This feels like a pretty low effort post that plays heavily to superficial reader's cognitive biases.

I work commercializing AI in some very specific use cases where it extremely valuable. Where people are being lead astray is layering generalizations: general use cases (copilots) deployed across general populations and generally not doing very well. But that's PMF stuff, not a failure of the underlying tech.

I think both sides of this debate are conflating the tech and the market. First of all, there were forms of "AI" before modern Gen AI (machine learning, NLP, computer vision, predictive algorithms, etc) that were and are very valuable for specific use cases. Not much has changed there AFAICT, so it's fair that the broader conversation about Gen AI is focused on general use cases deployed across general populations. After all, Microsoft thinks it's a copilot company, so it's fair to talk about how copilots are doing.

On the pro-AI side, people are conflating technology success with product success. Look at crypto -- the technology supports decentralization, anonymity, and use as a currency; but in the marketplace it is centralized, subject to KYC, and used for speculation instead of transactions. The potential of the tech does not always align with the way the world decides to use it.

On the other side of the aisle, people are conflating the problematic socio-economics of AI with the state of the technology. I think you're correct to call it a failure of PMF, and that's a problem worth writing articles about. It just shouldn't be so hard to talk about the success of the technology and its failure in the marketplace in the same breath.

> This feels like a pretty low effort post that plays heavily to superficial reader's cognitive biases.

I haven’t followed this author but the few times he’s come up his writings have been exactly this.