Alternatives
Products that do what SuperQode does
The harness interoperability layer for coding agents
- 1
Open-source unified interface for agent harnesses
21d ago · harnessrouter.ai
- 2
- 3
- 4ZY
May 2026 · zot.sh
- 5
- 6
- 7
- 8RC
Hi HN, we built SuperHQ, an open source app that runs AI coding agents in isolated microVM sandboxes instead of directly on your machine. Each agent gets its own VM with a full Debian environment. You mount your projects in, writes go to a tmpfs overlay so your host is never touched, and you get a diff view to accept or discard changes. API keys never enter the sandbox. We also just launched remote.superhq.ai which acts as a remote control for SuperHQ, allowing you to access your workspaces and agents from anywhere.
Apr 2026 · github.com
- 9GA
Hey HN! Wanted to show our open source agent harness called Gambit. If you’re not familiar, agent harnesses are sort of like an operating system for an agent... they handle tool calling, planning, context window management, and don’t require as much developer orchestration. Normally you might see an agent orchestration framework pipeline like: compute -> compute -> compute -> LLM -> compute -> compute -> LLM we invert this so with an agent harness, it’s more like: LLM -> LLM -> LLM -> compute -> LLM -> LLM -> compute -> LLM Essentially you describe each agent in either a self contained…
Jan 2026 · github.com
- 10
- 11AH
May 2026 · ahk.cardor.dev
- 12
HarnessRouter▲238Bring the world's best AI agents into your app, with one API
Jul 2026 · harnessrouter.ai
- 13
- 14
- 15
- 16
- 17PA
Hey HN. http://peerd.ai is an AI agent harness that lives entirely in your browser as a web extension. You don’t have to install a separate “AI browser”. You don’t have to bolt on or run some external process or manage a clunky mcp integration. It’s just a fully contained web extension, written in no build vanilla JS with minimal non-browser dependencies, using your own provider keys, and Apache 2. This isn’t just a fun hack. While it has largely been a solo side project, I genuinely believe the browser and the web could be the most natural platform for AI agents to operate safely,…
Jun 2026 · github.com
- 18AH
2025 · github.com
- 19
Hey HN! We are building HarnessRouter, a canonical API for running Codex, Claude Code, Hermes, and other managed agent harnesses as your product backend. Before building HarnessRouter, I used to build our own agent harness for our products. I tried LangGraph, agent SDKs from different vendors, pydantic, LLM tool use / function call, and so on. It's a very heavy lifting engineering effort, and I am disappointed about the agent deliveries compared to what Codex, CC can deliver. That changed my mindset. The frontier labs and famous open source communities are already putting so much…
20d ago · github.com
- 20
- 21
- 22ST
Hey HN, we’re Avi, Kiet, and Satya. We’re building Superset, an open-source terminal made for managing a bunch of coding agents (Claude Code, Codex, etc) in parallel. - Superset makes it easy to spin up git worktrees and automatically setup your environment - Agents and terminal tabs are isolated to worktrees, preventing conflicts - Built-in hooks [0] to notify when your coding agents are done/needs attention, - A diff viewer to review the changes and make PRs quickly We’re three engineers who’ve built and maintained large codebases, and kept wanting to work on as many features in…
Dec 2025 · superset.sh
- 232C
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
- 24
Ranked by how close each launch is in meaning, then by votes. Refine with a description →