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A full trading firm, made of AI agents

March 23, 2026via github · @TauricResearch
AImulti-agentfinanceopen-sourceworkflow

What they built

Imagine a trading firm with a full team — someone reading the news, someone studying the numbers, someone arguing the bull case, someone arguing the bear case, a risk manager pumping the brakes, and a fund manager making the final call. TauricResearch built exactly that, except every person on the team is an AI agent.

They all talk to each other, push back on each other, and eventually agree on a decision. No single AI making a gut call — a structured debate between specialists.

Why this caught our eye

Finance is just the demo. The real idea here is that some decisions are too complex for one perspective — even an AI one. You get better answers when you force multiple viewpoints to argue it out first.

Think about what that could look like for a design agency reviewing a client brief, a restaurant group evaluating a new location, or any business doing due diligence before a big contract. The same architecture works anywhere the stakes are high enough to warrant the extra thinking.

The system also lets you use cheaper AI models for simple tasks and more powerful ones for the hard judgment calls. Smart economics, not just smart technology.

Quick glossary

AI agent — An AI that doesn't just answer a question but takes a series of steps to complete a task. More like a junior employee than a search engine.

Multi-agent system — Several AI agents working together, each with a specific role, handing off to each other like a real team would.

Open-source — The blueprints are public. Anyone can look at how it's built, copy it, or adapt it for their own use — for free.

LLM (Large Language Model) — The underlying technology behind tools like ChatGPT or Claude. The "brain" that each agent runs on.

Worth sitting with

What decision in your business would genuinely benefit from five different expert perspectives arguing before anyone commits? That's the question this project quietly raises.

Written by David at AC0.AI. Follow on @ac0hero

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