Posted by aaronbrethorst 1 day ago
With my sincere apologies to the author if I'm wrong, I'm pretty darn sure this was written by AI.
Guys, c'mon. I don't get it. It's one thing to have an AI write code for you, because code is ultimately functional. At least in the general case, the primary purpose isn't to express an idea.
Prose is different. Your writing represents what you think. You are your writing. Why would you outsource that?
I don't get it! Unless you're a (cheating) student, or you're writing marketing drivel.... what is the point? Just don't write the blog post. It's okay. Telling the robot to write the blog post doesn't accomplish anything. I don't care what a robot thinks!
I'm sorry, I'm just getting really tired of AI generated articles on Hacker News. Please, please don't outsource your own speech.
1) Problem Domain Knowledge: This is what people generally mean when they say "domain expertise". This has always been and always will be the moat with/without AI. Simply because this is what understanding and modeling a problem is all about. It abstracts the key concepts/ideas and their relationships in the problem domain and builds a coherent model. This model embodies a set of functionalities with bounded scope and clear assumptions.
2) Solution Domain Knowledge: This is the implementation domain for the above problem. The model arrived at above gives the requirements which must be mapped to concepts/ideas and their relationships in the solution domain. When our implementation domain is a computer system, this takes the form of architecture, algorithms and data structures. The probability of a good solution here is directly proportional to how good a model we were able to construct in the problem domain above.
Albert Einstein;
"The mere formulation of a problem is far more essential than its solution, which may be merely a matter of mathematical or experimental skills."
"If I had an hour to solve a problem, I'd spend fifty-five minutes thinking about the problem and five minutes thinking about solutions."
My take is much less charitable. I think a lot of senior devs are lonely and enjoy talking to chatbots all day. Saying it amplifies their productivity is a justification.
But they know nothing about the scaling, performance or maintenance of a system that will inevitably come up in production.
They also can't tell if the code created is maintainable, or unmaintainable sphagetti code.
What happens if there is a race condition, or a memory leak?
So AI can easily replace the domain knowledge of software engineers but not of evey other profession?
Coding is not engineering but I'm glad that we will finally be able to prove that definitively thanks to AI. It's going to be a bumpy ride.
Any software engineer who has built software to solve domain problems in multiple industries knows that the engineering domain knowledge and systems thinking approach is far more difficult to attain than industry-specific domain knowledge... This is why there are software consulting firms which can work across multiple domains. Understanding the problem domain is not that difficult.
The work product probably offends real software engineers in the way that a normal home cooked meal would offend a Michelin star chef. Yet, before last summer, these people never contemplated the ability to cook their own meals before. The fact that they can do this now is a very big deal.
Now these skills don't matter as much because LLM's/Cloud/Java abstract out these problems.
What makes domain expertise a different category itself that lends it to be not automated out by LLM? Example: Why can't I go to into an agri-startup and become better than anyone else by querying an LLM even when I have no domain expertise? Much the same way I beat the dev who was good at DB internals?
That engineer still is indispensable. Any organization foolish enough to replace such a person with an LLM is going to find itself in deep water when the pile of hallucinations becomes too much to endure.
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.
if you’re actually building these things, you know they and the CEOs they’re hearing from are all 6 months behind. the executive’s frantic pivot to shove “AI” down everyone’s throat didn’t pan out in one quarter and had nothing to do with the actual concept at all
that, and every industry is different. I wouldn’t listen to analysts, I’m in an industry that even Anthropic thinks wont be touched by AI (even though they can read ours and everyone else’s sessions)
all public discourse is just flat wrong, and just like every week this year, you’re just going to wake up seeing a new AI capability headline that makes you question your role in society. So play devil’s advocate all you want, the silver lining is that there’s more work to do than ever before and more of it can be tackled at once