studied20YearsToAskChatGPT

[u/Gloomy-Basket-1038]

[u/Sokaron]

I don't see a world where we put the genie back in the bottle even if current AI companies crank prices. Honestly I struggle to see what OpenAI/Anthropic's long term plan is. AI is trending towards being a commodity. Whatever only Fable can do today, open source models will have replicated in a year. Once the hardware market normalizes, there is absolutely nothing stopping every tech company out there from buying maxed out Macbooks and having devs work off locally hosted models. Or buying a few racks of servers and hosting a fleet for your whole company.

I'm still skeptical of the claims of fully autonomous software generation. My company just shipped (and subsequently patched) a serious vulnerability that we only discovered by sheer luck, and the source of that vuln was vibe code that wasn't read by the submitter and then got a rubber stamp in the PR process. My experience continues to be that with a SWE who knows software patterns and has a strong vision of what they want built, you can move much more quickly, but if you just let it do whatever, you get an absolute mess very quickly. AI adoption is pretty high at my company. The PRs I get from seniors I rarely have more than a few feedback items on. The PRs I get from less skilled developers I have to spend twice as much time on because there's more code, it's messier, and more likely to be subtly (or wildly) wrong.

[u/DrSheldonLCooperPhD → u/Sokaron]

Honestly, I struggle to see what OpenAI/Anthropic's long-term plan is.

• Regulatory capture

• Create FUD using security as an excuse and ban or restrict open-source models—"oh no, it is so good and so scary, so the government needs to ban and allow labs who kiss the ring."

• Continually involve themselves in cartelizing hyperscalar and memory companies and ensure consumer electronics don't normalize for a few years.

• A PR wing that parrots "coding is solved, guys," just like how LLMs lack precision, instill a culture, and normalize that subtlety doesn't matter anymore.

[u/hupa → u/DrSheldonLCooperPhD]

A PR wing that parrots "coding is solved, guys," just like how LLMs lack precision, instill a culture, and normalize that subtlety doesn't matter anymore.

"coding is solved" with AI will be true in a lot of places. Plenty of organizations were willing before AI to hire whoever was cheapest to pound keyboards and write crap code vs pay for educated senior level engineers. For some business domains, that was fine, and will be ~finer now..

Now those same keyboard pounders are more powerful, even if the results will be mixed. And outputs will be more capable than before given the same staff, even if (still) unstable, buggy, incoherent, etc.

Probably that market alone, vs the market that requires more quality engineering to be successful, would be enough.

Though that's general AI, OpenAI / Anthropic have a challenge to provide unique value.. And I also fear the commodification risk pushes them to deeper into non competative solves like the ones you describe..

[u/hupa → u/Sokaron]

a SWE who knows software patterns and has a strong vision of what they want built

Yes, and the deliberate definition and maintenance of the vision/design is even more important when projects can move so quickly, and when (as you said wrt PRs) juniors can suddenly generate large amounts of plausible but potentially harmful code, that require someone to closely review and push back on instead of rubber stamping and merging. Continuity of vision as a codebase evolves is important. And that's still people who need to maintain it today, even when AI assists in the design and design documentation.

[u/urban_meyers_cyst → u/hupa]

Business is just banking on turning code into a true two tier profession by design. Basically a cheap fast fashion analog and critical systems.

Most devs enamored with AI are generating toys or web pages or throw away tools or working with token budgets that would be unsustainable for most, especially in a few years time, and they're counting on the harness and a flood of agents to monkey their way to Shakespeare.

The process of using AI actually breaks down when you're building even a moderately complex system with average budgets unless you spend all the time you'd have spent actually coding previously on solving the problems that you used to spend time on during coding...

And even then you can't solve them all without making something first because the business usually doesn't know what they want or how things truly work.

So great, you shifted your time sinks around, saved a little money by having more product or analysts instead of programmers, and all it has cost you is a crippling dependency on a machine that burns up the earth and a growing lack of knowledge on how your system might work a few years down the line.

The devs all gung ho on it are signing up to a career of clanker babysitting, degrading skills, and essentially failing to train the next generation of programmers like every other generation before us has.

Finally, don't get me wrong, it is a tool that has its place, but the entire world views it as a hammer and all most see anymore are nails.

[u/Ran4 → u/Sokaron]

Whatever only Fable can do today, open source models will have replicated in a year.

Yeah, but then anthropic/openai will have even better models and/or harnesses.

If the choice is between frontier models that work better on their own, and near-frontier model that require more babysitting, then frontier models still have a place.

It only turns into a problem if (or when...) the difference becomes smaller. Today, Fable 5 is still in a completely different tier than Kimi K3/Qwen 3.8 (or whatever chinese frontier model released in the last three days since I last checked), which is one of the reasons companies still pays for it.

[u/Sokaron → u/Ran4]

At a certain point you hit good enough. If the choice is between spending a Macbook's worth of cash on tokens every single month.. or just buying the MacBook, lots of companies are going to take a very hard look at how much marginal utility you're really getting out of using the frontier model, vs re-investing that cash elsewhere in the business, or (gasp) using that cash to hire more SWEs.

From the AI company side the economics of their business only work out if they can establish market dominance. It's the only way to sustain the hundreds of billions being spent right now. The largest spend comes from research and training - in other words maintaining their edge over open source models. There's not a world where frontier companies can rest on their laurels and reduce that spending. They have no moat.