Aigon is an open-source tool that runs multiple AI coding agents in parallel on the same feature specified in a markdown spec and uses an LLM judge to select the best implementation, with a visual dashboard and optional scheduling.
Hi. Been building something I think folks might find useful. I was using Claude Code daily on a project and kept wanting to throw the same feature at Codex or Gemini too and compare the different implementations and ideally choose the best one. There was no easy way to do that without a heap of manual worktree juggling. So I built Aigon. What it does: you write a feature spec as markdown in your repo, pick which agent CLI you want (currently supports Claude Code, Codex, Gemini, Cursor CLI, Kimi K2, OpenCode and AmpCode), and Aigon runs them in parallel in separate git worktrees on the same feature. Then choose an agent/model as the LLM judge, which scores all implementations and picks a winner. You accept the judge's decision and can also cherry-pick from the runners-up. No third-party API keys needed, it runs within the standard agent CLI sessions (claude, codex, gemini, etc), so you're using your own subscriptions. The dashboard spins up features in worktrees with agents running in tmux sessions. You can always jump into a session with your own tools and finish interactively. It has similarities to other spec-driven AI frameworks like OpenSpec and spec-kit. I've differentiated with: \- Multi-agent parallel runs + LLM judge \- Visual kanban dashboard. \- Scheduled autonomous builds (Aigon Pro — paid tier) — kick off a feature or a whole set of features and check out the results in the morning. Pro's "conductor" sequences features in dependency order, pauses on failure, runs unattended. If an agent runs out of quota (eg Claude Code hits the limit), it automatically switches to your configured backup agent (eg Codex). Great for maxing out subscription quota windows you'd otherwise waste. \- Aigon doesn't talk to models directly, it orchestrates the CLI agents you are already paying for. You control the spend through your own subscriptions and aigon has some handy dashboards to show where your quotas are at. It's evolved a fair bit from where it started as a couple of slash commands inside Claude Code. It grew into the kanban dashboard to help keep track of multiple concurrent features, and most recently picked up the scheduling and auto-switching stuff. Happy to answer anything in the comments — links to the repo and a 3-min demo in my first comment below. Cheers, John
A tool that lets you create AI agents with opposing goals to simulate arguments, useful for sales prep, idea stress-testing, and difficult conversations. Runs locally without API key in mock mode.
The author built an open-source agent that uses a panel of different LLMs with a judge and synthesizer for hard reasoning steps, alongside cost-aware routing, layered memory, governance, and subagent support. It is alpha software with mixed benchmarks on fusion effectiveness.
The author demonstrates JackHamr, a platform where autonomous AI agents build a dark-mode toggle feature from spec to deployment, with approval gates and sub-agent tasks.
The author shares lessons learned from deploying a multi-agent AI system for a law firm using Claude and LangGraph, highlighting the success of confidence-score handoffs and the critical need for human-in-the-loop oversight to prevent hallucinations.