One little detail. The models are already pre trained on similar system implementations. Likely whatever you are building has been built in some form or shape in the past and the ambiguity is resolved by someone in the training set.

I bet there were textile workers who would have written articles like this if the internet had existed back then.

Good post! Also, in my opinion, domain expertise is actually more interesting than pure coding ability. Coding, for me, has always been a means to an end. I'm equally happy with a spreadsheet if it solves my problem, and in fact I hate most apps.

“The hard part of writing software has never been the writing.”

I’m tired of these endless articles on HN about software engineers trying to reinvent their identity while trying not to lose touch with reality.

One way of dealing with LLMs is to deny the skill level of LLMs. Claim they can’t code as well as you. This excuse works to a certain extent but it also fails because not only are their multitudes of cases where the LLM IS intrinsically worse than me… but there are multitudes of cases where it is better. So this excuse cannot be universally true.

The other way is to claim software engineering was never the hard part of engineering and that other things were harder and that was always where your primary skill lied. This excuse is also idiotic. First, Software engineering is hard. It is genuinely not something that anyone can pick up very quickly. Second, all those other “skills” like “domain expertise” are STILL targets for the LLM. It’s not like the LLM exclusively is only good at software.

Just face the goddamn truth. AI is on a trajectory to dominate. That’s what all the trendlines say. It’s not currently dominating, but it’s close, and the trajectory points to an endgame where it is fundamentally better. The trendline could be wrong but the trendline is the best quantitative predictor we have and it’s been trumping all the half baked theories on HN where people were claiming self driving cars would never happen and AI could never code. HN was historically wrong… the trendlines and the VCs who made those bets have been right. So who’s the bigger idiot? Those VCs creating the AI bubble or HNers who have been continuously wrong about everything? (Minus crypto, HNers were right about crypto).

If the trendline is true our skills as engineers not just the software part is on track to being dominated by an artificial intelligence. The tools trivialize your skills until all the moats are gone. Not only that… AI is becoming better at art. Poetry, writing, paintings, music… AI shows us how trivially reproduceable all of it is. That is the truth. We aren’t not unique and all the meaning behind being human is just an algorithm. It’s all reproducible. Even your self delusional attempt to deny and delude yourself away from these truths is predictable. I can see someone formulating a retort right now.

This article is wrong. LLM's encode all the domain knowledge you could possibly want. As a software dev I can query an LLM, become a domain expert in a short amount of time, and then code up a solution. If people think their niche is safe from automation, think again. Even the people who think theyre the masterminds at the top.

Edit: Yes "expert" was too strong a word. Proficient would be better. A lot of the barrier to entry in a field is just not understanding the domain.

Agree on this one. As a Civil engineer, I can smell which software ( or some part of) was developed by computer engineers without much understating of the "domain". The worst offenders are software needing multi-domain expertise in the first place. Crude Ex. Payroll (Finance) and Leaves (HR) are 2 seperate domain, and they need to account for each other.

This is such a sane take. It is THE reality we have been always ignoring.

Writing software has never been difficult. It is the domain that has been the issue. Always.

I disagree because we're buying up companies and training models, creating skills and agentic workflows on individual domain expert's 30 years of notes and prior projects

The only moat is that there is so much more work for domain experts since they and many of the bureaucratic processes in between aren't the bottleneck anymore

I think it's important to be clear on what's really happening. Companies were accomplishing 5% of their annual plans, and now they're taking a realistic swing at all 100% to likely reach 20-25%. It's a crazy amount of work, for the same specialists and more human workers.

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