TL;DR: How To Build High-Performing Trading Strategies With AI condenses Larry Connors’ quantitative research process into 30-plus hours across four sessions. You feed ChatGPT-style tools your trade ideas, the AI drafts the rules, and Connors shows you how to test what comes back before real money touches it.
Across four long recorded sessions, Larry Connors shows traders how to turn AI tools into tested, rules-based systems without writing code. Most algorithmic trading education assumes you can already program; Connors assumes you can describe an idea in plain English.
Inside the Four Sessions
Each session runs six hours or longer, pushing total runtime past 30 hours. The first session lays the foundation: how markets overreact, why fear and greed keep producing the mean reversion edges Connors has published on for decades, and how ChatGPT-style tools can widen a statistical edge rather than replace it. The later sessions push into advanced AI strategy building and thematic AI trading, hunting for alpha that most screens miss and carrying each idea through to a fully executable system.
Prompt engineering for finance runs through the whole thing. Connors treats a prompt the way a quant treats a hypothesis: specific and falsifiable, phrased so the output can be tested.
From Prompt to Tested Rule Set
The build sequence is fixed: state the idea, let the AI draft the entry and exit rules, then validate before any capital goes in. Connors is blunt about the failure mode. AI generates candidate strategies quickly, and it produces overfitting just as quickly, so the validation framework, not the chatbot, is where the value sits.
In practice that means out-of-sample checks and paper trading come before funding anything, and his method for backtesting strategies is the discipline that separates this course from prompt-and-hope content.
About Larry Connors
Connors built his reputation the slow way: the Connors RSI indicator, the book Short-Term Trading Strategies That Work, and decades of published quantitative trading research through TradingMarkets, the firm he founded. TradingMarkets promotes this program as used by more than 100 portfolio managers, prop desk traders, and high-net-worth investors. Treat that as the vendor’s marketing line; we could not verify it independently, and it says nothing about what you will earn.
The Mismatch Buyer, Spelled Out
The buyer this course will disappoint wants tomorrow’s signals handed over. Connors hands over a process, and the process includes homework. If validating a system on historical data sounds like a chore you will skip, the sessions will sit unwatched. The same goes if you came for intraday tactics: GeniTrader also reviews Connors’ Professional Day Trading for Success, which covers live execution, while this one stays on the research side. And if you prefer trading psychology content to spreadsheets, the Larry Connors AI course will feel like work, because it is.
Trading Strategies With AI: The Sticking Points
Is Trading Strategies With AI worth it?
If a repeatable build process appeals to you more than finished signals, yes. The 30-plus hours cover idea generation through validation in enough depth to work from directly. Traders expecting a plug-in system will find homework instead, and the payoff depends on doing the testing Connors assigns.
Does Larry Connors have real credentials behind this course?
Yes, and they are checkable. Connors created the Connors RSI indicator, wrote Short-Term Trading Strategies That Work, and founded TradingMarkets. The statistical framework underneath the AI angle matches the research he has published for decades.
Do I need to know how to code?
No. The program targets traders without a programming or quant-finance background. You describe the strategy logic in plain language, the AI tools handle implementation, and the prompt engineering sessions make the output precise enough to test.
How is this different from Connors’ day trading program?
This is the research program: four sessions on building and validating rules-based systems with AI tools. Professional Day Trading for Success is the execution program, focused on managing live intraday trades. Both use Connors’ overreaction framework, but they solve different jobs.
The Verdict on the Build-It-Yourself Pitch
What earns the recommendation is the order of operations. Connors puts validation after the AI build and refuses to skip it, which is the opposite of how most AI trading content gets sold in 2026. The weak spot is inherent to the subject: models change, and some tool-specific walkthroughs will age faster than the framework. The framework is what you are buying. Treat it as coursework on a method; what you choose to trade with it stays your call.
