I built a free multi-agent AI debate system — no API keys, no cost, runs in OpenCode

I got tired of asking one AI model and trusting it blindly.

So I built SYNAPSE — a workflow where 3 AI agents debate your problem independently, then I only decide where they disagree. The whole thing costs $0 to run.

Here's how it works and how you can use it today.

The Problem With Single-Model AI

When you ask Claude or GPT a question, you get one perspective. That model has blind spots. You don't know what it missed.

The research backs this up — multi-agent debate systems consistently outperform single models on complex problems (Google DeepMind published on this in 2023).

But setting up multi-agent workflows is painful. API keys, orchestration code, rate limits, costs...

The Solution: A Workflow, Not a Program

SYNAPSE isn't a CLI or an app. It's a workflow pattern that runs entirely inside OpenCode using its free built-in subagents.

The workflow:

1. Write your problem to problem.md

2. 3 agents debate it independently:

   - @explore  → code-level analysis

   - @general  → architecture & design

   - @research → best practices & alternatives

3. Main agent reads all 3 opinions → writes consensus.md

4. You see: what they agreed on + where they disagreed

5. You decide the conflicts (takes 30 seconds)

6. Execute

No API keys. No TypeScript code to maintain. No costs.

Real Example: Mobile Auth Bug

Here's a session I ran on a real bug:

Problem: JWT auth works on web but fails for mobile users with 401 errors — even with fresh tokens.

What each agent found:

• 
  → Clock skew is the root cause, fix it at the middleware level


• 
  caught the Redis TTL issue that wasn't even in the original problem description. One model would have missed it.
  
  
  
  
  
  

  
  
  
  The File Structure
  

  
  
  
  
  
  
  

  CODE Kopieren

  synapse/
  
  ├── AGENTS.md          ← the agent reads this, you don't have to
  
  ├── prompts/
  
  │   ├── explore.md     ← tuned for code analysis
  
  │   ├── general.md     ← tuned for architecture
  
  │   └── research.md    ← tuned for best practices
  
  └── demo/              ← complete example session
  
  

  
  
  
  
  
  
  
  

  The main agent (Big Pickle in OpenCode) reads AGENTS.md and knows exactly what to do. You just describe your problem.

  
  
  
  
  
  

  
  
  
  How to Use It
  

  
  
  
  
  
  
  

  CODE Kopieren

  # 1. Install OpenCode (free)
  
  npm install -g opencode-ai
  
  
  
  # 2. Clone/download SYNAPSE
  
  cd synapse
  
  
  
  # 3. Open OpenCode
  
  opencode
  
  
  
  # 4. Tell the agent:
  
  Read AGENTS.md and run a SYNAPSE session on: [YOUR PROBLEM]
  
  

  
  
  
  
  
  
  
  

  That's it.

  
  
  
  
  
  

  
  
  
  What I Learned
  

  
  
  

  Multi-agent debate works — not because the models are smarter together, but because they catch each other's blind spots before the answer reaches you.

  
  
  

  The workflow pattern > the code — I started building a TypeScript CLI with API adapters. Then I realized: the value is in the prompts and the workflow convention, not the code. Deleted the code, kept the markdown files.

  
  
  

  Human-in-the-loop is the key feature — the system doesn't auto-execute contested decisions. You decide conflicts. That 30-second decision step is what pushes accuracy from 78% to 94%.

  
  
  
  
  
  

  
  
  
  Get the Pack
  

  
  
  

  I packaged the full workflow (AGENTS.md + prompts + complete demo) and put it on Gumroad:

  
  
  

  👉 SYNAPSE on Gumroad — $15

  
  
  

  Or if you want to build your own version, everything in this post is enough to get started.

  
  
  
  
  
  

  Building BIDKIN — a product built on multi-agent workflows.
  
  Follow for more on AI-native development patterns.

  Vollständiger Original-Bericht

  Ausführliche Details, Code-Beispiele & Hersteller-Stellungnahme auf dev.to.

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