[sussmannbaka]

So after years of being gleefully told that AI will replace all jobs an omniscient state of the art model, with heavy assistance, takes more than two weeks and thousands of dollars in tokens to do what child me did in a few days? Huh.

[rybosome]

“And, because AI never got any better or any cheaper after that point, sussmanbaka’s wry observation remained true in perpetuity, forever.”

- History, most likely

[ehnto]

We will only be able to see where the economic chips lie once all the current money games shake out. It's all a bit obfuscated at the moment.

[mchusma]

Cost per intelligence is shrinking by something like 100x per year. Even the Gemini flash release would potentially do as well for 1/5th already.

[dwaltrip]

Children are incredibly smart. All of this was fantasy 15 years ago. Comments like yours are amazing to me…

[TulliusCicero]

True AI is whatever hasn't been invented yet.

[murukesh_s]

I used to think the same until latest agents started adding perfectly fine features to a large existing react app with just basic input (in English) . Most of the jobs require levels of intelligence below that. It's just a matter of time before agents get to that.

[blauditore]

It's about the complexity of the task. Front end apps tend do be much less complex and boilerplate-y than backends, hence AI tends to work better.

[murukesh_s]

I disagree - having worked on backends most of the time, I find modern frontend much more complex (and difficult to test) than pure backend. When I say modern frontend - its mostly React, state management like Redux, Zustand, Router framework like React Router, a CSS framework like Tailwind and component framework like Shadcn. Not to mention different versions of React, different ways of managing state, animation/transitions etc. And on top of that the ever increasing complex quirks in the codebase still needed to be compatible with all the modern browsers and device sizes/orientation out there.

[Jensson]

> When I say modern frontend - its mostly React, state management like Redux, Zustand, Router framework like React Router, a CSS framework like Tailwind and component framework like Shadcn

AI is the best at adding standard things into standard boilerplate situations, all those frameworks just makes it easier for AI. They also make it easier for humans once you know them and have seen examples, that is why they exist, once you know those frontend is not hard.

[blauditore]

Actual complexity depends is not imposed by the framework, but by the application itself, and the amount of front-end logic tends to be lower. Yes, there is more complexity in the setup of front end code (now there are dependencies and build pipelines), but ultimately they should simplofy things especially for slighly more complex websites.

Testing is one of the things that's generally tedious in front end applications, but not inherently complex. There may be lots of config needed (e.g. for setting up and controlling a headless browser), and long turnarounds because tests are slow and shaky. But they are also boilerplatey.

[rafaelmn]

That's just a farmiliarity thing. I've worked on project doing full web FE, mobile and BE.

It's hard to generalize but modern frontend is very good at isolating you from dealing with complex state machine states and you're dealing with single user/limited concurrency. It's usually easy to find all references/usecases for something.

Most modern backend is building consistent distributed state machines, you need to cover all the edge cases, deal with concurrency, different clients/contracts etc. I would say getting BE right (beyond simple CRUD) is going to be hard for LLM simply because the context is usually wider and hard to compress/isolate.

[murukesh_s]

>Most modern backend is building consistent distributed state machines, you need to cover all the edge cases, deal with concurrency, different clients/contracts etc. I would say getting BE right (beyond simple CRUD) is going to be hard for LLM simply because the context is usually wider and hard to compress/isolate.

Seeing the kind of complexity that agents (not standalone llm) are able to navigate - I can only start to believe - just a matter of time it can do all kinds of programming, including state of the art backend programming - even writing a database on its own - good thing with backend is its easily testable and if there is documentation that a developer can read and comprehend - an llm/agent would be able to do that - not very far from today.

[etse]

Isn’t frontend more complex? If my task starts with a Figma UI design, how well does a code agent do at generating working code that looks right, and iterate on it (presuming some browser MCP)? Some automated tests seem enough for an genetic loop on backend.

[murukesh_s]

>Isn’t frontend more complex? If my task starts with a Figma UI design, how well does a code agent do at generating working code that looks right, and iterate on it (presuming some browser MCP)? Some automated tests seem enough for an genetic loop on backend.

Haven't tried a Figma design, but i built an internal tool entirely via instructions to agent. The kind of work I could easily quote 3 weeks previously.

[ehnto]

Training data is quite readily available as well, and the online education for React is immense in volume. Where enterprise backend software tends to be closed source and unavailable, and there's much less good advice online for how to build with say Java or .NET

That said, I still get surprising results from time to time, it just takes a lot more curation and handholding.

[ribosometronome]

Or perhaps the sort of things it's been trained on? There's not really a huge corpus of material re: beating Pokemon in the manner it has to play Pokemon, especially compared to the mountains of code these models have access to.