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Products that do what Enoch – Control Plane for Autonomous AI Research does
I built Enoch after working with OpenClaw and trying to get an agentic coding system setup with Codex. In the past, I was trying to manually generate, code, and test this all manually. Then - I figured I'd try to start automation. Too many times have I typed "Continue" and gone back to my work. I figured I could automate that. Well - Enoch is what stemmed from that. My first implementations were a mess with OpenClaw. I'll spare you the details. I moved to n8n. n8n was not bad but it felt like I had to strong arm it to do what I wanted. Had issues, but less. Then this system - LangGraph…
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
- 3OA
Hi HN, I’m Mike, the founder of OpenRig. I built this because my Claude Code + Codex setup kept forming little "topologies" of long-lived agents that worked well together, but the terminal sprawl was intense. So I built a primitive the agents could intuitively reach for to save and recreate these setups on the fly. This then led to more agent-first primitives like coordination, declarative workflow patterns, workspaces, etc. Several months in and these "rigs" I manage with openrig require a lot less babysitting and I can manage more projects at once without getting overwhelmed. The short…
May 2026 · openrig.dev
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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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We just open-sourced the internal system we built at Assembled for running coding agents as a team. Coding agents worked well for individual engineers, but the surrounding workflow was a bit of a mess. We generally found that many engineers had different MCP connections and context for their agents, personal automations running that other people couldn’t access, and very little introspection for what a human’s input into the coding agent looked like. So we built an internal system that converted coding agents into shared team infrastructure. The system runs Codex, Claude Code, OpenCode, and…
Jun 2026
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Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…
Jul 2026 · shikigami.dev
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I’ve been cautiously (and nervously) playing with openclaw and a number of other claw and code agents for a while now, but trying out different ones was tricky so I wanted a simple way to switch out channel ownership… then I wanted more. Security is hard, and I wanted to make it easier. This is FAR from polished, and no claims that I’m a “security expert” but I tried to think and research a bit on different threat models (I think of 2 broad ones for agents, external adversaries and internal agentic failures) and try and offer best in class protection on both, while also not having any…
Apr 2026 · github.com
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Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.
Mar 2026 · agents.zalor.ai
- 10OA
I built this over the weekend after reading about StrongDM's software factory (their writeup: https://factory.strongdm.ai/, Simon Willison's deep dive: https://simonwillison.net/2026/Feb/7/software-factory/, Dan Shapiro's Five Levels: https://www.danshapiro.com/blog/2026/01/the-five-levels-from...). OctopusGarden is an open-source implementation of the pattern StrongDM described: holdout scenarios, probabilistic satisfaction scoring via LLM-as-judge, and a convergence loop that iterates until the code works; no…
Mar 2026 · github.com
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I built a skill library for OpenClaw (always-on AI agent runtime, not session-based) where the agent can teach itself new behaviors during normal conversation. The idea: you tell your agent "every time I ask for a code review, always check for security issues first." It invokes a create-skill skill, writes a new SKILL.md, and that behavior is live immediately — no restart, no config change, no developer required. What I think is actually useful (the safety cluster): • loop-circuit-breaker: OpenClaw retries ALL errors identically. This halts on the 2nd identical failure before it burns your…
Mar 2026 · github.com
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I built DevClaw, an OpenClaw plugin that turns each Telegram group into an isolated, autonomous dev team: planner/orchestrator, DEVs, and QA all running on their own. I use it for all my development now. Issues on GitLab/GitHub are the single source of truth, and three things compound to save around 70% on tokens: model tiering (Haiku for typos, Opus for architecture), session reuse across tasks, and token-free scheduling that burns zero LLM calls for orchestration. Please try it and give some feedback. Also keen to hear from anyone running autonomous coding agents, especially what…
Feb 2026 · github.com
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Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…
Jan 2026 · marketplace.visualstudio.com
- 14OA
I've been running Claude Code and Codex together every day. At some point I figured out you can use tmux to let them talk to each other, so I started doing that. Once they could coordinate, I kept adding more agents. Before long I had a whole team working together. But any time I rebooted my machine, the whole thing was gone. Not just the tabs. The way they were wired up, what each one was doing, all of it. Nothing I'd found treats your agent setup as a topology, as something with a shape you can save and bring back. So I built OpenRig, a multi-agent harness. A harness wraps a model. A "rig"…
Apr 2026 · github.com
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While reading Agentic Design Patterns by Antonio Gulli, I wanted to see how these patterns look in real code. I cloned the OpenAI Codex repo (the open-source AI coding assistant that recently trended on HN) — but it was in Rust. So, I used an Cursor to help me extract and translate 18+ agentic patterns from Codex’s codebase into Python. That small experiment turned into a full open-source guide: GitHub: Codex Agentic Patterns https://github.com/artvandelay/codex-agentic-patterns Each pattern comes with: A short explanation and code sample A runnable exercise and agent…
Oct 2025 · artvandelay.github.io
- 16AS
AI changed the way we code, but we're still using the old processes, and we've become the bottleneck, the AI is waiting for us - to reply, to open our laptops, to review the code, and so on. We're building the future of AI software development. The agents are autonomous, they run in sandboxes, automatically fix the pipelines, and deliver you the final, working code. You can use live preview to see the changes they made. Working across multiple repositories, all within the same session. This is the future - you don't need an IDE, and you don't have to run anything locally.
Mar 2026 · agenhq.com
- 17IB
The main goal of this was to be able to not just run multiple Claude Code sessions at once, but actually manage them and keep track of what I was doing. Sometimes this is multiple attempts on the same task, sometimes I work several tasks at once. Really I was just sick of twiddling my thumbs waiting for the coding agent to finish, and I wanted it to be easy to work on/review/test another change while I waited.
2025 · github.com
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A friend and I spent a month throwing together a visual rule engine product– wanted to share it with HN today. I've been building automation tooling for a few years at prefix.app and one of the messier things both to support and to teach users was around encoding logic in their automations– most folks get a hold of the basic concepts quite easily, but every (visual) automation tool out there seems to have their own way of actually pulling it all together. For small decisions those work great! But for bigger decisions and more complex logic we don’t think it makes much sense to be embedding…
2022 · rulebricks.com
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I've been working on a new programming language for AI agents. I would love your input on what makes programming languages good for AI agents, especially syntax, compiler, and tooling that could help AI agents write code. What makes Sigil good for coding agents? I've turned conventions into compiler rules whenever possible. The compiler owns the canonical printer and every AST has one accepted textual representation. For almost every syntax feature I tried to save tokens. Order and naming conventions are enforced. No more "I think this argument is important so it should come first." Most…
Apr 2026
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I’ve been working on a multi-agent academic research lab, and I wanted to share it here today primarily to give a massive shoutout to the developers behind ZeroClaw. When designing the architecture for this, I needed an autonomous agent runtime that was lightweight, entirely agnostic, and highly secure for local execution. ZeroClaw’s pure Rust implementation provided exactly the zero-overhead foundation the project required. Because they solved the core runtime execution so elegantly, I was able to spend my time building the higher-level orchestration on top of it—like the retrieval graph…
Mar 2026 · rainlabteam.vercel.app
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