Alternatives
Products that do what Ductwork – A Go platform for running AI agents on autopilot does
I've been running Claude agents for various automation tasks — monitoring crypto news, syncing Todoist, running health checks — and I kept hitting the same problem: there's no clean way to deploy an agent that just runs on a schedule without a human babysitting it. Every agent framework I looked at was built around chat interfaces or one-shot workflows. I wanted something closer to cron for AI agents — define a task, give it a schedule, let it run forever. So I built Ductwork. You define tasks as simple JSON files — a prompt, a schedule, optional memory and skills — and ductwork handles…
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hi guys. been working on something i think is fundamentally missing in today's workflow with ai agents. vcs. i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session. just like git did for code, i think we are the same core capabilities with ai agents so... i developed an open source solution for that (currently supporting claude code) would love to…
May 2026 · github.com
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I think graph is a wrong abstraction for building AI agents. Just look at how incredibly hard it is to make routing using LangGraph - conditional edges are a mess. I built Laminar Flow to solve a common frustration with traditional workflow engines - the rigid need to predefine all node connections. Instead of static DAGs, Flow uses a dynamic task queue system that lets workflows evolve at runtime. Flow is built on 3 core principles: * Concurrent Execution - Tasks run in parallel automatically * Dynamic Scheduling - Tasks can schedule new tasks at runtime * Smart Dependencies - Tasks can…
2024 · github.com
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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
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Hi HN, I’m Vincent from Aden. We spent 4 years building ERP automation for construction (PO/invoice reconciliation). We had real enterprise customers but hit a technical wall: Chatbots aren't for real work. Accountants don't want to chat; they want the ledger reconciled while they sleep. They want services, not tools. Existing agent frameworks (LangChain, AutoGPT) failed in production - brittle, looping, and unable to handle messy data. General Computer Use (GCU) frameworks were even worse. My reflections: 1. The "Toy App" Ceiling & GCU Trap Most frameworks assume synchronous sessions.…
Feb 2026 · github.com
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This project (Agents Observe) started as an exploration into building automation harnesses around claude code. I needed a way to see exactly what teams of agents were doing in realtime and to filter and search their output. A few interesting learnings from building and using this: - Claude code hooks are blocking - performance degrades rapidly if you have a lot of plugins that use hooks - Hooks provide a lot more useful info than OTEL data - Claude's jsonl files provide the full picture - Lifecycle management of MCP processes started by plugins is a bit kludgy at best The biggest takeaway is…
Apr 2026 · github.com
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Automate boring work. Extensible and free desktop AI agent.
Aug 2026 · agent-one.dev
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AgentGrid▲77Hi HN, I’m Michael, I built AgentGrid with my friend Souren because we were tired of losing our coding sessions and couldn't keep track of what was actually being built across our many projects. Our approach was to use an infinite canvas desktop app for the TUIs we already know and love, mainly claude + codex. We drew inspiration from Figma and Railway. Overtime we added image nodes, notes, terminals, coding editors, source control, etc. I wasn't sure about it at first. It took me a month to give the first version Souren built a real try. What got me was an Apple System Update I've been…
Jul 2026 · agentgrid.sh
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Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image. We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that. Imagine if you are a…
2023 · lepton.ai
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Production-tested architecture for autonomous Claude agents
Apr 2026 · dvdshn.com
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Some time ago I built a simple app to run swarms of coding agents — I call it fleet (https://news.ycombinator.com/item?id=48256389). It's based on centralized beads with a Python orchestrator and can run any coder (Claude, agy, Codex). Recently I added a UI to manage the whole agent lifecycle: adding new tasks, monitoring running ones, and a chat interface built on MCP with a centralized SQLite DB. From the UI I can spawn agents to run in any directory, define dependencies on other tasks, and specify which coder/model should do the job. Today I can run 10–15 agents…
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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1. Headless mode Headless mode allows you to use the AI as a command-line utility for automation and scripting. In Claude Code you run it with the -p flag: claude -p, in codex - exec, opencode - run. 2. Ask human The traditional communication channel with the operator won't work in headless mode - we need to implement a dedicated tool. Here is an example of how this can be done https://github.com/sermakarevich/claude/tree/main/mcp/ask_hu... 3. Tasks queue Beads is a lightweight distributed graph issue tracker for AI agents, powered by Dolt. You can…
Jun 2026
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2025 · agentwrap.dev
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It uses your local Claude and GitHub CLI and git worktrees, so there's nothing to configure beyond what you already have. Our AI coding workflow was a hodgepodge of scripts and ad-hoc processes, so we built this to centralize and streamline - and most importantly adapt as things change. Some cool features so far (lots more planned): 1. One click github issue to agent working on it. 2. Ratcheting mode, where it watches CI for code review comments and build failures, and automatically fixes them. Would love genuine feedback, bug reports, PRs, suggestions, etc.
Feb 2026 · github.com
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