Running Hyperliquid Trading Agents with OpenClaw
The open-source playbook for deploying autonomous trading agents on Hyperliquid. Built by the Algo Traders Club community — operators who've been in the trenches building, breaking, and shipping trading agents for over a year.
Why This Exists
What Operators Build Here
The Curriculum
4 Parts · 12 Modules · Open Source
This is the path from zero to operating a live trading agent on Hyperliquid. It's the distilled knowledge of a year+ of building in this space. The outline is public. The codebase is public. ATC members get the full walkthroughs, live sessions, and the community of operators building alongside you.
The Stack
Every tool is open source. Every layer is documented.
OpenClaw
AI agent platform (145K+ GitHub stars)
Hyperliquid
Largest perps DEX ($1T+ monthly volume)
CCXT
Unified crypto exchange API (100+ exchanges)
Python 3.12 + UV
Modern Python with Rust-speed tooling
SQLite
Zero-config database for trade logging
DigitalOcean
One-click hardened cloud deployment ($24/mo)
Who This Is For
You belong here if:
- • You're a developer comfortable with AI coding tools (Claude Code, Cursor, Copilot)
- • You're drawn to permissionless, on-chain opportunities
- • You want to understand the full stack — not just copy-paste someone else's bot
- • You value sovereignty: income you control, infrastructure you own, no gatekeepers
- • You want to be in the room with other operators who are actively building
This probably isn't your thing if:
- • You're completely new to programming (learn basics first, come back anytime)
- • You're looking for a get-rich-quick scheme or a "magic bot"
- • You want someone to hand you a profitable strategy
- • You're uncomfortable managing your own keys and risk
- • You want a passive, watch-videos-and-forget experience
Open Source Knowledge. Operator Community.
You can absolutely do this alone with the open source materials. But if you want to move faster and be around people doing the same thing, this is the room.
- • Full curriculum outline and structure
- • Hyperliquid Operator codebase (GitHub, MIT license)
- • Module summaries and learning objectives
- • SKILL.md, CLAUDE.md, and all documentation
- Everything you need to go solo is free and open source.
- • Full module walkthroughs with commentary and context
- • Weekly live sessions — building, debugging, strategizing together
- • Community strategy sharing and peer code reviews
- • Direct access to Fodé and experienced operators
- • Private channels for real-time discussion
- • Ongoing experiments, findings, and historical data
- The curriculum tells you what to learn. The community is where operators build together.
FAQ
Do I need coding experience?
Basic programming skills, yes. You should be comfortable with the command line and able to read Python code. But you don't need to be an expert — most of us are 'vibe coders' who use AI tools like Claude Code or Cursor to build and iterate. If you can describe what you want in English and verify the output, you'll be fine.
How long does the curriculum take?
6-8 weeks at 5-10 hours/week if you go front to back. But it's self-paced — some people sprint through it in 2 weeks, others take a module a month. The content isn't going anywhere.
Is this actually open source?
The curriculum outline, the Hyperliquid Operator codebase, and all documentation are MIT-licensed and on GitHub. Fork it, improve it, teach from it. ATC membership gets you into the community — live sessions, strategy discussions, code reviews, and the ongoing experiments we're running.
How much does it cost to run a trading agent?
$24/month for the DigitalOcean Droplet, $5-20/month for LLM API costs (Anthropic or OpenAI for OpenClaw). Plus whatever capital you trade with — Hyperliquid minimum is about $10, though we'd recommend starting with $50-100 for meaningful testing.
Why Hyperliquid?
Largest perpetual futures DEX. Over $1 trillion monthly volume. Fully on-chain order book. Mature CCXT integration. Active developer ecosystem. It's the best venue for algorithmic trading on-chain, and it's where our community has the most depth of experience.
Will this make me money?
This is a community of builders, not financial advisors. Trading involves real risk of real loss. The curriculum teaches the technical infrastructure — building agents, managing risk, deploying safely. Whether any strategy profits depends on market conditions, your risk management, and your own judgment. We always start with paper trading and we share both wins and losses openly.
What's the difference between ATC and a trading course?
Courses have a teacher and students. ATC has operators at different stages sharing what they're building. Fodé has the most experience in the room — over a year of building trading agents with some of the most-starred Hyperliquid repos on GitHub — but members regularly contribute strategies, find bugs, and push the community forward. You're joining a shop floor, not a classroom.
The Future Belongs to Operators
AI agents that trade 24/7. Risk management that never sleeps. Infrastructure you control. No permission needed. This is the new frontier — and we're building it together.