Like we said before, LLMs are tools. They have some impressive functionality and can be highly useful if you understand them and know the job that needs to be done.
Cory Doctorow has done a fine job over the years explaining this distinction, as well as the fundamental misalignment of incentives between what LLMs are good for and what the AI industry needs people to see them as in order to keep the bubble inflated.
The linked article is highly recommended (and is considerably more nuanced than the title would suggest). The other question Suresh implicitly raises is: "How can you reconcile the failure of AI in the enterprise with the individual claims of skilled technologists who insist that AI is helping them do great work?" The answer is that these AI users are "
[centaurs]" – experienced workers who are assisted by automation on terms that they set for themselves.Thanks to their skill and experience, these workers possess
discernment, the ability to tell good code from bad, and (more importantly) goodusesof code-generation tools from bad. They demonstrate the adage that worker-driven automation improves quality, while capital-driven automation improvesthroughput.An automation technique that requires close supervision by skilled and experienced workers isn't going to be a raw productivity powerhouse. You don't "100x" your code this way, at least, not in the sense of firing 99 of your coders and having the remaining programmer pick up all their work. Rather, an automation tool that requires the continuous and conscientious exercise of discernment will let individual practitioners improve their work in extremely satisfying and useful ways. It's a way to spend more on operations in order to produce better outputs. It's
nota way to cut your workforce, realise a gigantic saving, and still produce comparable goods and services at a far lower cost.That is why some individual coders report such delight with their AI tools. They engage with those tools on their own terms, to improve their work in the ways that they, in their expert judgment, consider beneficial. No one ranks them on a "token-maximisation" scoreboard. No one tells them they can't do a project if it isn't "sufficiently AI". When they set out to do a project, no one makes them prove that it couldn't be "done by AI".