{"slug": "i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode", "title": "I built a free multi-agent AI debate system — no API keys, no cost, runs in OpenCode", "summary": "A developer built SYNAPSE, a free multi-agent AI debate system that runs entirely inside OpenCode without API keys or costs. The workflow uses three AI agents to independently analyze a problem, then presents consensus and disagreements for human decision, catching blind spots that a single model would miss. In a real debugging session, the system identified a Redis TTL issue not in the original problem description, leading to a fix for mobile JWT auth failures.", "body_md": "I got tired of asking one AI model and trusting it blindly.\n\nSo 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.\n\nHere's how it works and how you can use it today.\n\nWhen you ask Claude or GPT a question, you get one perspective. That model has blind spots. You don't know what it missed.\n\nThe research backs this up — multi-agent debate systems consistently outperform single models on complex problems (Google DeepMind published on this in 2023).\n\nBut setting up multi-agent workflows is painful. API keys, orchestration code, rate limits, costs...\n\nSYNAPSE isn't a CLI or an app. It's a **workflow pattern** that runs entirely inside OpenCode using its free built-in subagents.\n\nThe workflow:\n\n```\n1. Write your problem to problem.md\n2. 3 agents debate it independently:\n   - @explore  → code-level analysis\n   - @general  → architecture & design\n   - @research → best practices & alternatives\n3. Main agent reads all 3 opinions → writes consensus.md\n4. You see: what they agreed on + where they disagreed\n5. You decide the conflicts (takes 30 seconds)\n6. Execute\n```\n\nNo API keys. No TypeScript code to maintain. No costs.\n\nHere's a session I ran on a real bug:\n\n**Problem:** JWT auth works on web but fails for mobile users with 401 errors — even with fresh tokens.\n\n**What each agent found:**\n\n`verify()`\n\nhas no `clockTolerance`\n\n+ Redis TTL has no buffer`clockTolerance: 300`\n\nis the standard fix + send server timestamp for mobile**Consensus (91%):**\n\n`clockTolerance: 300`\n\nto JWT verify`notBefore: '-30s'`\n\nto token signing**My decision:** Later — mobile release in 3 days, minimum risk.\n\n**Result:** 3 files changed, mobile auth fixed, web auth unchanged.\n\nThe key thing: ** @explore caught the Redis TTL issue** that wasn't even in the original problem description. One model would have missed it.\n\n```\nsynapse/\n├── AGENTS.md          ← the agent reads this, you don't have to\n├── prompts/\n│   ├── explore.md     ← tuned for code analysis\n│   ├── general.md     ← tuned for architecture\n│   └── research.md    ← tuned for best practices\n└── demo/              ← complete example session\n```\n\nThe main agent (Big Pickle in OpenCode) reads `AGENTS.md`\n\nand knows exactly what to do. You just describe your problem.\n\n```\n# 1. Install OpenCode (free)\nnpm install -g opencode-ai\n\n# 2. Clone/download SYNAPSE\ncd synapse\n\n# 3. Open OpenCode\nopencode\n\n# 4. Tell the agent:\nRead AGENTS.md and run a SYNAPSE session on: [YOUR PROBLEM]\n```\n\nThat's it.\n\n**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.\n\n**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.\n\n**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%.\n\nI packaged the full workflow (AGENTS.md + prompts + complete demo) and put it on Gumroad:\n\nOr if you want to build your own version, everything in this post is enough to get started.\n\n*Building BIDKIN — a product built on multi-agent workflows.*\n\n*Follow for more on AI-native development patterns.*", "url": "https://wpnews.pro/news/i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode", "canonical_source": "https://dev.to/bidkineg/i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode-49ij", "published_at": "2026-06-19 12:46:22+00:00", "updated_at": "2026-06-19 13:07:24.122555+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-agents", "developer-tools"], "entities": ["SYNAPSE", "OpenCode", "Google DeepMind", "Claude", "GPT", "Gumroad", "BIDKIN"], "alternates": {"html": "https://wpnews.pro/news/i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode", "markdown": "https://wpnews.pro/news/i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode.md", "text": "https://wpnews.pro/news/i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode.txt", "jsonld": "https://wpnews.pro/news/i-built-a-free-multi-agent-ai-debate-system-no-api-keys-no-cost-runs-in-opencode.jsonld"}}