Michael Rishi Forrester does AI workforce transformation at Accenture LearnVantage, after three years at KodeKloud and about thirty years in IT before that. Whitney and Coté talk with him about running tabletop role-playing games with AI. He built his 19-year-old son a homebrew campaign on top of Lancer, the sci-fi mech game, in about 20 hours instead of the 60 to 100 it would have taken him before - and got a website, a virtual tabletop and some Discord bots out of it. What breaks is the interesting part: there was a night when every shot did one damage, because the model had quietly stopped using the dice harness and started doing the math itself.

From there it turns into an argument about where AI actually pays off at work. Michael’s position is that the ROI is at the workflow level and there is no organizational ROI to go find, that read-only work over more information than a person can hold is where it currently earns its keep, and that everything he has had success with is a bound system with a finite rule set. Whitney names the through-line: what can be deterministic should be deterministic, and if you need an LLM, scope it tightly and have it write the deterministic thing.

It ends on mantis shrimp.

You can watch the video version of this episode as well, if you prefer that kind of thing.

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Special Guest: Michael Rishi Forrester.

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