Alternatives
Products that do what Lemon Agent – Plan and Solve agent for workflow automation does
I built this Plan and Solve (PS) agent because I struggled to build stable sequential tasks with LangChain and GPT3.5 turbo. After many failed attempts with LangChain's PS agent, I decided to build my own. I built the agent in a way that it acts as a workflow automation co-pilot rather than trying to play AGI. For example, the user has to tell the Lemon Agent which task needs to be solved and whether the suggested workflow automation is the right one for the task. I decided to go with a PS architecture since I consider the separation of responsibility a great way to increase the accuracy of…
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Build AI automations & agents using natural language
Oct 2025 · docs.n8n.io
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Hello HN, I don't post on here much, but wanted to get some eyes on a new project I'm just launching. I think we definitely need one more AI code agent.. I'm a long-term C++ dev, and over 30+ years I've created some successful audio dev tools (JUCE, the Tracktion DAW, the Cmajor DSP language). All of these came from me getting annoyed with something I had to use, and deciding to have a go at my own take on whatever it was. So Juggler is my attempt at an AI code agent, after spending too many hours loving what the models could do, but hating the CLI experience, and having some opinions of…
Jul 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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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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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 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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Hi, as the LLM models are getting smarter in coding tasks, we will soon be using agents as co workers, as current tools like github copilot and cursor are not optimized for team collaboration, we began building PhantomX, please give your feedback, if you think we are in the right direction or what should be changed for finding the optimized development workflow which works for both humans and agents.
Jan 2026 · phantomx.dev
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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…
Mar 2026 · github.com
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Hey HN, I'm Mo. I'm building Paseo, a multi-platform interface for running Claude Code, Codex and OpenCode. The daemon runs on any machine (your Macbook, a VPS, whatever) and clients (web, mobile, desktop, CLI) connect over WebSocket (there's a built-in E2EE relay for convenience, but you can opt-out). I started working on Paseo last September as a push-to-talk voice interface for Claude Code. I wanted to bounce ideas hands-free while going on walks, after a while I wanted to see what the agent was doing, then I wanted to text it when I couldn't talk, then I wanted to see diffs and run…
Mar 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
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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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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 tinkering with what a “multi-agent IDE” should look like if your day-to-day workflow is mostly in terminal (Claude Code, OpenAI Codex, etc.). The more I played with it, the more it collapsed into three fundamentals: * A good TUI: Terminal is the center stage, with other stuff (CodeEdit, Diff, Review) baked on the side. I don’t like piping Agent’s output through some electron wrapper, here you get to run CC/Codex/Droid/Amp/etc directly. * Isolation: agents shouldn’t step on each other’s toes. The simplest primitive I’ve found is Git worktrees. It is not as…
Jan 2026 · agentastic.dev
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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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Hi! I spent 3 years evaluating LLMs for OpenAI, Anthropic, METR, and other labs. Kept running into the same problem: AI workflows break in production because there's no clean way to add human oversight, handle failures gracefully, or deploy without choosing between "all cloud" and "all self-hosted." WeaveMind is a visual workflow builder in Rust. The core idea is that humans and AI are interchangeable nodes in the same graph. When a workflow needs judgment, it pauses, notifies the team via browser extension, first responder picks it up. There's also an AI assistant that generates workflows…
Feb 2026 · weavemind.ai
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Hey HN, I'm Mo. I'm building Paseo, a multi-platform interface for running Claude Code, Codex and OpenCode. The daemon runs on any machine (your Macbook, a VPS, whatever) and clients (web, mobile, desktop, CLI) connect over WebSocket (there's a built-in E2EE relay for convenience, but you can opt-out). I started working on Paseo last September as a push-to-talk voice interface for Claude Code. I wanted to bounce ideas hands-free while going on walks, after a while I wanted to see what the agent was doing, then I wanted to text it when I couldn't talk, then I wanted to see diffs and run…
Mar 2026
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Hey HN, I'm Mo. I've been building Paseo, an open source environment for running Claude Code, Codex, and OpenCode across desktop, mobile, web, and CLI. It started last September as a push-to-talk voice interface for Claude Code. I wanted to talk to an agent while going on walks. Then I wanted to see what it was doing. Then text it when I couldn't talk. Then review diffs, run multiple agents, and manage work across machines. After a lot of iteration, it turned into a broader environment. The basic model is: - A daemon runs on your machine (MacBook, desktop, VPS, etc.). - Clients connect to it…
Mar 2026 · github.com
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