alt Hacker NewsI agree with the author that -- right now -- we're still in the part of the AI adoption / product development curve that it's an extreme force multiplier.
I like to think of it as a normal distribution, the further away a programmer is to the right of the mean, the more their benefit. It's almost like it's their standard deviation squared (σ²). So someone like Matt Perry (as OP mentioned), who is a >99.99% programmer for argument's sake and is therefore four standard deviations away from the mean... Matt gets a (4×4) 16x multiplying effect on their productivity.
Someone who is a slightly above average programmer might see a 2 or 3x boost on their productivity, which is huge(!) and might also make them fear for their job. Which tracks with the level of moral panic we are seeing and experiencing. This math kinda still holds up for "bad programmers" too (i.e. left of the mean), as in they still see a boost to their productivity (negative squared is a positive number)... but there's something iffy about their results. The technical debt is unmaintainable and because they don't _understand_ the systems that they're operating in, they end up in the "3 hour" prompt loops that the OP refers to.
> Similarly, if Matt Perry handed me the keys to the Motion repository and told me to take over, I wouldn’t have the same results even though I have access to the same set of LLM tools.
The question is -- how long is this multiplier going to exist for? Some people would wager "for the foreseeable long-term future"; some people think it will widen further; and some people think it will diminish or god forbid even collapse. It feels like most arguments at the moment (like this article's) are that the humans who "know what they are doing" will be able to baton the hatches and avoid being usurped by ever-capable models. I saw it in a café yesterday: someone was using a coding agent to build a marketing website for their project, getting more and more frustrated by not getting the outcome they wanted. Their friend typed a couple of sentences on their keyboard and got a "Dude! How did you do that? That was sick!" a minute or so later. "I used to build websites" the friend said. -- The friend 'knew what they were doing'.
How much longer is knowing what you're doing going to be a moat?
Replies
> How much longer is knowing what you're doing going to be a moat?
To me, I don't see how this will ever not be an advantage. All software requires constraints. Some of those constraints might be objective (scale, performance, etc.) but a lot of them are subjective and require active decision making (architecture, UI, readability).
So if there was only one way to do something or only one desired output, then yes I think models would surpass humans. But like art, I don't think there is a objective truth to software and because of that, humans get the opportunity to play an important role.
Now whether that is valued from a business/industry perspective is a question that I think we all know the answer to unfortunately.
100% agree with this. I think takes like OP's would be much more interesting if they staked out a position in the future. I think it's pretty uncontroversial to say that someone with a great deal of technical expertise is going to be a hugely more effective LLM user today.
The question that really matters is whether that will continue to be the case. My guess is that technical expertise matters less over time, and the ability to specify the desired outcome is eventually the only thing that becomes important. But I could be wrong! The direction this all goes is pretty fuzzy in my mind.
Cafés are no proper workspace though.
They're full of noise and distractions. They offer no ergonomics, no proper screens, no nothing.
Anything that happens or doesn't happen there is mostly irrelevant to relevant software at large.
> How much longer is knowing what you're doing going to be a moat?
For a looooonnnnngggg time, unless there's massive progress in AI research.
Fundamentally, next token prediction is limited. Granted, I'm pretty amazed at how well it's done, but if you can't activate the right parts of the models (with your prompts), then you're not going to get good results.
And to be fair, for lots of things this doesn't matter. Steve in Finance or Mindy in Marketing can create dashboards that actually help them, and the code quality mostly doesn't matter.
For stuff that needs to be shipped, monitored and maintained you still need to know what you're doing.