Building a 7-Agent AI Trading Desk with OpenClaw
This article outlines a practical case study of setting up a 7-agent AI trading desk using OpenClaw, which significantly changes the manual trading process. Running on a Mac mini with Claude as the primary AI, this setup is designed to automate various aspects of the stock trading workflow.
Key Details
- AI Agents: The setup consists of seven AI agents managing distinct tasks.
- Wilson (Opus) — The orchestrator, coordinating all activities.
- Scanner (Sonnet) — Analyzes 2,100+ stocks each morning and scores them based on multiple factors.
- Researcher (Sonnet) — Provides deep research briefs on stocks with fundamentals and insider activity.
- Regime (Sonnet) — Monitors market health and advises on favorable conditions for trading.
- Investigator (Sonnet) — Scans Reddit for stock mentions using free .json endpoints, intercepting misinformation.
- App Builder (Sonnet) — Builds and maintains dashboard apps.
- Framework and Tools: Leverages OpenClaw for structuring the trading desk with Claude powering the AI processing, and uses Sonnet-based agents.
- Apps Developed: Four custom Flask dashboards were built.
- Trade Tracker — Tracks stocks and options portfolio, managing position sizing and stop losses.
- Mission Control — A central hub for activity feeds, reminders, and real-time agent updates.
- Daily Journal — Records trades, lessons, and trader mood.
- Data and Automation: Utilizes historical stock charts analysis by Claude's vision AI, extracting critical data such as pattern types and pivot prices. Implements cron jobs to automate recurring tasks, including pre-market prep, technical signal monitoring, and Reddit scanning.
Lessons Learned
- Sonnet agents are efficient for niche tasks and cost-effective.
- Avoid configuration changes during market hours to prevent disruptions.
- Use
launchdto manage processes, ensuring they restart if terminated. - Direct JSON endpoint access for Reddit is effective without API requirements.
- Regular persistence of trading data is vital to prevent data loss.
📖 Read the full source: r/openclaw
👀 See Also
Personal Finance Dashboard Built with Claude AI: Self-Hosted with Google Sheets Backend
A developer built a full-stack personal finance dashboard using Claude AI that aggregates investments across stocks, mutual funds, physical gold, and fixed deposits. The app runs on a spare PC, uses Cloudflare Tunnel for serving, and stores all data in the user's own Google Sheets.
Building a Voice Assistant with OpenClaw, Alexa, and Local LLM
A developer built a voice-first assistant using OpenClaw as the AI agent backbone, Alexa for voice input, and a local LLM (Ollama with Qwen 2.5 3B) to handle general knowledge queries with sub-second response times and reduced API costs.
OpenClaw experiment tests AI temporal continuity with memory and commitment systems
A team has been using OpenClaw for 8 days to test whether persistent memory and accumulated commitments can create temporal continuity in AI. They've implemented episodic/distilled memory splits, commitment checking, and per-turn state logging in JSONL.
Developer Rebuilds LinkedIn Research Agent After Account Restriction
A developer rebuilt their OpenClaw agent to use LinkedIn's API instead of browser automation after mass-visiting 200 profiles triggered an account restriction. The new approach uses direct API calls for cleaner data and avoids detection.