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Call me an unbeliever, but I don’t believe in the future of no code solutions. You will still have to align that button at smaller device resolutions, leave extra space so it looks nice in another language, and other requirements. Maybe it’ll enable us to use even more abstracted languages to build apps faster at most. This only works for extremely basic and common things like tic tac toe and not original works.



A huge part of the problem with LLM based no code is that the output is non-deterministic, so you can only check in the output to version control.

Imagine what happens when you have dozens of barely technical people all adding features by sketching them and clicking “make it real”. Each one is producing hundreds of lines of code. At the end of the day someone is responsible for understanding the output because since the output is non-deterministic, that’s all we have.


> Imagine what happens when you have dozens of barely technical people all adding features by sketching them and clicking “make it real”. Each one is producing hundreds of lines of code. At the end of the day someone is responsible for understanding the output because since the output is non-deterministic, that’s all we have.

Joking reply: Have you seen modern software development?

Joking-but-not-really reply: I wonder if someone could train a "bad AI code to human-maintainable code" AI.


I'd prefer a "bad human code to AI-readable code" AI.


This reminds me of what I’ve been saying to friends… we will either see al lot more layoffs of us software engineers or another big boom because the technology is moving way faster than normal humans can learn. Non tech people will just hire software engineers to do it for them.


The gpt4-turbo api is now deterministic


It isn’t. It’s “mostly deterministic,” whatever that means.

https://platform.openai.com/docs/guides/text-generation/repr...


From the link: Sometimes, determinism may be impacted due to necessary changes OpenAI makes to model configurations on our end. To help you keep track of these changes, we expose the system_fingerprint field. If this value is different, you may see different outputs due to changes we've made on our systems.


If you can so easily and cheaply generate a new version of the app/widget, why would you even use traditional version control?


Generally because although you can easily generate new versions, it is difficult to generate a new version that is different from the old version in a specific way, without also being different in 100 other ways that you didn't want.

It's like a revision control system where when you submit a commit that changes one line, which it faithfully records, it also records a change in dozens of other lines in the file. (Which leads you down the merry road of Stable Diffusion where you can "inpaint" that one line, but now it's not able to adjust the rest of things to accommodate that change because you told it not to...)


It’s like autotune.

Artisans who can sing on key will continue to make very interesting things.

But also in parallel a whole new wave of people that couldn’t or didn’t want to learn to sing on key will make entirely new genres of music and also pop for the masses with far less effort.

Even the artisans will use it sparingly to enhance and perfect and speed up some of their workflows


Unlike software, a song doesn’t need to be maintained to keep working. A song doesn’t need to grow in complexity as more people use it, and a song can’t contain subtle bugs that steal listeners’ credit cards or damage other songs.

Of course metaphors have limits, but the limits of this particular metaphor hide all of the flaws of this technology.


"Entirely new genres" of anything is unlikely from ML models trained on existing work. Someone using AI to implement an entirely new idea will be frustrated as the AI keeps gravitating toward convention.


It's more like autotune in that "literally everyone will use it all the time."


I think a lot of these demos aren't necessarily trying to push forward a no-code purist approach, but rather showing how you can get basically a live wireframe going in no time at all. I think tools like canva, figma, etc will be all over this stuff and really improve high-fidelity wireframes/demos


That was my initial gut reaction, this will be an utter nightmare to customize and integrate. Wonderful for prototyping though.


Either LLM / ai becomes perfect or we will start writing code/frameworks which makes it much easier for LLM/ai to use them.


Look at the success of ComfyUI in the Generative AI world and node-based editing in the graphics world (i.e. blender). "No code" works, but it has to be tailored towards experts who want to actual write code sometimes, not billed as making it possible for suits to write software.




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