Better late than never.

Some of us have been taking this approach for literally years now.

Many startups can now work in ways that were only fathomable in Big Tech before. Do you want a build system like Bazel for your monorepo? You can have it. Do you want to rewrite your app in a faster language? Sure, go ahead. Do you want to have native apps in all platforms? Yes, please.

Though, I am an "Ultra Noob," light years behind most people here, I am actually in the process of making a couple or four Vibe Coded apps, starting with a Markdown editor, a couple of training suites that target the areas where my knowledge is weakest, which turns out to be every area apparently. I am also working on an app for Linux that Microsoft has had for a few years that Ubuntu users--the noobs--are in desperate need of, and should have, but sadly has been missing from most Linux distros, in my view. Of course, this is using free tier AIs and not locally hosted agents. None-of these apps are rust-based a the moment, but I try to instruct the AI to make it as fast as possible for the given platform.

It's really challenging to do this, especially creating the AppImages locally so I can test them when the apps do not not work correctly, having to alter the files manually. Yup, I'm not an avid GitHub pusher, just more of a cloner.

I'm having to use multiple free-tier AI agents to help me do this and record the steps and commands I use in markdown files so I don't forget them the next time I try to improve the app.

If I am successful in making these apps work without hosing my system, I'm hopeful that this will become a game changer, for those Noobs that using Ubuntu, or myself at least.

The hardest part is when the AI does not follow my instructions such as requests to generate markdown README.md files with instructions on how to create AppImages, Flatpak, deb files, etc. Have to ask other AIs for help with that while dealing with the frustrating Free-tier cutoff periods :(

I sympathize with the sentiment in this post but it’s a losing proposition.

In the past building something fast, complicated etc required quite a lot of skill and some time. Now you need far lesser skill and lesser time. This just means what you are building is commodified, and has far lesser value that it had before. Take typescript, if it becomes clear that LLMs can speed it up with no regressions and a week or so of prompting, then most likely every company will have their own typescript compiler and no one will use your new one that you built with your 200$ plan.

A lot of tasks are much easier now and also monetarily they’re not worth the 200$ or so tokens of the ChatGPT plan you’re using, because anybody (or at least a number of people) can do it now.

Rather than being more ambitious with AI, you will be far better off finding a unique combination of skills and services that does not compete / AI can’t provide. Only the big labs can be really ambitious with AI.

amazing

Sounds like marketing for AI to me.

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But now that AI writes everything, should not the question be why AI does not yield perfect software?

Even he’s not ambitious enough. Set the boundaries according to the hardware – billions of ops a second . Your rewrite should run at least 1000x faster than the handwritten version , with 1/10 resources.

I noticed my cloud images had 150mb ram wasted by vendor slop. AI rewrote the functionality into a few mb .

We’ve had slop long before AI . What you produce now is up to you

Something I've been thinking about lately is how doing anything well is an unknown factor more difficult than you originally think. Your initial estimate of how hard something is to do is usually terribly wrong. Once you think that you're 20% into a project, you realize that you're only actually 5% into the project. Then later, when you reach what you think is finally 20% again, you realize that, once again, you're only 5% into the project! This repeated discovery of "more to do" really beats people down and discourages them from doing ambitious things.

(See also Hofstadter's law: It always takes longer than you expect, even when you take into account Hofstadter's law.)