I Built 174 AI Agents That Fight Each Other.
Source: Dev.to
Overview
This submission was created for the DEV April Fools Challenge. Most multi‑agent systems make agents cooperate; BlackSwanX makes them fight.
BlackSwanX is an adversarial intelligence engine where 200 citizen AI agents argue, panic, and emotionally spiral while a BlackSwan Assassin tries to “murder” the consensus. It runs 100 % locally on Ollama – zero API cost, maximum chaos.
It deploys a Vedic Astrologer, a Panic Seller, a Chaos Mathematician, a Gen Z Culture Decoder, and a Street‑Smart Hustler (who will tell you “your pitch deck is pretty, show me your bank account”) to predict the future… together, by fighting. The system doesn’t solve real‑world problems; it simply finds where the crowd is wrong.
👉 GitHub Repo – BlackSwanX
Quick Start (≈ 2 minutes)
git clone https://github.com/Kalki-M/BlackSwanX.git
cd BlackSwanX
ollama pull llama3.2:3b && ollama pull phi4:14b
pip install -r requirements.txt
bash start.shExample Run — “Will NVIDIA crash when the AI bubble pops?”
- Kill Shot: Quantum computing making GPUs obsolete (10 % probability)
- Citizens: 25 % bull / 65 % bear
- Dissonance: 33.6 / 100 — MAXIMUM CHAOS
- Antifragile Play: Diversify into quantum‑computing partnerships
How It Works
BlackSwanX doesn’t seek consensus; it seeks the widest gap—the cognitive dissonance between what the masses believe and what the experts fear. That gap is where the “alpha” lives.
The Comparison
| Feature | BettaFish | MiroFish | BlackSwanX |
|---|---|---|---|
| Cost | $$$ (7 API keys) | $$ (2 keys + Zep Cloud) | $0 (Ollama) |
| Setup time | 30 + min + PostgreSQL | 15 min + Zep account | 2 min, zero config |
| Expert agents | 5 | 0 (generic personas) | 174 domain experts |
| Citizen agents | 0 | ~100 per run (OASIS) | 200 per run (Shadow Swarm) |
| Citizen simulation | None | OASIS framework | Shadow Swarm |
Models (all local, all free)
| Role | Model | Purpose |
|---|---|---|
| Swarm | llama3.2:3b | 200 biased citizens arguing |
| Assassin | phi4:14b | Kill‑shot reasoning |
| Nexus | mistral-small:24b | Synthesis + DAG |
The Pipeline
- Crawl – Gather data from five free sources (DuckDuckGo, Reddit, Hacker News, YouTube, Twitter).
- Assassin’s Mark –
phi4:14bidentifies the “Kill Shot” before citizens start debating. - Shadow Swarm – 200 citizen agents react with biased, emotional opinions.
- Cognitive Dissonance Matrix – Calculates where belief diverges from reality.
- Decision‑Ready Map – Produces a Linchpin and an Antifragile Play.
- Self‑Learning (SONA) – After each run, SONA audits all agents:
- Boosts citizens that caught risks others missed (×2 weight).
- Demotes agents that missed critical threats (×0.3).
- Stores patterns in a ReasoningBank.
The more you use it, the smarter (and more chaotic) it becomes.
Community favorite because nothing says “April Fools” like deploying a Vedic Astrologer and a Panic Seller as serious financial analysts and calling it an intelligence engine. The project is technically real, completely unhinged, and genuinely runs on your laptop.