Comment by dnw

I'd note a couple of things:

Not to nitpick but if we are going to discuss the impact of AI, then I'd argue "AI commoditizes anything you can specify." is not broad enough. My intuition is "AI commoditizes anything you can _evaluate/assess_." For software automation we need reasonably accurate specifications as input and we can more or less predict the output. We spend a lot of time managing the ambiguity on the input. With AI that is flipped.

In AI engineering you can move the ambiguity from input to the output. For problems where there is a clear and cheaper way of evaluating the output the trade-off of moving the ambiguity is worth it. Sometimes we have to reframe the problem as an optimization problem to make it work but same trade-off.

On the business model front: [I am not talking specifically about Tailwind here.] AI is simply amplifying systemic problems most businesses just didn't acknowledge for a while. SEO died the day Google decided to show answer snippets a decade ago. Google as a reliable channel died the day Google started Local Services Advertisement. Businesses that relied on those channels were already bleeding slowly; AI just made it sudden.

On efficiency front, most enterprises could have been so much more efficient if they could actually build internal products to manage their own organizational complexity. They just could not because money was cheap so ROI wasn't quite there and even if ROI was there most of them didn't know how to build a product for themselves. Just saying "AI first" is making ROI work, for now, so everyone is saying AI efficiency. My litmus test is fairly naive: if you are growing and you found AI efficiency then that's great (e.g. FB) but if you're not growing and only thing AI could do for you is "efficiency" then there is a fundamental problem no AI can fix.