I think the real challenge is not whether AI will “replace” people, but how we preserve the spaces where skills are actually practiced and refined. Entry-level jobs, internships, and junior projects have always been more about learning curves than efficiency. If AI shortcuts those too aggressively, we risk cutting off the very ladder that produces the next generation of capable engineers and creators.

Maybe the question isn’t “Will AI take jobs?” but “How do we redesign pathways so humans still get the training ground they need—while AI handles the repetitive load?”

If we can create an AGI, then an an AGI can likely create more AGIs, and at that point you're trying to sell people things they can just have for free/traditional money and power are worthless now. Thus, an AGI will not be built as a commercial solution.

There are plenty of companies making money. We are using several “AI powered” job aids that are leading to productivity gains and eliminating technical debt. We are licensing the product via subscription. Money is being made by the companies selling the products.

Example

https://specinnovations.com/blog/ai-tools-to-support-require...

The part that stuck with me most: "Success will mean defeat." That nails the challenge of investing in the current AI landscape

Never say never, but I certainly don’t see LLMs as the basis for industrial fortunes. Maybe future forms of “AI” could be that.

This is a great perspective.

If anything, I'd think that crypto in 2010 had all the hallmarks of a new wave as described. The concept was open to anyone who wanted to tinker with it. It had to be sold to skeptical consumers by wildcat startups. It certainly had the potential to upend the financial industry, but no incumbent would touch it. Yet it did end up more or less being sucked into the gravity well of the incumbents, although in the case of crypto we very much need to consider governments which control the money supply to be the heavyweights, even more so than banks and lenders.

Maybe I'm pessimistic, but I'm not sure any new innovation now can escape the gravitational nexus of the duopoly of government and incumbent tech, in a way that would lead to the kind of wild growth and experimentation we had with microprocessors in the 70s.

We had some guy named Satoshi write a paper that basically handed the keys to anyone who wanted to experiment - and 17 years later, after a significant bubble, that wave has done very little to change the status quo.

I suppose if someone released a DIY genome editor or protein folding was solved or, like, a working Mr. Fusion device showed up on Kickstarter, or a "feed"/"seed" a la the Diamond Age made it possible to turn dirt into anything you wanted, or a FTL drive came out of someone's garage or something... yeah. That would seriously upset the incumbents. But even with sci-fi stuff like that, what's the moat once you make your findings public anymore? This article suggests that the only serious moat has ever been that large companies are slowed down by inertia and take some time to spin up once their internal cultures go from deriding something to deciding it's essential.

How do we know if we have stalled to the point that no one will come along and be the next Amazon or Google, until 50 years from now we see that no one did?

Maybe the basis of concentration of power and wealth more than anything else

Seems like the thing to do to get rich would be to participate in services that it will take a while for AI to be able to do: nursing, plumbing, electrician, carpentry (i.e., Baumol). Also energy infrastructure.

This article seems to have scoped AI as LLMs and totally missed the revolutionary application that is self driving cars. There will be a lot more applications outside of chat assistants.

AGI is where the real money is. Gen AI is okay but mostly benefits the consumer.

Gen AI is not nearly powerful enough to justify current investments. A lot of money is going to go up in smoke.