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HATCHET
Orchestration engine for AI agents, background tasks, and durable workflows
MIT
ABOUT
AI agents and multi-step workflows need reliable execution with retries, timeouts, and state persistence, but building this infrastructure from scratch is complex and error-prone. Hatchet solves this with a workflow orchestration engine purpose-built for AI agents — handling task scheduling, automatic retries on failure, durable execution that survives process restarts, and built-in observability for debugging complex agent chains.
INSTALL
go install github.com/hatchet-dev/hatchet/cmd/hatchet-admin@latestINTEGRATION GUIDE
1. Orchestrate multi-step AI agent workflows with automatic retries and durable state persistence
2. Build a background job system for AI tasks that processes prompts, generates images, or runs inference reliably
3. Create a scheduling system for periodic AI tasks like daily report generation or model re-evaluation
4. Implement a fan-out workflow that parallelizes AI processing across multiple model API calls
5. Build a human-in-the-loop workflow that pauses execution, waits for approval, and resumes the agent pipeline
TAGS
orchestrationworkflowai-agentstask-queueschedulingdurabilitygolangobservability