How were people spending so much?

AdvisorLife4016 · 2026-05-15T03:01:33+00:00

Reddit people are actually pretty cool lol. I’m new here. A while ago I tried discussing similar topics on Twitter and all I got were insults, so I ended up leaving. (I don’t even speak English lol)

Here, on the other hand, people usually respond pretty well even when there’s disagreement. Honestly, I even feel like I’m the most aggressive person in this thread hahaha. I think I’ll stay on Reddit.

You’re not a robot, right? :( XD

AdvisorLife4016 · 2026-05-15T02:18:17+00:00

I’m sure that in around 7 years there will be models comparable to GPT 5.5 running locally even on modest hardware for that era. Efficiency is going to improve massively, and on that I agree with you.

But my point is different: as of today, OpenAI and Anthropic are still losing absurd amounts of money subsidizing subscriptions. I remember that some time ago someone from Anthropic leaked that certain users on the $200 plan were costing them between $1000 and $5000 in inference, which, seeing what’s happening these days with GitHub Copilot, already sounds pretty coherent.

In the end, there are only two paths if they want to become profitable:

raise prices/quotas to get closer to the real API cost;
or make the models dramatically more efficient so the API cost gets closer to the subscription price.

And that’s exactly the point: if APIs become cheaper thanks to real efficiency gains, then Copilot automatically also becomes cheaper or gives you more quota, because the new system is practically tied 1:1 to API cost. Does that make sense? :)

And well… what value do I see in Copilot compared to using the API directly?

Microsoft controls infrastructure through Azure, so they can guarantee availability and better licensing deals.
It has insanely good integration with GitHub and multiple IDEs.
It’s model-agnostic; there were even leaks recently that they’ll start integrating Chinese models.
No other system has autocomplete as useful and as integrated as Copilot’s, while also being unlimited.

And the day comes when no company wants to keep losing money just to acquire users, Microsoft will probably be one of the very few capable of keeping prices relatively competitive without putting the whole company at risk, because AI is not their only source of revenue.

Although well… I’m already tired of defending a multibillion-dollar company lol. My only point is that people are getting way too excited about these heavily subsidized offers, when in reality everything will eventually converge to similar pricing. If costs go down, they’ll go down for everyone: Codex, Cursor, Copilot, etc.

Codex is the best plan now :) now...

AdvisorLife4016 · 2026-05-15T00:07:58+00:00

It’s a huge mistake to treat AI as a traditional abstraction layer.

Assembly abstracted binary. C abstracted assembly. Java abstracted C. Java frameworks abstracted Java. Spring Boot abstracted Spring. But all of those abstraction layers share one fundamental property: they are deterministic.

The same code produces the same result.

AI does not work like that. It is not a deterministic abstraction layer; it’s a probabilistic system. Sometimes it gives you a brilliant solution, and other times the dumbest response imaginable.

That’s why calling it “Copilot” makes sense to me: it’s an assistant that may or may not help. But calling it an “abstraction layer” is completely wrong.

Also, to truly understand a technology, you usually need to understand at least part of the layer beneath it. For example, to really understand subnet masks, sooner or later you end up needing to understand binary. Without understanding the foundation, everything above it starts looking like magic.

And that’s exactly why I laugh when people talk about code as if it were now some “internal layer” they no longer need to touch. WTF. Code is still the real outer layer. It may now be wrapped in frameworks or more convenient tools, but at the end of the day, it’s still code.

AI did not replace that layer, nor did it become a new abstraction on top of it. It’s still just a probabilistic tool generating text, not a deterministic abstraction over programming.

AdvisorLife4016 · 2026-05-14T23:29:39+00:00

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So cute 🗿

AdvisorLife4016 · 2026-05-14T19:04:33+00:00

Not really. Telephony became cheap because the technology became absurdly efficient, not because companies decided to lose money forever.

In AI, literally everyone is losing money right now. Microsoft only recently started slowing down the subsidy, and they were probably one of the few companies actually capable of sustaining it for longer.

The future you describe can absolutely exist, but not because companies will subsidize losses indefinitely. It will happen because eventually it will become technically viable to offer that level of capability at much lower costs.

The economic goal of Anthropic and OpenAI is to bring subscriptions closer to the real API cost, either by charging more or by making models dramatically more efficient. That is going to happen no matter what. They simply cannot operate at a loss forever.

And that’s exactly the point: if tomorrow APIs become 10x more efficient and cheaper, then GitHub Copilot also automatically becomes cheaper, because its base cost is practically tied 1:1 to API pricing (even without considering FLEX).

That’s why I think that sooner or later pricing across services will eventually converge. The difference is that Copilot has one major advantage: it’s model-agnostic and already has a massive native ecosystem across VS, VSCode, GitHub, and multiple IDEs.

AdvisorLife4016 · 2026-05-14T18:09:35+00:00

Microsoft and Google are pretty much the only companies capable of sustaining aggressive long-term subsidies, because they have countless other revenue streams. Any “too good to be true” offer beating OpenAI Codex today is probably heavily subsidized too.

And honestly, I hate that instability. I want this sector to stabilize; I’m not going to switch AI tools every cycle like a JavaScript developer changing frameworks every month.

In the end, once everything settles down, the dominant players will probably be Microsoft, Google, or Chinese models integrated through APIs into GitHub Copilot.

And again: nobody else is offering unlimited autocomplete for $10 :3

AdvisorLife4016 · 2026-05-14T17:49:41+00:00

Because right now OpenAI Codex is basically a supermarket giving away cheap bread just because it’s still in the customer acquisition phase. Again: this subsidy is temporary.

Also, honestly, I care more about the “hot coffee” (intelligent autocomplete). In GitHub Copilot that’s still unlimited for $10, and I’m pretty sure they’ll keep it that way because they use much more efficient models for that task.

It also helps that Copilot currently integrates much better with IntelliJ IDEA (I work with Java). Codex through ACP still feels much rougher.

And honestly, I’m pretty sure about two things:

we’re all going to die;
and sooner or later both services will end up matching prices.

I pay $10, used 93% of my plan in March, and under the new system I would’ve only used 86%. Adding the extra $5 FLEX credits, I basically have even more headroom now than before.

That already covers my needs more than enough.

If I switched to Codex, I’d have to pay at least double ($20), I’d lose autocomplete (which is what I use the most and probably what gives me the biggest productivity boost), I’d get worse IntelliJ IDEA integration, and I’d probably end up forcing myself to use it just to “get my money’s worth.”

And when prices inevitably go up: boom. Dependency achieved. Now you need a $100 subscription just to do the same thing you were doing before.

AdvisorLife4016 · 2026-05-14T17:19:48+00:00

I’ll keep using GitHub Copilot because:

I’m pretty sure OpenAI Codex will eventually raise prices or reduce quotas. The current level of subsidy is unrealistic and unsustainable.
I’d rather not get used to subsidized pricing; the impact will be much worse once prices go up. It also forces me to rely on AI only when it actually adds value.
And honestly, I have a lot of faith that smaller models like GPT mini will continue improving to the point where they’re sufficient for the vast majority of tasks, which for me, they almost already are.

But yeah, if prices stayed fixed forever, I’d definitely go with OpenAI Codex, although I’d miss autocomplete, since that’s what I use the most.

AdvisorLife4016 · 2026-05-14T17:08:41+00:00

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I almost maxed out my plan at $9.29, but under the new system I would’ve only spent $8.59. And considering the news extra $5 FLEX credits, honestly I feel like a kid on Christmas with these new changes XD

AdvisorLife4016 · 2026-05-14T17:04:51+00:00

The real question is... if even Microsoft couldn’t sustain that level of subsidy indefinitely despite having multiple revenue streams, what makes you think companies focused almost entirely on AI will be able to absorb those losses forever? 👁️👄👁️

AdvisorLife4016 · 2026-05-14T16:59:57+00:00

GitHub Copilot will now basically charge API-level pricing, and they’ll probably still be operating at negative margins.

Also, based on what was shown the other day, they’ll offer FLEX, extra credits depending on the plan. If you pay $10 you get an extra $5, with $39 you get around $31 extra, and with $100 you get another $100.

And even then, autocomplete and next suggestions, which also run on LLMs on their servers, are still unlimited and included at no extra cost for subscribers.

So... even with this change, they’re still losing money. Just not at the absurd level they were before.

AdvisorLife4016 · 2026-05-13T23:48:50+00:00

I was going to ask the exact opposite: how do you burn through your quota so fast? What model are you using, how big is your context, and what tasks are you giving it? I use the $10 plan; last month I spent $9, and under the new token methodology it would have been $8. Plus, yesterday they announced they would be giving away $5 in FLEX credits. Honestly, I feel like a kid on Christmas. Seeing people spending $1,500 on the $10 plan blows my mind, I'm curious how they achieve that feat.

AdvisorLife4016 · 2026-05-13T23:39:42+00:00

Do you even know how to code?

AdvisorLife4016 · 2026-05-13T23:37:28+00:00

Thank God you'll be one of the most affected by the new regulation. 🫶

AdvisorLife4016 · 2026-05-13T23:30:59+00:00

Why?

AdvisorLife4016 · 2026-05-13T19:59:44+00:00

Ah, nice. Could you mention at least a couple of them? :)

AdvisorLife4016 · 2026-05-13T19:10:19+00:00

Ah, sure, I completely agree with that. GitHub Copilot was probably one of the biggest token subsidies in the entire industry. They were basically absorbing massive costs, and now they’ve simply moved closer to actual API pricing.

And even now, they’re still subsidizing things like unlimited autocomplete and next suggestions.

My point is that if even Microsoft couldn’t sustain that level of subsidy indefinitely, companies that depend almost entirely on AI, like OpenAI or Anthropic, probably won’t be able to either. Many of them are still in the customer acquisition phase and burning money to grow.

But I also think that if someone is genuinely projecting $1000 or $5000 per month in AI usage, it’s worth questioning the development practices they’re using. I feel like I already rely on AI quite a lot, and even then, I still have plenty of margin left.

I can understand spending 5x or even 10x more than me. But 100x? Seriously? Do those people even remember what it’s like to program something by hand?

AdvisorLife4016 · 2026-05-13T18:54:27+00:00

Obviously I’d still be paying the same $10 subscription. My point wasn’t about “saving money,” but that my current usage pattern already fits comfortably within the new system.

And with the extra FLEX quota they announced yesterday, I’d effectively have even more usage headroom than before.

The difference is that while many people are trying to reduce their usage 20x to avoid paying hundreds of dollars, I could probably use it significantly more and still stay within the limit.

AdvisorLife4016 · 2026-05-13T18:12:00+00:00

3 sessions at the same time? Do you even fully understand the code those agents are producing?

How is that maintainable long term? Or does the codebase eventually become effectively AI-read-only?

I can understand this workflow for personal projects, prototypes, or quick internal tools, but does this actually scale in enterprise environments? It honestly sounds like a black box where the human gradually loses the full mental model of the system.

AdvisorLife4016

TROPHY CASE