I feel like this aspect has been discussed on HN many times. The thing that resonates with me strongly is that there’s rarely a clear or fixed set of requirements to begin with - at least from my work experiences. Then, domain expertise helps with being able to proactively call out when they are missing and support in defining them. Still I am of the view that with enough context AI could also replace the best engineers with the best domain expertise.
That's not true at all, sure CRUD might not have been that difficult, but absolutely there is extremely complicated software out there that is really difficult to write in a performant and correct manner.
Yes. Audio, video encoders, decoders etc, 3D modeling, rendering etc.
That too is "domain" even it feels like it is NOT. Domain of signal processing, Euclidian spaces, information theory and what not. Thar too is all "domain" and that "domain" part is difficult to write.
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.
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.
I’ve been an engineer for a while now, where we have a mix of EE, ME, SysE, SWE, and the programmatic folks, lots of software/hardware integration at pretty “low” levels for each discipline, really fun.
One of the things I say is when I’m on my soapbox is: we are all engineers. We have different tools in our toolbox to solve problems. We get paid to solve problems, not (for example) write software. Software is just a tool.
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 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.
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.
Once someone taught me "you can do xyz reading a book, but you cant do surgery by reading a book". Now replace the book with LLM. This is what "domain expertise" look like for some domain.
“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 was located. 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.
Have you considered becoming a residential electrician? Good job, pays well, lots of problem solving, and it won’t be replaced with an AI. I’m serious!
I’d go with physical therapy! Or something else that’s closer to humans and health. “Problem solving” becomes that much more tangible and directly meaningful to another person
chatgpt can already do a big part of this job since most of the "therapy" needs to be self directed. So consult the AI and have it tell you what you need to do.
I feel like this aspect has been discussed on HN many times. The thing that resonates with me strongly is that there’s rarely a clear or fixed set of requirements to begin with - at least from my work experiences. Then, domain expertise helps with being able to proactively call out when they are missing and support in defining them. Still I am of the view that with enough context AI could also replace the best engineers with the best domain expertise.
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.
> Writing software has never been difficult.
That's not true at all, sure CRUD might not have been that difficult, but absolutely there is extremely complicated software out there that is really difficult to write in a performant and correct manner.
Yes. Audio, video encoders, decoders etc, 3D modeling, rendering etc.
That too is "domain" even it feels like it is NOT. Domain of signal processing, Euclidian spaces, information theory and what not. Thar too is all "domain" and that "domain" part is difficult to write.
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
Encyclopedic knowledge does not equal expertise, much like raw intellect does not equal wisdom.
Knowing "too much" and not knowing what belongs to the core and what is a secondary detail is exactly a lack of domain expertise.
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.
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.
I’ve been an engineer for a while now, where we have a mix of EE, ME, SysE, SWE, and the programmatic folks, lots of software/hardware integration at pretty “low” levels for each discipline, really fun.
One of the things I say is when I’m on my soapbox is: we are all engineers. We have different tools in our toolbox to solve problems. We get paid to solve problems, not (for example) write software. Software is just a tool.
I bet there were textile workers who would have written articles like this if the internet had existed back then.
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.
That “likely” is doing a lot of work, especially in mission critical software.
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.
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.
Once someone taught me "you can do xyz reading a book, but you cant do surgery by reading a book". Now replace the book with LLM. This is what "domain expertise" look like for some domain.
You might /think/ you've become a domain expert, but you haven't.
This guy has clearly never asked an LLM whether New York City is entirely south of the state of Oregon.
> become a domain expert in a short amount of time
how does that work exactly?
“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 was located. 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.
Have you considered becoming a residential electrician? Good job, pays well, lots of problem solving, and it won’t be replaced with an AI. I’m serious!
I’d go with physical therapy! Or something else that’s closer to humans and health. “Problem solving” becomes that much more tangible and directly meaningful to another person
chatgpt can already do a big part of this job since most of the "therapy" needs to be self directed. So consult the AI and have it tell you what you need to do.
I have. Or general well rounded construction worker who knows how to build all aspects of a house. A full stack builder.
Have you?
DIY’er exclusively but if my thesis is wrong it sounds like an interesting backup.