Cheap or expensive is the wrong question
There are two arguments running side by side on the feed right now, and the people having them don't realize they're having the same one.
The first is about the Chinese models. DeepSeek will run you about $0.14 per million tokens of input and $0.28 on the output — somewhere between 35 and 100 times cheaper than a frontier Western model — and at that price the conclusion writes itself: it's over, the bottom has fallen out, intelligence is basically free. The other end I can speak to personally, because I recently paid $160 for an hour of a frontier model on a genuinely hard problem. That's the fully loaded rate of a $330K-a-year engineer. You can call it absurd, and depending on the day I'll agree — except some days I mean absurdly expensive and some days absurdly cheap for what it actually did, and that whiplash is the whole story.
Both reactions are correct. $0.14 a million tokens and $160 an hour aren't competing claims about whether AI is cheap or expensive; they're two points on the same curve. The only honest answer to "is this cheap or expensive" is another question: for what you're trying to do? When I paid for that hour I wasn't overpaying and I wasn't getting robbed — I had a problem that lived at that end of the frontier. On a different problem the same week I'd have reached for something 100x cheaper and been just as right.
The confusion comes from a mental model we haven't let go of. People still think in terms of the prompt — you write it, you hit go, and either it works or the magic dies and you decide the whole thing was oversold. But the prompt was never the unit of work. The loop is. An agent, the way I'd define it now, is something with a goal, a loop, and an eval, and it grinds against that eval until the goal is met. Seen that way, the disappointment looks less like broken technology and more like a loop nobody bothered to give an eval or a second attempt.
Once work is loops instead of prompts, the loops vary in quality, and that's where it becomes a market. For a fee you'll rent whatever a loop needs — expertise dropped in, compute by the hour, a live link to the real world, a skill on demand — chosen on a blend of price and quality tuned to the job. Which is just the cost-quality frontier showing up one level down.
That's the part we're underrating. At any moment there's a frontier of cost and quality, and different problems sit naturally at different points on it. Cleaning a spreadsheet doesn't belong where designing a bridge belongs. Today we have a handful of crude dots; soon we'll have hundreds, and the frontier itself marches outward the way it did for the semiconductor — the same dollar buys more next year than this year.
This is good news. Stop asking whether a model is cheap or expensive. Nothing is, in the abstract. It's positioned — and the only question that matters is where on the frontier your problem belongs.
What I wish I knew before a Physics PhD
My physics PhD took up 22% of my life, and I hope I learned a lot during it. If I had to pick one thing that would have materially changed how I approached it: a physics PhD is judged by the volume and quality of the publications you produce. Classes, volunteer work, extracurriculars are essentially irrelevant to the task at hand. If you're serious about physics, optimize (volume of publications) × (quality per publication). Everything you do should boost one or the other.
On the economics of the decision
Theoretical physics PhDs bear enormous opportunity costs. The time isn't free — you could be doing another kind of research, learning a trade, or being paid handsomely to move numbers around a screen. They carry many of the intellectual challenges of medicine without the impact of relieving a child's suffering, and many of the challenges of engineering without owning valuable IP. Time spent on this instead of anything else needs to be accounted for.
Motivations change. When you start, your focus is on expanding horizons — curiosity, new experiences, growth. When you finish, much of your focus is on becoming rooted — family, career, a personal brand. There are real tidal forces between the ideal program when you begin and the ideal one when you finish.
High supply and low demand for theoretical physics PhDs means a low price of labor. Being smart doesn't mean the market values your contribution. And building an alternative career requires skills a PhD doesn't develop — the modern economy values teamwork, quick decisions, and clear communication, none of which thrive in a monastic working style.
Finishing a PhD can be a red flag for startup entrepreneurship. Your 20s are perfect for startup dynamics; finishing first tends to lower, not raise, your odds. The most successful startups based on PhD research usually had the students drop out before completion.
On physics itself
Physics is an experimental science and the best work is done in experiment, not theory. A mediocre experimentalist contributes vastly more than an outstanding theorist. And formal methods are for chumps — you won't beat a 60-year-old Russian master at asymptotic series, but you can beat him with intelligent numerics sampling billions of examples. If you aren't using computers early, you're doing it wrong.
On being a good PhD
Treat your research like a job: show up on time, write clear presentations, read the relevant work, find the people who can get you over the sticky bits, and care enough to do it well. Bad employee behavior translates directly into bad research. Alignment with your advisor is built over a long time — if you want early graduation or first authorship, build the case for why it's in their interest too. Generalists don't publish much; specialize quickly or run out the clock with something shallow.
What I'd do again
Productive goofing off paid enormous dividends. My unstructured time went to Chinese, economics, and programming — three things I use every day, and more profitable than my formal education during the PhD. Going to a name-brand school helped even more once I left physics; alumni networks can make or break a first job search. And I took a deliberate, two-year job search to figure out what I actually wanted to do.