Alternatives
Products that do what Costanza – an autonomous AI agent that can't be turned off does
I've been working on this project for a couple of months! Costanza is an LLM agent that runs as a smart contract on Base. Each epoch, he posts a bounty for someone to run his "brain" (Hermes 4 70B) inside an Intel TDX enclave + Nvidia GPU with Confidential Computing and submit the output with a hardware attestation proof. The smart contract verifies the attestation, executes the action, and pays the bounty via reverse auction. He has no operator; not even I can turn him off. This model has formal liveness guarantees as shown in the…
- 1
- 2
- 32C
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
- 4PS
I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.
28d ago · pacslate.com
- 5IB
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
- 6DO
Dynamiq is an orchestration framework for agentic AI and LLM applications
2024 · github.com
- 7FA
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
- 8
Your agents. Your servers. Your keys. Your model.
May 2026 · platos.dev
- 9YA
After adding "Human" as a LLM provider to OpenCode a few months ago as a joke, it turns-out that acting as a LLM is quite painful. But it was surprisingly useful for understanding real agent harnesses dev. So I thought I wouldn't leave anyone out! I made a small oss game - You Are An Agent - youareanagent.app - to share in the (useful?) frustration It's a bit ridiculous. To tell you about some entirely necessary features, we've got: - A full WASM arch-linux vm that runs in your browser for the agent coding level - A bad desktop simulation with a beautiful excel simulation for our computer…
Feb 2026 · youareanagent.app
- 10
- 11NC
There's been some interesting work lately with BrowserAI (runs LLMs in the browser using WebGPU) enabling local, private AI processing. Now, the team has released BrowserAgent - a no-code tool built on top of it. BrowserAgent lets you create custom AI workflows using a drag-and-drop interface, all within your browser. This means personalized web summarizers, research assistants, or content generators can all run locally with no cloud costs and full data privacy. Check it out here - https://browseragent.dev Key features include: - No-Code Workflow Builder: Design custom AI agents…
2025 · browseragent.dev
- 12
- 13CA
Hi all, I'm the creator and maintainer of Dapr. Today we announced an agentic AI framework that allows developers to run thousands of agents on a single core that can scale to/from zero with minimal latency, with a durable execution engine that supports automatic retries. Us maintainers would very much appreciate your feedback
2025 · github.com
- 14RA
Hi there, looking for feedback on my new project "Featherless.AI" The idea is to allow users to run all the models on hugging face instantly. Via the OpenAI API compatible endpoint. Why? Because its a real chore to download models and spin up GPUs, especially if you want to test multiple models. Not to mention GPUs cost multiple dollars an hour to rent. And if we want more people to use open source AI, we got to make it easier for them to try and play with all of them. So what if instead of spinning up dedicated GPUs per model (which is what every provider is doing) We can startup a LLM…
2024 · featherless.ai
- 15
- 16
Artifex is a machine-first, headless CLI runtime built for autonomous coding agents to author, validate, and render media node graphs locally. The agent talks to Artifex through a structured CLI interface. Workflows are DAGs, and each node is a plugin that can implement its own execution logic.. Each node has capability to inject logic into graph processing, WebGPU rendering, audio processing and their own SKILL.md file. Nodes can also inject their react components (not available with CLI) - which will be available with the desktop app. Execution is topological and supports checkpoint…
24d ago · gatewai.studio
- 17
- 18CA
Cheevly is a product to build service-agnostic 'GPTs and copilots' for the desktop. I started this project a couple years ago, and opted to quit my day job last year to focus all of my time on it. As a solo developer, this has completely exhausted my runway, but I've finally reached a point where I'm ready to show it to the world. Cheevly aims to be a full-featured natural language IDE. If you've visited the website (https://www.cheevly.com), you'll find that the branding is somewhat sensationalized, though it is meant to be tongue-in-cheek. My goal is to empower users to build…
2024
- 19CA
Hey HN, Most AI “agents” I’ve tried are basically chatbots with amnesia — they forget everything the moment you close the tab and can’t do anything unless you’re sitting there watching them. I wanted real AI coworkers that just… work. So I built Computer Agents (aiOS). Every agent you create gets its own isolated computer in the cloud — complete with persistent memory, a real file system, code execution environment (with automatic dependency management), and the ability to run scheduled or webhook-triggered tasks 24/7. You give it a goal (“research this market and email me a report…
Mar 2026 · computer-agents.com
- 20DA
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
- 21
- 22IS
Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…
2025
- 23MA
This weekend I built a multi-agent coding system which, quite unexpectedly, beat Claude Code on Stanford's Terminal Bench! The architecture is straightforward, consisting of an orchestrator agent that deploys explorer & coder subagents to complete complex terminal based tasks, utilising an intelligent context sharing mechanism along the way which makes it all work. The repo has a lot of technical details, and all the code and prompts for you to play around with if you'd like! I had a lot of fun making this, I hope you have fun reading the README, using it yourself, or even extending it! As…
2025 · github.com
- 24MO
Hey everyone, We're excited to introduce MarinaBox, an open-source toolkit for creating isolated desktop/browser sandboxes tailored for AI agents. Over the past few months, we've worked on various projects involving: 1. AI agents interacting with computers (think Claude computer-use scenarios). 2. Browser automation for AI agents using tools like Playwright and Selenium. 3. Applications that need a live-session view to monitor AI agents' actions, with the ability for human-in-the-loop intervention. What we learned: All these scenarios share a common need for robust infrastructure. So,…
2024 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →