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Open-source API for AI workflow orchestration

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  11. 11CO

    Hi HN! I’m excited to share ControlFlow, our new open-source framework for building agentic workflows. ControlFlow is built around a core opinion that LLMs perform really well on small, well-defined tasks and run off the rails otherwise. I know that may seem obvious, but the key insight is that if you compose enough of these small tasks into a structured workflow, you can recover the kind of complex behaviors we associate with autonomous AIs, without sacrificing control or observability at each step. It ends up feeling a lot like writing a traditional software workflow. With ControlFlow you:…

    2024 · github.com

  12. 12OO

    I think like many of you, I've been jumping between many claude code/codex sessions at a time, managing multiple lines of work and worktrees in multiple repos. I wanted a way to easily manage multiple lines of work and reduce the amount of input I need to give, allowing the agents to remove me as a bottleneck from as much of the process as I can. So I built an orchestration tool for AI coding agents: Optio is an open-source orchestration system that turns tickets into merged pull requests using AI coding agents. You point it at your repos, and it handles the full lifecycle: - Intake —…

    Mar 2026 · github.com

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  15. 15OA

    Hey HN, we're Jon and Kristiane, and we're building Orloj (https://orloj.dev), an open-source orchestration runtime for multi-agent AI systems. You define agents, tools, policies, and workflows in declarative YAML manifests, and Orloj handles scheduling, execution, governance, and reliability. Over the past year we tried to use many different platforms/frameworks to build out agent systems and while building we hit some sort of problem with all of them, so we decided to have a go at it. Jon has worked with kubernettes and terraform for years and always liked the declarative…

    Mar 2026 · github.com

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  18. 18PO

    Hi HN, We are excited to share patchwork - an open-source CLI for dev chore automation that you can use with your LLM of choice. Dev Teams can orchestrate custom workflows (called ‘patchflows’) using a combination of reusable steps and prompt templates to fix vulnerabilities, upgrade breaking dependencies, generate documentation, and more. We built scanning tools in the past, and saw how overwhelmed developers get with their DevSecOps pipelines. LLMs have the potential to help - but there is a need for an 'outer-loop' solution that can be customized to accommodate the processes, priorities,…

    2024 · github.com

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  21. 21OS
  22. 22SO

    Henry, Matt and James here – we’re building an open source toolkit that makes it easy to integrate an LLM-powered copilot that talks to your API into software products. It works by calling API endpoints which you choose to expose to it. This lets the chatbot complete tasks within your software in response to natural language queries. It’s also open source, so you don’t have to send user data to another 3rd party. We support Llama 2, but we haven’t fine-tuned Llama 2 yet (coming soon) so highest accuracy is seen with GPT-4 or fine-tuned GPT-3.5 (much faster). We started working together 2…

    2023 · github.com

  23. 232C

    Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…

    Feb 2026 · github.com

  24. 24AR

    So, it feels like this should exist. But I couldn't find it. So I tried to build it. Agentflow lets you run complex LLM workflows from a simple JSON file. This can be as little as a list of tasks. Tasks can include variables, so you can reuse workflows for different outputs by providing different variable values. They can also include custom functions, so you can go beyond text generation to do anything you want to write a function for. Someone might say: "Why not just use ChatGPT?" Among other reasons, I'd say that you can't template a workflow with ChatGPT, trigger it with different…

    2023 · github.com

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