As a SaaS author, I couldn't agree more. That's how I see my work: the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me). It's in deciding what to build and what not to build, defining the overall character and vision of the product, looking at each screen and thinking "how does this help my customer do their job".
This, unfortunately, takes time, as one has to restart many times because of ideas that turned out not to be as great as one had initially thought. And it results in software that is called "opinionated", and often does not follow what the "industry" does.
If AI can write better code and design better architecture, why can’t it make better product decisions? I don’t see how they are fundamentally different
LLMs are disembodied-the products are ultimately by and for bodies on different ends of a transaction. The loop between llm and body is primitive today. Therefore products need someone who can speak in body and translate for AI.
Also, where are the AI-operated startups?? Why has nobody’s openclaw biz gone multinational by now?
> Why has nobody’s openclaw biz gone multinational by now?
Maybe it keeps deleting and the emails and business records.
https://www.pcmag.com/news/meta-security-researchers-opencla...
Seems like it happens fairly often, considering the amount of pages like this I just found.
https://drecov.pandaoffice.com/data-recovery/how-to-fix-open...
Products that people use require the developer to imagine they are the person using this. Those of us who develop user interfaces whether visual dashboards or automations driven by voice agents call it "empathy for the user."
AI is not capable of empathy.
AI is not capable of having good taste.
So to clarify it can imagine its way through writing massive gnarly page-long regexps or imagine how a complex API works and what will happen if it makes a given call or imagine just by reading disassembled code precisely how a binary works, but it will never be able to imagine how a human might feel about a user experience?
I have an experiment to offer. Find a really, really great example of something poorly-designed, too busy or whatever other metric you want to use as your "poorly-designed" thing, then ask Claude what's wrong with it and how it should be improved?
It doesn't "imagine" at all.
This is like explaining to someone that there are no little people in the TV set, what a movie is, and then they go "yeah but sometimes they don't just talk, they also sneeze, and you can't fake sneezing, I read that in an article".
Ok and then in your thought experiment, after Claude builds its solution, what are the chances you can prompt it to be improved even more? Or has Claude reached perfection?
yeah you got it. they really can't. I'm a product manager, I'm STRUGGLING to create a harness for product work, the llms models just can't model a user's mindset very well and make very obvious bad choices that seem to be consistent (and getting worse with the new generations). That doesn't bother me, the code is getting better, but the work to talk to users and understand what needs to be built is still far from being conquered by AI.
i would expect it to make great product decisions for it's own model, and perhaps other LLMs. for humans, why would you assume it would?
AI is good at code but bad at writing. So what makes you think that its skill with code would generalize to product decisions?
AI is very good at writing, in a vacuum. The issue with AI writing isn’t quality, it’s 1) shows the prompter may not have but as much effort as one would expect from a polished writing and make amateur mistakes 2) uses cliches that are grating due to being very easy to recognized at this point. If you submit a LLM written article to a website/paper in 1990, no one would say that it is a technically poor piece of writing.
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Assuming high-quality models are around for the foreseeable future, and at this point I’m convinced that they will be. I think we’re moving into an era where breadth and hybridization of skill sets will become more valuable than pure technical depth. We’ll need more “wide T” shaped people that can exercise good UX, product, and architectural judgement and fewer “long T” shaped technical purists.
This puts large orgs at a disadvantage because they are built to coordinate work across a collection of narrowly scoped roles and keep people in their lane, so they aren’t built to hire for and leverage broad skillsets.
> fewer “long T” shaped technical purists
Then we will soon forget how our airplanes works
There’s still inherent value in people that can write code better and make architecture better than LLMs; even if you can’t.
> the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me)
The lies of this decade. Hopefully we will heal sooner than later
How is AI anywhere close to making better architecture decisions? And how it is close to even writing better code?
People keep saying this, and again and again I find it be false; a single session with Claude Opus is all it takes to debunk this, and yet people take it as given.
I have to wonder, have people drunk the vibe-coding cool-aid so much so that they are asserting the superiority of code they have never reviewed?
This is exactly what software architects and management consultants have been telling us for decades, and we laughed at them for being out of touch because they didn't grind code all day!
Well, who's laughing now!
> the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me). It's in deciding what to build and what not to build, defining the overall character and vision of the product,
Defining what to build in enough details is how you get the business logic nailed down (aka essential complexity, aka the domain in DDD). Code is just formal writing and architecture is there for maintenance (a program can be in a single file).
Sure there are accidental complexity like the intricacies of the tech, but those are actually explained very well in the docs.
> it's in deciding what to build and what not to build
Unfortunately, humanity seems like a race destined to kill itself. People are more interested in how much they hate their neighbor or feel excited about an advertisement than anything meaningful. such a society has no basis for stable governance.
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