AI Trading Bootcamp

About this bootcamp

This is a live five-week bootcamp taught by Rob Grzesik, CEO of Lumiwealth BotSpot. He helped build Voyager into a billion-dollar crypto company, and he built technology at Greystone, a mortgage lender, that handled over $3 billion in transactions. He also has a Master of Finance, 25+ years of coding experience, and 15+ years in financial technology.

You are not watching lecture videos. Each week you show up on Zoom for a hands-on class, build the workflow live, place a reviewed trade, and leave with a recording you can replay forever. You also join the community: work with other students, retake future classes, and keep new material we add going forward.

Week one gets your AI trading workspace working: Claude, Codex, Cursor, BotSpot, market data, and your broker. You place your first stock or ETF trade the same night.

Week two turns AI into a research desk that saves hours. You pull filings, financials, earnings, insider data, and news, then build scanners that surface the next candidates. Stop spending hours building watchlists. Stop guessing when you skip the work.

Week three has two jobs. First, you learn Claude with TradingView to analyze charts and setups. Second, you learn to trade options, crypto, crypto futures, and prediction markets with AI doing the research and preparing the trades. Even if you are not an options trader yet, Claude, Codex, Cursor, or BotSpot can help you understand and build complex options trades.

Week four turns a plain-English idea into a deterministic Python strategy you can read and trust. You backtest it, review the results, then iterate and improve. That is how you learn from the past before the same rules place trades without babysitting every click.

Week five finishes with an AI trading agent you control. It can research, decide, and place trades on a schedule inside guardrails you set. When the cohort ends, that workspace keeps working for you.

Plan on about one to two hours for each live Zoom call, plus about one to two hours of practice between sessions on your own setup with the prompts and checklists from class.

You also get lifetime access, so you can retake later cohorts, keep new material we add, and join the optional five-week trading competition if you want a shared scoreboard. Real money is encouraged. The front door is using AI to research, review, and trade with control.

Course syllabus: Week 1: Set Up Your Tools and Place Your First Trade

Connect Claude, Codex, BotSpot, and your broker, place your first reviewed stock or ETF trade with real money if you want, and join the optional five-week trading competition.

Finish night one with a working AI trading desk and a real trade on the books. Real money is encouraged. You place the trade yourself. Install and configure Claude and Codex for trading work Connect BotSpot, live market data, and your brokerage account Set up the tools you will use for research, writing code, broker access, and placing trades Analyze one stock or ETF live and place your first reviewed trade Join the optional five-week trading competition with one fixed brokerage balance

Week 2: Research Stocks with AI and Build Market Scanners

Use AI to research stocks and ETFs with filings, financials, earnings, news, and insider data, then build a market scanner that surfaces the next candidates.

Use AI to research stocks and ETFs in class, verify the evidence, and build a scanner so you are not hunting charts by hand. Research multiple stocks or ETFs live, not just one ticker Learn how to use AI agents to read SEC filings, financial statements, earnings releases, and earnings-call transcripts Get AI to pull and analyze company news, competitors, industry research, and macro factors Get AI to inspect reported insider transactions and ownership filings Build a market scanner with Claude, Codex, or Cursor for setups such as opening-range breakouts, momentum, gap-and-go, or unusual volume Compare bull and bear evidence, then place the next reviewed stock or ETF trade for the competition

Week 3: Trade Options, Crypto, and Prediction Markets with Claude and TradingView

Use Claude with TradingView, turn chart ideas into trades, and place a reviewed trade in options, crypto futures, or Polymarket.

Week two covered stocks, ETFs, and scanners. This week opens options, crypto, crypto futures, and prediction markets with Claude on TradingView. Use Claude, Codex, or Cursor with TradingView charts and alerts Read charts with common tools such as VWAP, RSI, Bollinger Bands, and Fibonacci as working examples Translate TradingView / Pine Script indicators into Python so Claude can use those indicators and trade with them Learn the basics of options trades so you can review them and trade safely Expand into crypto and crypto futures with Bitunix, Coinbase, Kraken, KuCoin, or Binance Research and place a prediction-market trade on Polymarket Place one reviewed trade in options, crypto or crypto futures, or Polymarket

Week 4: Build a Python Trading Strategy That Runs Automatically

Turn one plain-English setup into a Python strategy, backtest it, improve it, and run the same rules automatically on your broker with real money under your control.

Leave with a simple Python strategy you understand: clear rules, a backtest you can read (a historical simulation of how the rules would have traded), and code that can place those same trades on your broker without you rewriting them every day. Describe one repeatable setup in plain English with clear entry and exit rules Use Claude, Codex, Cursor, or BotSpot to turn those rules into a working Python strategy Run a backtest and learn how to read the results so you can improve the strategy Tweak the strategy and run the backtest again instead of chasing a pretty chart Run the strategy so it can place trades from the same rules automatically Use a current strategy signal for the next competition trade when it fits

Week 5: Build an AI Trading Agent That Trades for You 24/7

Create an AI-powered agent that can research, decide, and trade automatically for you every day on a schedule with real money under your control.

Week four was a Python strategy with fixed rules in code. Week five is an AI agent that can think, research, and act in plain English inside limits you set, around the clock on your brokerage account with real money. Learn how an AI trading agent differs from a fixed Python strategy Build an AI trading agent that can run on a schedule (daily, hourly, every five minutes, or whatever you choose), researching and trading while you sleep or go to your day job Learn how to write and refine system prompts so the agent does what you actually want Learn how to build AI trading teams that debate each other before a trade is prepared Study real examples such as Ray Dalio style principle-driven agents and Citadel style research teams Learn how to compare models such as Gemini, OpenAI, Anthropic, Grok, and open-source options so your agent stays smart and cost-effective Add guardrails: approvals, size limits, alerts, logs, failure handling, and a stop control Prove the agent with evals and backtests before you run it with real money on a schedule Schedule the agent on your brokerage account Trading competition finishes. Review the leaderboard and see who won