It's really important to define what "people who can leverage AI" means. I've found that using AI judiciously with close human supervision provides an advantage, but using the latest models with the latest harnesses can look like it's giving you a huge advantage superficially while actually costing you more time in the long run.

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theturtletalks 15 hours ago | parent | next [-]

That's hard to define, but I measure it as how quickly people reach for AI for complex, tedious tasks. Let's say you're doing market research for a car to buy. A person who doesn't use AI, might just ask ChatGPT, but many websites block searches like that now. Someone who uses CC or Codex could ask it and it will use curl to get the live data and make a HTML you can browse.

Another is someone making a workout plan or a meal plan. Coders will ask AI to make a plan and add it to their calendar using GOG Cli. It's a fundamental shift in thinking and that hasn't diffused to the mass public yet. But just like the internet, it will get to them eventually. In the mean time, those who leverage AI like that will have an advantage.

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CuriouslyC 15 hours ago | parent | prev [-]

If you're already trending towards 10x developer status in a niche area of programming, sure, AI will secretly make you less productive (in that niche) while making you feel like you're going faster, for a little while.

For everyone and every other situation, hard disagree.

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apical_dendrite 14 hours ago | parent [-]

We're currently wasting a lot of time cleaning up slop created by overusing AI. The loop is: developer uses AI to create a huge amount of code very quickly. But the developer didn't understand the underlying system very well so the specs generated by the AI contain a lot of faulty assumptions and the code was then built on those assumptions. So you have features that probably shouldn't have existed in the first place, but because they do exist people have provided feedback on them, and the developer then uses the AI to implement that feedback, but still doesn't understand the system so much of the code for the revisions is still wrong. So that individual developer saw a huge productivity increase, in the sense that he generated a vast amount of code really quickly, but the team as a whole saw a productivity decrease.

	▲	CuriouslyC 2 hours ago \| parent [-]
		Ironic plot twist, AI is just exposing your coworker's weakness. They could slow down and understand before blasting away at code, or explicitly hang back and generate tech demos/PoCs for architectural choices while building understanding, but they didn't. The only reason things were ok before was because they were handicapped to a speed slower than their ability to figure things out.