AI For Luddites

AI arrived whether you asked for it or not. AI For Luddites is a plain-English podcast for the skeptical, the resistant, and the merely exhausted \u2014 no hype, no jargon, and no promises that everything is about to change forever. Each episode puts one piece of artificial intelligence on the workbench and takes it apart: what it actually does, what it actually costs, and whether it has earned a place in your work. The original Luddites were not fools who feared machines \u2014 they were skilled craftspeople who asked who the machines were really for. Good question. Still is. From 210 Digital Marketing in Eagle, Idaho.

AI For Luddites is a general podcast hosted by Unknown Host, with 0 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Unknown Host hosts AI For Luddites, a general show with 0 episodes published.

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  Episode #2

  Local Models, 950 Million Tokens, and Why Free AI Isn't Free

  Sep 7, 202643 minS1

  In episode two of AI for Luddites, Cody, Gonzalo, and John Wee are joined by special guest Eugene, with Jesus sitting this one out. John explains why small businesses and students are turning to local open-source models to keep their data at home, and what that costs in hardware. Cody breaks down a day that burned 950 million tokens on Fable 5.1 and why the return on that API bill was still enormous. The group weighs AI as a force multiplier against the disappearing entry-level developer job, argues that soft skills are the hard ones to teach, and lands on a rule...

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  Episode #1

  AI Reality Check: Enterprise Tech, Layoffs, and Token Optimization

  Aug 27, 202636 minS1

  In the inaugural episode of AI for Luddites, hosts Cody, Gonzalo, and Jesus hit the rock climbing gym to discuss the practical realities of artificial intelligence in the enterprise. They cut through the industry hype to explore how companies are actually using AI, the truth behind tech layoffs, and the process of building semantic data layers. The conversation also covers open-source models, agentic programming, and strategies for token optimization to save costs.

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