The initial, feverish enthusiasm for large language models (LLMs) is beginning to cool, and for good reason. It’s time to trade the out-of-control hype for a more pragmatic, even “boring,” approach. A recent MIT report shows that 95% of companies implementing this technology have yet to see a positive outcome. It’s understandable to feel confused.

When I get confused, I write. This is why I wrote the first part of this series, Hype is a Business Tool as the online debate had become so overheated. In part 2, The Timmy Trap, I covered why we are, surprisingly, a large part of this hype problem. We’ve allowed ourselves to be fooled, confusing an LLM’s language fluency with actual intelligence. LLMs have effectively hacked our social protocols, fooling us into believing they are more intelligent than they are.

So in this final part, I want to answer the question: why should we still care? The tech is problematic, and signs point to the bubble bursting. When we hit the “Trough of Disillusionment,” what rises from the ashes? Two lessons from my career help me navigate uncertainty: 1. technology flows downhill, and 2. we usually start on the wrong path.

– Scott Jenson