Custom AI Code Controversy
This episode explores the pitfalls and risks of developing custom AI code, questioning whether bespoke solutions are worth the trouble. The hosts discuss the hidden challenges, security concerns, and the case for using established AI frameworks.
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Chapter 1
Why Custom AI Code Raises Red Flags
Timothy Chester
At a recent gathering of CIOs, a colleague shared how their team was using GenAI. To move fast and respond to emerging customer requests, they’d established a new group within IT, separate from their ERP and data teams, focused entirely on delivering AI-generated solutions.
Timothy Chester
This team utilized GenAI models to generate code, creating custom software that delivered ERP automations, reports, and analytical capabilities. The strategy, my colleague explained, allowed them to create highly tailored software quickly, without relying on vendor-delivered tools. It was efficient, cost-conscious, and—in their view—an ingenious use of code-writing that GenAI now makes possible.
Timothy Chester
From my facial expression, though, my friend could tell I had reservations. I’ve seen this movie before, and I know where it all leads—and it’s nowhere good.
Timothy Chester
In today’s Dispatch, we explore why the rush to build—even with the best of intentions—often takes us back to a world we thought we’d outgrown. A world where speed and precision come at the cost of resilience, and where every new line of custom code quietly ties another strand into Andy Kyte’s Gordian knot.