skill pack for long-running project work

Codex skill for designing and scaffolding durable agent harness projects, with a Ralph Loop preset and upgrade-friendly doctrine.

Evidence-bound workflow diagnostics and certified lower-bound reporting for long-running AI agent pipelines. Improve agent workflow throughput without changing the model.

Personal website of Iris Shen, focused on memory, evaluation, orchestration, and runtime systems for long-running AI agents.