My experience with Gemini has been pretty dismal. The CLI works much better than the VS code extension and both of them have struggled with one shotting go. Single files or single functions no problem though.

I'd really like to know what type of apps you're actually one-shotting with an AI. Seriously, can you please give me some example code or something because it seems like anything past a trivial program that doesn't actually do what you specified is far beyond their capabilities.

if AI could really one-shot important, interesting apps, shouldn’t we be seeing them everywhere? where’s the surge of new apps that are so trivial to make? who’s hiding all this incredible innovation that can be so easily generated?

If AI could really accelerate or even take over the majority of work on an established codebase, we should be seeing a revolution in FOSS libraries and ecosystems. The gap has been noted many times, but so far all anyone's been able to dig up are one-off, laboriously-tended-to pull requests. No libraries or other projects with any actual downstream users.

It's taken over my mature codebase just fine. I'm not in the business of spending tokens on open source projects though.

But plenty of maintainers are in the business of spending mass amounts of time, energy, and actual money on open source projects. Some make a business out of it. Some are sponsored by their employer to spend paid work hours on FOSS projects. If LLMs could help them, some significant number would.

But if there are any instances of this, I have not seen them, and seemingly neither has anyone I've posed the question to, or any passersby.

How would you know? I don't label my changes that were made by AI.

Somebody would. Somebody would be an AI evangelist, or would become one. The FOSS ecosystem is large enough to be sure of that. We're not seeing nothing, we're just not seeing at all what the marketers and AInfluencers are prophesying.

There is a Cloudflare project that published the entire AI generated history complete with prompts. And of course in many projects the majority of PRs are opened by dependabot, it's not an LLM but it's a "bot" at least.

I agree we're not seeing open source projects be entirely automated with LLMs yet. People still have to find issues, generate PRs (even if mostly automatic), open them, respond to comments, etc. It takes time and energy.

I've made another comment in this thread about a nice tool I one-shotted. The reason I don't publish anything now is because in the UK at least, companies are not behaving will with relation to IP: many contracts specify that anything you work on that can be expected of you in the course of your duties belongs to the company, and tribunals have upheld this.

There's also a bit of a stigma about vibe coding: career wise, personally I worry that sharing some of this work will diminish how people view me as an engineer. Who'd take the risk if there might be a naysayer on some future interview panel who will see CLAUDE.md in a repo of yours and assume you're incompetent or feckless?

Plus, worries about code: being an author gives you a much higher level of control than being an author-reviewer. To err as a writer is human, to err as a reader has bigger consequences.

I did a flask application that read an AWS account's glue resources, displayed them based on category (tag of "databasename" and "driver" etc) and offered the ability to run those jobs in serial or parallel, with a combined job status page for each batch. It also used company colours because I told it to pick a colour palette from the company website. It worked first time and produced sane, safe code.

There was a second shot, which was to add caching of job names because we have a few hundred now.

(Context: I'm at a company that has only ever done data via hitting a few hand replicated on prem databases at the moment and wanted to give twitchy folks an overview tool that was easy to use and look at)