Free Lesson
How AI Agents Change the ML for Trading Workflow
30 min
Oct 7, 2026 11:00 AM
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What you'll learn
See where an agent carries real work
Which parts of a research pipeline a coding agent can build, and what you must specify before it starts.
Keep the judgment that decides the result
What the label means, whether validation prevents look-ahead, and whether the number at the end is real.
Read a result honestly, agent or not
Naive against corrected inference, and zero-cost against costed, on the same strategy.
Why this topic matters
Coding agents and research agents now write a large share of the code in a quantitative workflow, and the demos make it look like the whole job. It is not. This session runs the ML for Trading workflow end to end, shows the two places an agent genuinely carries the work, and names the decisions that stay with the person running it. It previews the entry-point workshop, ML for Trading in the Age of AI Agents.
