I think it depends a lot on what you think "wrong position" means. I think skepticism only really goes wrong when it refuses to see the truth in what it's questioning long past the point where it's reasonable. I don't think we're there yet. For example, questions like "What is the long term effect on a code base" take us seeing the long term. Or there are legitimate questions about the ROI of learning and re-learn rapidly changing tools. What's worth it to you may not be in other situations.

I also think hype cycles and actual progress can have a variety of relationships. After Bubble 1.0 burst, there were years of exciting progress without a lot of hype. Maybe we'll get something similar here, as reasonable observers are already seeing the hype cycle falter. E.g.: https://www.economist.com/business/2025/05/21/welcome-to-the...

And of course, it all hinges on you being right. Which I get you are convinced of, but if you want to be thorough, you have to look at the other side of it.

Well, two things. First, I spent a long time being wrong about this; I definitely looked at the other side. Second, the thing I'm convinced of is kind of objective? Like: these things build working code that clears quality thresholds.

But none of that really matters; I'm not so much engaging on the question of whether you are sold on LLM coding (come over next weekend though for the grilling thing we're doing and make your case then!). The only thing I'm engaging on here is the distinction between the hype cycle, which is bad and will get worse over the coming years, and the utility of the tools.

Thanks! If I can make it I will. (The pinball museum project is sucking up a lot of my time as we get toward launch. You should come by!)

I think that is one interesting question that I'll want to answer before adoption on my projects, but it definitely isn't the only one.

And maybe the hype cycle will get worse and maybe it won't. Like The Economist, I'm starting to see a turn. The amount of money going into LLMs generally is unsustainable, and I think OpenAI's recent raise is a good example: round 11, $40 billion dollar goal, which they're taking in tranches. Already the largest funding round in history, and it's not the last one they'll need before they're in the black. I could easily see a trough of disillusionment coming in the next 18 months. I agree programming tools could well have a lot of innovation over the next few years, but if that happens against a backdrop of "AI" disillusionment, it'll be a lot easier to see what they're actually delivering.

So? The better these tools get, the easier they will be to get value out of. It seems not unwise to let them stabilize before investing the effort and getting the value out, especially if you’re working in one of the areas/languages where they’re still not as useful.

Learning how to use a tool once is easy, relearning how to use a tool every six months because of the rapid pace of change is a pain.

This isn't responsive to what I wrote. Letting the tools stabilize is one thing, makes perfect sense. "Waiting until the hype cycle dies" is another.

I suspect the hype cycle and the stabilization curves are relatively in-sync. While the tools are constantly changing, there's always a fresh source of hype, and a fresh variant of "oh you're just not using the right/newest/best model/agent/etc." from those on the hype train.

This is the thing. I do not agree with that, at all. We can just disagree, and that's fine, but let's be clear about what we're disagreeing about, because the whole goddam point of this piece is that nobody in this "debate" is saying the same thing. I think the hype is going to scale out practically indefinitely, because this stuff actually works spookily well. The hype will remain irrational longer than you can remain solvent.

Well, generally, that’s just not how hype works.

A thing being great doesn’t mean it’s going to generate outsized levels of hype forever. Nobody gets hyped about “The Internet” anymore, because novel use cases aren’t being discovered at a rapid clip, and it has well and throughly integrated into the general milieu of society. Same with GPS, vaccines, docker containers, Rust, etc., but I mentioned the Internet first since it’s probably on a similar level of societal shift as is AI in the maximalist version of AI hype.

Once a thing becomes widespread and standardized, it becomes just another part of the world we live in, regardless of how incredible it is. It’s only exciting to be a hype man when you’ve got the weight of broad non-adoption to rail against.

Which brings me to the point I was originally trying to make, with a more well-defined set of terms: who cares if someone waits until the tooling is more widely adopted, easy to use, and somewhat standardized prior to jumping on the bandwagon? Not everyone needs to undergo the pain of being an early adopter, and if the tools become as good as everyone says they will, they will succeed on their merits, and not due to strident hype pieces.

I think some of the frustration the AI camp is dealing with right now is because y’all are the new Rust Evangelism Strike Force, just instead of “you’re a bad software engineer if you use a memory unsafe languages,” it’s “you’re a bad software engineer if you don’t use AI.”

The tools are at the point now that ignoring them is akin to ignoring Stack Overflow posts. Basically any time you'd google for the answer to something, you might as well ask an AI assistant. It has a good chance of giving you a good answer. And given how programming works, it's usually easy to verify the information. Just like, say, you would do with a Stack Overflow post.

Who you calling y'all? I'm a developer who was skeptical about AI until about 6 months ago, and then used it, and am now here to say "this shit works". That's all. I write Go, not Rust.

People have all these feelings about AI hype, and they just have nothing at all to do with what I'm saying. How well the tools work have not much at all to do with the hype level. Usually when someone says that, they mean "the tools don't really work". Not this time.