I have the opposite take. Because Claude is also a domain expert at most things, and you can unit test your way to making things "just work".

If you ask me and a logistics dispatcher the task of building logistics dispatching software (whatever that is), I will get there first.

Highly agree with much of the article. IMO, this is why many engineers who learned to code in the post-2010 'new hot framework every week' era but before LLM coding took hold are able to get much better results from AI assisted coding than those on either end of that sweet spot. The domain expertise in this case is constantly having to adapt to learning the latest flavor of the week DB or JS framework and adapt existing patterns and paradigms to new ones. Agentic coding itself is, in this case, one of those new paradigms.

Knowing the caveats and pitfalls of this through years of (often-painful) experience is what, at least for me, allows me to preempt a lot of the sloppy assumptions or omissions that even the frontier models make when working on systems at scale. This means I can leverage my domain expertise on these high-level areas while delegating the grunt work that is harder to screw up to the agents. I find this enables me to work faster while avoiding the slop making its way into critical engineering decisions.

LLMs are the best domain experts, but the curse is that they know too much.

so it takes a domain expert to remove unnecessary things, similar to how stone carvers create by removing material, not adding

These kind of posts always miss the point that in a team of 10 not everyone needs to be a domain expert, and that now the same work can be delivered with a team of five or less.

Bad luck for the remaining ones.

> If you’re an experienced engineer betting on where to spend the next few years, this is the bet. The mechanical skill you sweated for, turning a clear idea into clean code, has gotten dramatically less valuable. The thing that’s still scarce is a deep, verified model of some real domain. Go get one. Pick an industry, an instrument, a regulatory regime, a physical process, and learn it the way you once learned a programming language or framework. That’s the part the agent can’t do for you, and it’s the part that’s now worth the most.

I'm not sure that even that will remain as valuable or work as a viable moat.

We live in an era of corporate consolidation and absolutely, positively having to meet the revenue target. We also have invested literal trillions of dollars into the AI technologies that made the first skill the author mentions less valuable. However, the result just isn't there. Like the author says, there's a need for domain expertise.

However, you had a bunch of investors plow that trillions of dollars into the current AI boom with the understanding that they could, at the very least, take anyone and have them create what used to take an experienced software engineer, and in far less time and cost, and they invested thinking that the corporate oligopoly would deliver this. They'll now do anything to get that money back. Anything.

If that means telling the corporate oligopoly to tell customers that they need to expect less in the way of domain expertise from the models, well, they'll do that. And since there are relatively few players (the literal meaning of oligopoly) and they all have incestuous financial relationships with each other, they have incentive to hold that line as an entire industry. Development of better tools to create better domain expertise models would take even more money, which the investors don't want to provide, and, short of soaking the public investment markets, can't even find the cash for. Thus, the customer has to lower their expectations if the investors are to not lose their asses on the AI bet.

Something has to break.

> The mechanical skill you sweated for, turning a clear idea into clean code, has gotten dramatically less valuable.

But that was never the hard part!

Come now.

After twenty plus years as a professional software developer I can name two hard problems, not more. One is related to the article, the other is not:

1. Getting that clear idea out of a stakeholder's brain. Traditionally this would be a specification but doesn't need to be that formal. Remember, remember the first panel of https://i.redd.it/i2aeyrivmjoz.jpg An LLM doesn't help here because it doesn't push back. It'll do whatever you tell it to do even if it's not what you really wanted. The software developer here operates very similarly as a translator and it always has been true a translator who speaks both sides well will be able to do the highest quality work. This is not at all new. It always has been the advice that if you know things like, say, logistics and software or any such pair then you'll be well off financially either because you can do this translation well or because you realize what's missing and can do a product for it.

2. The other problem, of course, is debugging. Since LLMs fundamentally work from a training set any debugging problem not blatantly obvious to a sr developer is hopeless for them.

This is why Google is pushing SEOs to get their clients to codify and publish their domain expertise: while it gives them a way to filter signal from noise/slop right now (supposedly helping to "improve search experiences"), it also simultaneously extracts that experience into a consumable form for later training.

They really do want to know the ins-and-outs of the HVAC service business, for example, because they hope their agents will be handling it in a few years.

the idea that llm's can't help if you're missing domain knowledge is crazy.

Perhaps the good news is that even the best spreadsheet-slinging accountant in the west would still going to need some programming experience to do their verification.

I mean, they could ask an LLM "what does this code do, and will it always X when Y", but that's just nesting the verification problem inside another verification problem.

Network effect is the moat not domain expertise. Domain expertise build on network effect (for instance the knowledge of the network) yes, but just simple domain expertise is only a training round way.