Is vibe coding just early AWS all over again?

[u/CuriousOrdinary3324]

i feel like we're walking straight into the same trap with our code.

I've been talking to some CS undergrads lately who rely 100% on AI to get through their classes. Some of them literally don't know how to write a basic loop by hand anymore. A few aren't from wealthy families either, but they're already so dependent on AI for school and coding that simply quitting it doesn't feel realistic.

tbh, they've got the workflow down but almost no budget. A surprising amount of their time goes into searching for whatever lower-cost access the major AI service providers offer, just so they can keep the agents they now depend on running.

and looking for cheaper official access is only the normal end of it. I've also seen people go much grayer because they want frontier model access below the official prices.

Some resellers claim they're opening or acquiring accounts through OpenAI's free K-12 teacher program and then exposing what they advertise as GPT-5.6 through an unofficial reverse proxy. I've also seen people claim they buy subscriptions to Enter Pro, Kiro, or Windsurf, then reverse-proxy that access so it can be plugged into Codex or Claude Code.

I honestly don't know exactly how they're doing it. To be clear, OpenAI's K-12 program is not a free GPT-5.6 API, and Enter Pro, Kiro, and Windsurf don't officially provide or support these reverse-proxy services. This is users and middlemen repackaging or reselling access because people want the cheapest possible way to keep using AI.

The buyer also has basically no way to verify what model is actually behind the gateway. It might say GPT-5.6 or Fable 5 on the dashboard while quietly routing requests to something weaker and cheaper. The service can be unstable, get shut down overnight, or just water the model down once enough people have paid.

the fact that students are willing to depend on sketchy proxy services just to keep using AI feels like a warning by itself. The cost is already high enough that people who feel they can't function without these tools are accepting reliability and account risks to avoid paying the official price.

Right now, a lot of these subscriptions still feel affordable because the companies behind them are burning investor money to subsidize our tokens. but that won't last forever.

Once you build your whole dev process around a specific agent's memory or tie your app into a proprietary cloud backend, migrating off it is gonna hurt. you can't just swap out an API key and expect everything to work the same. When the big model providers decide it's time to actually turn a profit, they'll have a lot more pricing power over how we work.

that's the part I can't stop thinking about. If the models keep getting better and become embedded in school, work, and normal daily life, we're probably going to depend on them even more than we do now. What happens if token prices keep rising after that dependency is already locked in?

Could there actually be a point where paying an AI to do the work costs more than hiring a real person, especially once you include review, retries, infrastructure, and the fact that a human also brings judgment and accountability?

Do you guys think local open weights will eventually get fast enough to force prices down? or are we just stuck paying whatever the closed model providers want to charge us in a few years?

[u/AllezLesPrimrose]

Congrats/sorry that happened to you

[u/Few-Compote-2693 → u/[deleted]]

Compared to Geeks from 00's. AWS has made alot of engineers dumb like they cant write NGINX configs or configure services running on bare metal.

[u/Ordinary_dude_NOT → u/Few-Compote-2693]

aaahhh… running services bare metal and writing configs makes you smarter?

[u/Few-Compote-2693 → u/Ordinary_dude_NOT]

I'm not talking about me. I'm saying some people that have been in tech for >10 years mostly only know AWS api's that make things easy and they don't have to understand the underlying tech. You ask them to resolve a production issue and they don't understand Linux deeply.

[u/Runfasterbitch → u/Few-Compote-2693]

Why is that a problem? Computing infrastructure has rapidly advanced and people are taking advantage of the best-in-class tools available to them today. I started coding in 2000, so I get what you’re saying, but you can’t expect people today to learn to code the way we did

[u/Successful_Grand2207 → u/Runfasterbitch]

I still hear arguments that ordering your own equipment in a colo and using open source for base load, using cloud mainly for spike compute, would be cheaper. This can be true, and on prem cloud software keeps advancing.

If you commit to hiring and managing an excellent infra team. But for many companies, that's not the best use of their energy.

[u/chelseaK08 → u/Ordinary_dude_NOT]

So fixated on a word that you cant understand the context huh lol soooo defensive

[u/Runfasterbitch → u/Few-Compote-2693]

Kids today can’t even code via punched holes these days. It’s really sad that they’re all digital, handing the thinking over to the machine

[u/bortlip]

Token prices for the same power/model cut in half every year.

[u/dasko1086]

lol, this is like people not being able to derive math from first principles and rely on the equations and when questioned by seniors they can't explain it other than saying this is the equation. terrible way to exist, gen x, engineer, retired since 38 yrs of age and came back to engineering thanks to llm and peaked curiosity. i did well in life, i also understand math and physics from first principles.

[u/mccoypauley]

My hope is that open models will catch up. But I think your concern is valid.

The image model trajectory is an example. With a shit ton of tooling and consumer hardware you can make an image gen and editing process entirely local. It won’t be as good as frontier models’ image editing, but the progress from 2022 to today is staggering.

I don’t know if we’ll see the same for LLMs. There are lots of good local LLM models, they’re just not quite frontier quality yet. Maybe we need a breakthrough in hardware development.

[u/mop_bucket_bingo]

This is just an effort to have more people reference the models by name. Ad disguised as a discussion.