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 launchd to 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.