Alternatives
Products that do what Patchwork – Open-Source AI Workflows for Dev Chores does
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,…
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Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…
2024 · github.com
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I have been a daily HN reader and would like to use this as a starting point to show SimWorkflow so that the HN community can get to know SimWorkflow. This project has been the love child of myself for the past year or so. A bit of background: Previously, I worked as a consultant specializing in designing, implementing, and maintaining Business Process Management and Content Management Solutions. I was surprised at the effort required to implement such solutions; specifically, the time it took, the number of people involved, and the amount of custom code. I thought: What if we could make…
2024 · simworkflow.com
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I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
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I have been trying to create AI retool where tooling is done via AI, to create full stack apps like internal portals, ERP apps. Which led me to an architecture where we give ai pre build component, tools and let is just do the binding, content generation work to create full stack apps. With this approach in a single prompt AI is able to generate final config jsons using chained/looped agentic llm flow and we render a full stack app with the configs at the end. I have open sourced the whole project whole code, app builder, agentic architecture, backend for you to use. Github:…
2025 · oneshotcodegen.com
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Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…
Dec 2025 · docs.trysoma.ai
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Hello Hacker News! We're excited to introduce DeskFlow, an AI-driven Slack and Microsoft Teams bot, designed to streamline HR and IT operations in your workspace. DeskFlow harnesses LLM to provide immediate answers to HR and IT related queries, functioning like an in-house expert. Its features include instant access to your knowledge base and HR system, automatic ticket routing, and soon, auto-drafting responses to inquiries. By integrating DeskFlow directly into your communication channels, employees save time and boost productivity by eliminating the need to switch context or apps. We'd…
2023 · deskflow.ai
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I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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Hey HN! When I started looking into LLMs and agents for software development and introducing them at work, I quickly realised that a person new to the topic faces a real barrage: - all the hype (AGI, engineers getting replaced by AI etc.) - conflicting opinions in virtually every discussion—for every person saying they’ve 10x-ed their productivity, there is a comment decrying LLMs as an utter failure - a lot of jargon (MoE, MCP, RAG, distillation, quantisation etc. etc.) - a profusion of models, IDEs/IDE extensions, CLI agents, other tools etc. Sorting through all of this can be quite…
2025 · nohypeai.dev
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Hi HN, I recently open sourced a small tool (Remuda) that I built at work to remove some of the friction of launching and managing agents and figured HN might be interested. I also wrote a post on the company blog that goes into more detail about why I built it and showcases its features: https://www.yendo.com/blog/remuda-an-agent-orchestrator
Jun 2026 · github.com
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Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…
2023 · gethorizon.ai
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Every time I wanted to use LLMs in my existing pipelines the integration was very bloated, complex, and too slow. This is why I created a lightweight library that works just like scikit-learn, the flow generally follows a pipeline-like structure where you “fit” (learn) a skill from sample data or an instruction set, then “predict” (apply the skill) to new data, returning structured results. High-Level Concept Flow Your Data --> Load Skill / Learn Skill --> Create Tasks --> Run Tasks --> Structured Results --> Downstream Steps And the bast part: Every step can be saved and reused as…
2025 · github.com
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LLM agents rely on tool calls — but tool responses are huge. Gmail, CRMs, and APIs return bloated JSON LLMs choke on large responses You only need 2–3 fields, but frameworks give you zero control Toolflow is an AI-native framework to fix this: * Filter tool responses before they hit the LLM * Context modes: `minimal`, `full`, `custom`, or `ai` * Composable TypeScript tool registry GitHub: [https://github.com/dksingh1997/toolflow](https://github.com/dksingh1997/toolflow) Would love feedback — especially from those building with LLMs in production.
2025 · github.com
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Hi HN, I am Umer. I recently built an experimental framework called HyperFlow to explore the idea of self-improving AI agents. Usually, when an agent fails a task, we developers step in to manually tweak the prompt or adjust the code logic. I wanted to see if an agent could automate its own improvement loop. Built on LangChain and LangGraph, HyperFlow uses two agents: - A TaskAgent that solves the domain problem. - A MetaAgent that acts as the improver. The MetaAgent looks at the TaskAgent's evaluation logs, rewrites the underlying Python code, tools, and prompt files, and then tests the new…
Apr 2026
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