551–560 of 615 posts
Earlier quoted context omitted.
> I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. That's great, but professional programmers are afraid of the future maintenance burden.
"maintenance burden" is introduced when a non-original programmer starts contributing to a repo, regardless of how objectively maintainable the code is.
About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with L…
I'm surprised at the description that it's "useless" as a programming / design partner. Even if it doesn't make "elegant" code (whatever that means), it's the difference between an app existing at all, or not. I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. I wouldn't describe myself as a programmer, and didn't plan to ever build an app, mostly because in…
> There’s a flipside to this too: a lot of better informed people have sworn off LLMs entirely because they can’t see how anyone could benefit from a tool with so many flaws. The key skill in getting the most out of LLMs is learning to work with tech that is both inherently unreliable and incredibly powerful at the same time. This is a decidedly non-obvious skill to acquire! I wish the author qualified this more. How…
The best prompts though are always written in a separate text file for me and pasted in. Follow up questions are never as good as a detailed initial prompt.
I would imagine well formulated questions to solve the problem at hand is a skill but beyond that I don't think there is anything special about how to ask LLMs a question.
In areas the LLM is rather useless, no amount of variation in prompting can solve that problem IMO. Just like if the tasks is something the LLM is good at, the prompt can be pretty sloppy and seem like magic with how it can understand what you want.
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Off topic, but I'm a bit confused. Your iOS apps as listed on your website are CarPrep and Brocly, neither of which appear to have notable review activity or buzz in the media. If the app you're referring to is one of these, the more interesting question (to me) is: how on Earth are you generating $10,200 MRR from it? Or is there another app that I'm missing? (In my experience as an app developer, getting any tractio…
Those are just my silly personal projects, not businesses. The business I mentioned above is in the recruiting agency space, B2B SaaS. The app itself is not the thing being purchased per se, the point was it was built using LLMs. $10K MRR isn't much; we're still validating PMF. We're carefully selecting paid customers at this point, not open for wide release, hence my vagueness. Just wanted to illustrate that buildin…
> There’s a flipside to this too: a lot of better informed people have sworn off LLMs entirely because they can’t see how anyone could benefit from a tool with so many flaws. The key skill in getting the most out of LLMs is learning to work with tech that is both inherently unreliable and incredibly powerful at the same time. This is a decidedly non-obvious skill to acquire! I wish the author qualified this more. How…
I think most tech folks struggle with it because they treat LLMs as computer programs, and their experience is that SW should be extremely reliable - imagine using a calculator that was wrong 5% of the time - no one would accept that! Instead, think of an LLM as the equivalent of giving a human a menial task. You know that they're not 100% reliable, and so you give them only tasks that you can quickly verify and corr…
The problem is: for the tasks that I can give the LLM (or human) that I can easily verify and correct, the LLM fails with the majority of them, for example
- programming tasks of my area of expertise (which is more "mathematical" than what is common in SV startups), where I know how a high-level solution has to look like, and where I can ask the LLM to explain the gory details to me. Yes, these gory details are subtle (which is why the task can be menial), but the code has to be right. I can verify this, and the code is not correct.
- getting literature references about more obscure scientific (in particular mathematical) topics. I can easily check whether these literature references (or summaries of these references) are hallucinations - they typically are.
Earlier quoted context omitted.
I'm surprised at the description that it's "useless" as a programming / design partner. Even if it doesn't make "elegant" code (whatever that means), it's the difference between an app existing at all, or not. I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. I wouldn't describe myself as a programmer, and didn't plan to ever build an app, mostly because in…
> I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. My experience is that people who claim they build worthwhile software "exclusively" using LLMs are lying. I don't know you and I don't know if you are lying, but I would be willing to bet my paycheck you are.
The relationship also builds a natural moat.
Earlier quoted context omitted.
> I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. My experience is that people who claim they build worthwhile software "exclusively" using LLMs are lying. I don't know you and I don't know if you are lying, but I would be willing to bet my paycheck you are.
They are also usually selling another AI-wrapper. I don't know the parent poster either but if your LLM product is generating $10k/month, your moat is really weak and you'll probably shut the f* up because your only moat is obscurity. Why risk that?
It sounds like they are doing productized consulting, so the relationship is the moat.
Earlier quoted context omitted.
I think most tech folks struggle with it because they treat LLMs as computer programs, and their experience is that SW should be extremely reliable - imagine using a calculator that was wrong 5% of the time - no one would accept that! Instead, think of an LLM as the equivalent of giving a human a menial task. You know that they're not 100% reliable, and so you give them only tasks that you can quickly verify and corr…
> Instead, think of an LLM as the equivalent of giving a human a menial task. You know that they're not 100% reliable, and so you give them only tasks that you can quickly verify and correct. The problem is: for the tasks that I can give the LLM (or human) that I can easily verify and correct, the LLM fails with the majority of them, for example - programming tasks of my area of expertise (which is more "mathematical…
> There’s a flipside to this too: a lot of better informed people have sworn off LLMs entirely because they can’t see how anyone could benefit from a tool with so many flaws. The key skill in getting the most out of LLMs is learning to work with tech that is both inherently unreliable and incredibly powerful at the same time. This is a decidedly non-obvious skill to acquire! I wish the author qualified this more. How…
My experience is that for certain tasks LLMs are great, for certain tasks LLMS are basically useless. The best prompts though are always written in a separate text file for me and pasted in. Follow up questions are never as good as a detailed initial prompt. I would imagine well formulated questions to solve the problem at hand is a skill but beyond that I don't think there is anything special about how to ask LLMs a…
About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with L…