11–20 of 33 posts
Every summer, my community pool has a cardboard regatta. Kids can use as much duct tape as they want to waterproof a cardboard box and paddle it 25 yards to the other side. Half of the vessels sink within a length or two and the kids have to swim to the edge of the pool. There’s no age limit, and last year a grown man entered a fully engineered catamaran design that beat all the others handily. The secret was using w…
They are, in every case I've seen, creating software _demos_. Those things will fall over under their own weight with 1-2 more iterations.
Someone with no code experience can say "Make snake!" and for other contrived examples and maybe even add a handful of features but very quickly they will code themselves into a corner that they can't get out of. Heck, I sometimes go 3-4 prompts deep on something with Aider then git reset back once it turns out something isn't going to work out.
If some has _fully launched_ a product using only AI to write _all_ the code (Press X to doubt) then it's either a product that will never grow past its initial feature set and/or something trivially copied (with or without AI).
What AI tools may change is the ability for "ideas people" to create a basic MVP (Of the tool itself, I don't think you are going to get an LLM to churn out a whole SaaS codebase without a developer guiding) and raise interest/funding/recruit-others. That's not the "barrier to entry" lowering, that's just a "better slide deck".
I think the super played out twitter adage has some merit to it: "it makes 10x devs 100x devs." Those who already have a high level idea of what to do and roughly how to execute it benefit the most from LLMs at the moment. This is very good for purely "technical" devs in greenfield environments. Less useful for super large interconnected codebases, but tools are getting there. It will not, however, make a bad dev a g…
The exception (in that you must learn something) is in design, though. If you ask AI to add something to your API, and do it repeatedly, you will end up with a very poorly designed API, with separate endpoints for updating separate fields in the same record, etc, which will happily work fine.
Unless you knew what to do from the start, you’re going to make a lot of tech debt.
It saves time in searching documentation but sometimes hallucinates.
The key here is that I can tell the difference and I have spent time in many codebases and read up on code design theory.
So in my case it’s a multiplier of clear understanding and somewhat sufficient subject matter expertise.
For someone without expertise, the LLM quickly becomes a multiplier of the Dunning-Kruger Effect.
I know enough to not try and write an organic chemistry paper with an LLM. But Twitter tells everyone they can do a similar thing in the area of software engineering.
For software meant to be consumed by the masses it's too unreliable for the all the boring details, but otherwise if you want something that serves a specific purpose then sure, it seems to work really well.
Otherwise though I haven't really hard of any non-technical founders leveraging it to finally get their app off the ground.
I think we'll have a new programming language(natural language with rules), I'm biased though as I've made that language :)
Going lot lower