Calculus of IT - Season 3 Episode 10 - Training Our Elders (and Ourselves)

The new episode is live, and special guest Kevin Dushney joined us to ask the question nobody wants to answer: at what point do people just stop learning technology, and what the hell do we do about it?

We set out to explore whether IT should hire someone with 10 years of experience or someone who learned everything in the last two years via YouTube and GenAI, which spiraled into a debate about aptitude versus historical context, and whether we're designing systems for people we have or people we wish we had. The uncomfortable truth: we're in a race to train everyone as fast as possible, but the second we finish, everything changes and we have to start over, which means the only winning move might be to stop caring entirely and just tell retirement-age folks to click "yes" on everything (we're kidding, mostly). We also realized that nobody outside a tiny fraction of nerds gives a shit about token optimization or Opus pricing, that reviews written by AI are the corporate equivalent of outsourcing your soul, and that Nate once testified in court about a Nest cam recording of a drunk driver who tried to flee the scene with a tow truck. The breakthrough moment: maybe the elders aren't screwed - maybe they're the only ones who figured it out by refusing to engage with this madness at all. We also continued building out our IT Department of the future with our new roles including the Token Optimization Engineer (TOE), Pre-Prompt Engineer (PPE), all reporting to the omnipotent Chief Truth Officer, who reports to the Department of Generative AI Truth. Next week we're tackling Shadow AI vs Shadow IT, aka "the sequel is worse."

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—Nate, Mike & Kevin

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