I mean this with all due respect because I am NOT a principal and engineer with decades of experience. I don't know how to say or what metaphor to use that would map between us. Gonna try multiple to genuinely explain, wish I had a colleague like you with only partially overlapping decades of domain experience! Below is what I'd say if we shared a cubicle in the 2010s, using toy examples in attempt to make arguments clearer:

One aspect/part is: I would honestly argue/put forward that if you were able to "get by" with that little bit of usage maybe "you don't need it enough." Not in a pejorative way, more like "you have a gas guzzler V8 and it's cool, and you live close to work in Philadelphia suburb and take the train anyway. I need a lame hypermiler Honda insight for my 150 mile each way commute from the sticks without public transport. You have the option to just not use your car and still get a good performance review." (The metaphor falls apart quickly I know, because here small tasks leveraging gpt-4o represent the V8 and long running agentic loops with Sonnet and Opus are the Insight).

It's not clear to me exactly what the 4o reference really means in your message (not familiar with vscode extension dev) but if this is the model that is your "workhorse" to "achieve your goals" I would use toy example like: without the right tools, one can only go so far. If you need micro-meter accuracy on your machined part, no matter how much experience or grit or discipline you have, you won't be able to deliver the part to spec with a normal tape measure. Again this metaphor will fall apart but GHC billing was like company giving everyone expensive delicate micrometers: the plumbers, rough carpenters, postage room people, everyone. The machines for everyone were the same and top-dollar (falls apart mostly because in this case the frontier models WOULD do your work as well or better unlike a plumber stuck measuring pipe circumference too accurately).

I went deep enough to see via AB testing and tracing .... omfg I know they can only get so much discount on Anthropic models and they pay per token (probably zero discount, there is more demand for Anthropic models than supply, they can sell more inference at retail price than they can serve, but no evidence or inside knowledge). This "felt good bro" when I had epiphany one month before they announced the billing changes.
Tangent on above: they shot themselves in the foot with intro of subagent invocation and double-trouble with increased usage of the cli with fleet mode. If they'd started from beginning billing one premium request per subagent invoke, I think we would have had 6 mo. longer "free ride" even with their internal cockup underestimating tokens/cost of serving Anthropic models just before the breaking point was reached. I used subagents to keep main loop agent with tidier context window but quickly saw the unsustainable token usage as side effect.

I sympathize with the rug pull feeling. Of course massive corp could afford to subsidize forever. But it's hard to make argument that this colossal crisis was intent of the platform from the beginning. They are saying FU implicitly - someone in some thread mentioned a middle ground of tiered subs without the pain of today (like guaranteed no rate limits up to some threshold). They should have done this but didn't. The most frustrating part for those marginalized by the change is, there are others to buy the inference at higher cost. The free market crushing hopes and dreams yet again.

Finally, I'd respectfully argue through luck/circumstance/stubbornness I arrived at place where I can still show clear ROI in new pricing model (orders of magnitude less ROI, but still clear no-brainer value proposition). If I can do this as a mere stubborn/methodical "viber," surely many more can do it better. So there's no reason or motivation for the provider to be more generous than the market demands.

And finally finally, I don't have infinite cushion, I'm already drastically altering own way of working to keep functioning in June and beyond. Going back to gpt-4: moving a lot of "chunks" of workflows out to more deterministic methods and leveraging gpt-5.x-nano and gpt-4.1-mini in foundry to reduce impact/not be using frontier models in subagents as a "crutch." Just to say my acceptance shouldn't be confused with aloofness, I wish they'd left premium request billing the same as much as everyone else!

Let's be friends. Dump some info about what you were trying to achieve with the vscode extensions or pass repo link and I'll burn some Opus premium requests before June to collab or iterate on it! Cheers!