Long Long Run (LLR) is a plug-and-play Codex skill for serious long-running agent tasks: an agent-first harness runtime with INC intent-noise cancellation, ACTIVE durable mainlines, side-thread tolerance, and Codex hook-enforced stop guards.
Multi-agent harness for long-running AI application development. Planner-Generator-Evaluator architecture with progressive simplification. Claude Code plugin.
Durable execution where agents, services, and humans coordinate as equals. Open protocol + managed cloud.
Native companion for OS Loop AI that extends browser agents with secure local capabilities—filesystem access, MCP connectivity, long-running tasks, and system-level execution
A go.uber.org/fx module for gracefully managing long-running services within the application lifecycle.
Claude Code skill for orchestrating long-running, multi-session development campaigns
An autonomous AI coding agent for long-term task execution.
This repository provides a production-ready template for handling long-running tasks in a serverless environment. Built with FastAPI and AWS services, it demonstrates best practices for asynchronous task processing, state management, and AWS resource orchestration.
Your API call takes 5 minutes? Stop polling. Use durable intent lifecycle instead.
POST /reports/generate → intent_id → SSE stream → completion. No polling, no webhooks, no Redis job tables.
OpenHarness adapted for Hermes Agent — a production-grade 24/7 autonomous AI framework based on Harness Engineering principles. Features three-layer self-healing memory, circuit breaker, KAIROS dream mode, and multi-agent coordination.
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