070- Boil the Ocean

In February 2026, Y Combinator CEO Garry Tan published a short essay arguing that “don’t boil the ocean” — the most common piece of startup advice — is now obsolete. His reasoning rests on a chain of ideas stretching back 160 years, through a Victorian economist, a radical architect, and two professors betting on the price of tin. I followed that chain. It changed how I think about everything.

The Paradox That Triggered a Coal Panic

In 1865, a 29-year-old English logician named William Stanley Jevons published The Coal Question. His central observation was so counterintuitive that economists are still debating it 160 years later:

“It is wholly a confusion of ideas to suppose that the economical use of fuel is equivalent to a diminished consumption. The very contrary is the truth.”

Making fuel more efficient does not reduce consumption. James Watt’s steam engine used 75% less coal than the Newcomen engine for the same work. And yet British coal production grew 3.5% per year for 80 straight years — from 5.2 million tons in 1750 to 292 million tons at peak in 1913. A 56-fold increase.

Watt’s engine didn’t conserve coal. It made coal-powered work so cheap that steam engines migrated from mine pumps to cotton mills to railways to steamships. Every new application that became economically viable created demand that overwhelmed the efficiency gains.

This is the Jevons Paradox. And it has repeated with eerie precision wherever a fundamental resource has gotten dramatically cheaper.

14,000x Cheaper Light, 6,500x More Consumption

Economist William Nordhaus traced the cost of artificial light from the 1300s to the present. One million lumen-hours cost the equivalent of £40,800 in the 1300s. By 2006: £2.90. A 14,000-fold decline.

Did humanity respond by consuming the same amount of light? The average UK resident in 2000 consumed 6,500 times more artificial light than in 1800. Computing tells the same story — cost per gigaflop dropped from $18.7 million in 1984 to three cents in 2017. Total compute consumed went up by orders of magnitude. Storage, communication, bandwidth — same pattern, every time.

The cheaper the resource, the more we consume. As long as human desire for it is elastic, Jevons holds.

Fuller’s Arc: From Stone to Nothing

While economists debated the paradox, Buckminster Fuller was watching the same phenomenon through a different lens. He called it “ephemeralization” — doing more and more with less and less until eventually you can do everything with nothing.

Stone arches. Iron trusses. Steel cables. Wireless signals. Each generation of bridge required less material. But the number of connections, the volume of communication, the scope of what bridges enabled — that exploded beyond imagination.

Fuller and Jevons aren’t contradictions. They’re two sides of the same process. We do more with less of this specific thing (Fuller’s insight), which makes the underlying capability so cheap that we consume vastly more of it (Jevons’ insight).

The Ehrlich-Simon Bet

In 1980, Stanford’s Paul Ehrlich — who predicted hundreds of millions would starve in the 1970s — bet economist Julian Simon $1,000 that five metals would rise in inflation-adjusted price over ten years. Ehrlich picked chromium, copper, nickel, tin, and tungsten.

All five declined. Tin fell 55%. Tungsten dropped over 60%. The $1,000 basket was worth $423.93 by 1990 — despite world population growing by 800 million, the largest single-decade increase in human history. Scarcity incentivized innovation, substitution, and new discoveries. Ehrlich mailed a check for $576.07 and never bet on resource prices again.

Intelligence Is Collapsing Faster Than Anything Before It

Now there’s a resource collapsing in cost that makes coal, light, and metals look like gentle declines. That resource is intelligence.

Epoch AI found that LLM inference prices are falling between 9x and 900x per year, with a median of 50x. Since January 2024, that accelerated to 200x per year. GPT-3.5-level performance dropped 280-fold in cost — from $20 per million tokens to 7 cents — in two years.

And here’s the Jevons effect in real time: despite per-token costs falling 280x, total inference spending grew 320% over the same period. Researchers found super-elastic demand — a 1% price decrease drives a 1.42% volume increase. Price times quantity riseseven as price falls. Demand for intelligence is, in the paper’s language, “currently un-satiated.”

No previous resource — not coal, not electricity, not computation — has become cheap this fast.

This Is Personal

I spend every day thinking about what happens when energy becomes the bottleneck. When intelligence is cheap but you need electricity to run it. When every home has solar and batteries and heat pumps and EVs, but nobody has figured out how to coordinate them.

Germany had 457 hours of negative electricity prices in 2024. Generators paying people to take their power. Jevons would have recognized it instantly — we made electricity generation incredibly efficient, and demand exploded into categories nobody anticipated: data centers, EVs, heat pumps, AI inference clusters drawing megawatts.

Tan’s essay distinguishes two responses to this moment. The zero-sum response: use AI to do the same thing cheaper, cut headcount, eke out 5% efficiency gains. The positive-sum response: attempt things that were previously impossible.

Applied to the energy grid — the zero-sum response is building more solar panels and bigger batteries. Throwing hardware at the problem. The positive-sum response is asking: what if every home was a power plant? What if every battery was a grid asset? What if every EV was a node in a distributed network that could balance the grid in 200 milliseconds, from the edge, locally?

The Ocean Is Already Boiling

If Jevons is right — and 160 years of evidence says he is — the demand response to near-free intelligence will be proportionally extraordinary. The organizations and founders who raise their ambitions rather than protect their incumbency will define the next era. The ones who respond with zero-sum fear will find that the ocean is boiling around them whether they like it or not.

Fuller, who died in 1983, anticipated this moment: “Ephemeralization trends towards an ultimate doing of everything with nothing at all.” Intelligence approaching zero marginal cost is the logical terminus of his arc from stone to wireless.

The question is no longer whether this is happening. It’s whether we’ll use the moment to boil oceans — or drown in committee.

Key Takeaways

* The Jevons Paradox — making a resource more efficient doesn’t reduce consumption, it unleashes demand. Coal, light, computing, and storage all followed this pattern over 160 years.

* AI inference costs are collapsing faster than any previous resource: 280x cheaper in two years, accelerating to 200x per year. Yet total spending on inference grew 320%, showing super-elastic demand.

* Jevons and Fuller describe two sides of the same process: we do more with less material (ephemeralization) while consuming vastly more of the underlying capability (the paradox).

* The energy grid is the next Jevons battleground — cheap solar created 457 hours of negative prices in Germany, and AI-driven demand is exploding. The positive-sum response isn’t more hardware, it’s coordination infrastructure at the edge.

Full transcript available below the audio player.

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