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.
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...
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.
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:
verify()
has no clockTolerance
- Redis TTL has no buffer
clockTolerance: 300
is the standard fix + send server timestamp for mobileConsensus (91%):
clockTolerance: 300
to JWT verifynotBefore: '-30s'
to token signingMy decision: Later — mobile release in 3 days, minimum risk.
Result: 3 files changed, mobile auth fixed, web auth unchanged.
The key thing: ** @explore caught the Redis TTL issue** that wasn't even in the original problem description. One model would have missed it.
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.
npm install -g opencode-ai
cd synapse
opencode
Read AGENTS.md and run a SYNAPSE session on: [YOUR PROBLEM]
That's it.
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%.
I packaged the full workflow (AGENTS.md + prompts + complete demo) and put it on Gumroad:
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.