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Domain expertise has always been the real moat

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Re: Domain expertise has always been the real moat

#91

Post by andai »

consumer451 wrote: post #71
azuanrb wrote: post #47

I recently reviewed an app built mostly with vibe coding. The owner said it was almost ready to launch and just needed a quick check. After looking through it, the database design was a mess. Some features worked, some didn’t. I explained the missing pieces and why things were breaking. Like OP said, he’s the domain expert. I used billions of tokens last month alone. The tools are getting better fast. But giving AI t…

> I used billions of tokens last month alone. I use Claude Code (Opus 4.6 at max effort) all day long, and I genuinely don't understand how this is possible. Is that usage paying off? This is very likely due to my lack of understanding, but... how?

Vibe coded a simple game (10,000 tokens of source code) with two popular coding agents. (Once each, to compare.)

One spent 200,000 tokens, to produce 10,000.

The other spent 1.9 million.

It could have been a single LLM call (10k tokens). lmao

(I note that the latter was designed by a company whose main source of revenue is token spend...)

Re: Domain expertise has always been the real moat

#92

Post by michaelchisari »

xkcd-sucks wrote: post #68
azuanrb wrote: post #47

I recently reviewed an app built mostly with vibe coding. The owner said it was almost ready to launch and just needed a quick check. After looking through it, the database design was a mess. Some features worked, some didn’t. I explained the missing pieces and why things were breaking. Like OP said, he’s the domain expert. I used billions of tokens last month alone. The tools are getting better fast. But giving AI t…

Domain expertise combined with a QA mindset could replace SWE, but consistent QA mindset is rare

I disagree. At some point of complexity, building it yourself is faster, better and (as we're finding out) cheaper. And more fun, although that varies person to person.

Wrestling with a code generator also creates a sunk cost fallacy where progress grinds to a halt but you still try and use the tools to fix the problems the tools created. Or you go in and fix things yourself, in a codebase you don't truly understand. A single developer can recreate the contextual nightmare miasma of a large corporation all by themselves.

There's also an emerging market consideration: MVP are easy to build so time to market is no longer hard to achieve. It's not a differentiator.

X was built in 3 days but is slow and riddled with bugs and security errors. There are also A, B, C, D and E which are effectively the same thing built just as fast.

Z was built over six months and is rock solid and performant.

Who wins the market share?

Re: Domain expertise has always been the real moat

#94

Post by gerdesj »

toastmaster11 wrote: post #62

How much pontificating needs to be done before people acknowledge nobody has any idea what to do with AI on an individual level? First being good developer and learning how to use AI was sufficient, next it was being able to design architecture, then it was “taste” that made all the difference and now being an expert in the domain is the only thing that matters really. Until AI is basically in a stable, predictable,…

LLMs are an additional tool to add to your arsenal. They are not omnipotent and need care, just like any other tool.

My best effort, so far, at an analogy is a modern drill driver compared to a screw driver/brace and bit/etc:

You can get some remarkable results in a very short time compared to the "old school" gear.

You can get some "amazing" anecdotes eg "I screwed down an entire floor at 16" x 1" c/c within an hour instead of an entire day and I took loads of fag breaks" (I could have used a nail gun instead in half the time but I'll never raise that floor easily in the future, and probably done at twice the cost)

I have several on prem LLMs and access to the rest and I'm pretty sure I'll be extending my analogy to ... brand, eventually.

What I do not expect to be doing is looking for a new job. A drill driver is not a carpenter/site labourer/useful without a person!

Re: Domain expertise has always been the real moat

#95

Post by TrackerFF »

I work as an analyst, and our group has roughly 20% analysts with strong technical (software engineering) skills, and the rest are more traditional analysts / domain experts.

In the past year we've seen these non-technical analysts become more productive when it comes to developing internal tools, by leveraging AI models for the dev part.

Prior to this, pretty much everything was developed in Tableau. It was the most accessible way for non-devs to build working tools.

Just the other day one analyst in our group presented a tool he had been working on, which was basically a port of a tableau report, made into a more flexible app.

Re: Domain expertise has always been the real moat

#96

Post by skulk »

esikich wrote: post #59
skulk wrote: post #50

Earlier quoted context omitted.

what does actually playing chess have to do with writing an efficient game tree search algorithm beyond a few simple principles? You challenged him to a programming contest and won, as the vastly more experienced programmer. Even though he could use AI, your domain knowledge here proved to be the deciding factor.

I had never tried to make a chess bot before though, we both started at the same spot. There are obvious things you can search for to make one. We both had the same information there. The domain was chess, and his expertise didn't help him win. If you are a chef, shouldn't you be able to make better recipes with AI? If you are a fitness trainer, better routines? Etc? Or is AI only for programmers?

I've studied how pre-NNUE stockfish worked and the principles of static position evaluation are accessible to a 500 rated player. The rest is writing an efficient search algorithm, which is purely an endeavor in computer science, not chess playing. So your expertise in programming gave you the leg up here, and predictably your opponents experience in chess doesn't help. Your point only serves to bolster TFA's argument.

Re: Domain expertise has always been the real moat

#97

Post by throw1234567891 »

toastmaster11 wrote: post #62

How much pontificating needs to be done before people acknowledge nobody has any idea what to do with AI on an individual level? First being good developer and learning how to use AI was sufficient, next it was being able to design architecture, then it was “taste” that made all the difference and now being an expert in the domain is the only thing that matters really. Until AI is basically in a stable, predictable,…

All of those things matter. One needs to be able to judge the solution in order to make a judgement if it is fine, or not. Why yes, and why no. No matter who you export the typing process to. LLMs are just tools speeding up the typing process.

Re: Domain expertise has always been the real moat

#99

Post by [deleted] »

globalnode wrote: post #56
jodacola wrote: post #39

Earlier quoted context omitted.

I won't over-generalize here, because maybe your statement is true in some cases, but I will provide a counterpoint: this is not true (in my experience) in real estate title insurance and escrow services. I've consulted for and led large teams for real estate title insurance and escrow companies for many years, and the domain expertise is so incredibly deep, nuanced, and multivariate (especially depending on jurisdic…

Agree with you there. What you are working on and the commenter below talking about surgery, they are all valid counter examples where the degree of expertise is quite extreme. But most people are not living on the edge of domain expertise. Im guessing 80% of the domain knowledge out there is up for grabs. For example: I dont have to go get a job at a security software company to figure out how security camera system…

[deleted]

Re: Domain expertise has always been the real moat

#100

Post by crab_galaxy »

andai wrote: post #91
consumer451 wrote: post #71

Earlier quoted context omitted.

> I used billions of tokens last month alone. I use Claude Code (Opus 4.6 at max effort) all day long, and I genuinely don't understand how this is possible. Is that usage paying off? This is very likely due to my lack of understanding, but... how?

Vibe coded a simple game (10,000 tokens of source code) with two popular coding agents. (Once each, to compare.) One spent 200,000 tokens, to produce 10,000. The other spent 1.9 million. It could have been a single LLM call (10k tokens). lmao (I note that the latter was designed by a company whose main source of revenue is token spend...)

What about the other 998 million tokens?
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