Involuntary Insulls: Frontier Labs as Banks

RSI and maximizing utility

the Sams

precious resources

San Francisco is obsessed with a new term; Recursive Self-Improvement. RSI is the holy grail of the AI quest that Claude Code launched 6 short months ago, when coding harnesses and their ability to steer self-improving loops became the target of nearly every lab on earth. The paradigm of call-and-answer chatbots suddenly became the passé lame Old Thing, and code-your-way-to-RSI was the New New Thing.

I think that it’s worth it to spill some words on what the shape of Frontier Labs will become if we succeed in automating the work of making AI, and how the priorities of these orgs will shift from talent to capital.

Today I’m going to argue that if you believe that RSI is around the corner, you should expect that labs will be banks, not research institutions.

the man who financialized the light bulb

Sam Insull is not a household name in 2026, but he was for a few dazzling moments 100 years ago both the most loved and most hated man in America. He arrived in the US in 1881 and became Edison’s private secretary, and is responsible for doing a lot of the boring work of getting the lightbulb out of the realm of “interesting” and into the realm of “indispensable”.

Insull took the lightbulb invention to Chicago, built the central power stations and worked out the business model of electricity, and made the first modern utility company. He took electricity from an engineering business to a capital business, and built himself an empire of leverage and lightbulbs.

Electricity plants, you see, cost a fortune, but one more kilowatt costs almost nothing. Whoever could build the biggest plant won, because the economics compounded. Thus the buildout was about who could raise the most money, build the biggest plant, and that meant the engineering happened at the finance level.

He invented much of the financial machinery we take for granted in the modern era; utility stocks sold to hundreds of thousands of ordinary people, stacking holding companies, leveraged apparatuses that turned small savings accounts into big ol’ power plants.

This all made him one of the most famous people on earth- he was on the cover of Time in ‘26 and again in ‘29, weeks before the crash that kicked off the depression.

At the peak his structure controlled something like five hundred million dollars of assets on about twenty-seven million dollars of actual equity, (about ten billion dollars of assets on roughly five hundred and forty million of equity in 2026 money) which is a way of saying the whole thing was leveraged to hell and back.

By 1932, that leverage crashed down and 600k ordinary Americans were wiped out. Insull became a hated figure, the poster boy for the great depression, and was eventually charged with mail fraud and antitrust, acquitted on every count, and died penniless in Paris four years later. He was identified by police through a slummy hotel laundry bill in his pocket.

Insull is the ghost that haunts frontier labs. Edison is the devilishly charming frontman, sure, but the grim transition from “the age of research” to “we automated all that” is a very prescribed journey to scaling the technology.

Fans of Carlota Perez know this is not an original idea of mine; this passage from the inventor to the financier is inevitable. The railroads went from engineer-heroes to J. P. Morgan consolidating the whole industry from the deck of a yacht.

If AI is going to be a utility, then RSI is the moment where SF hangs up the researcher title and admits that we’re just financiers. The final scaling law of AI may be discovered on Wall Street, not in SoMa. Everyone wants RSI, but nobody wants to work for a bank; but if RSI works we’re all involuntary Insulls.

four things in the building

Last week I wrote about the four things of value in a frontier lab- weights, methods, people, culture. I argued that the culture is the most durable of the four and the hardest to steal- and I still believe that. My argument today is that the culture of labs is going to change as the MTS role transitions from researcher to technician (an agent-babysitter, whatever you want to call it). The talent-first lab that is fiercely protecting the dishevelled researcher is swept away with the rise of RSI-first lab culture; it’s just a question of GPUs, which is the same as saying it’s a question of financing.

If a lab today is a machine that concentrates the focus of a few hundred minds into a vital effort, that bottleneck may disappear with RSI. Agents propose the architecture, write the training code, run the experiment, read the results, and move onto the next one, faster than any human can execute.

This is far from a certainty- Ali Ghodsi, who runs Databricks, yesterday did an admirable job of grounding the conversation at Open Frontier by saying when he looks at how the labs actually train, “the next training run is more expensive, more complicated, and more humans involved,” which is “the opposite of what you would have expected if we’re going towards that kind of recursive self-improvement loop, where you would expect that the next GPT-6 or GPT-7 costs a thousand dollars and takes a week.”

So this isn’t a certainty, but a possible future. If you believe this is possible then two of those four pillars of value in a lab become a commodity- 1. culture but especially 2. researchers, even leaning negative due to the cost of deals made by enthusiastic collectors of talent. Instead, it is the compute the automated researchers run on, the energy that feeds the compute, and the capital that buys both.

Capital, dear reader, is not anything like talent. Talent is scarce, ideally sticky, has a conscience. The only thing important that capital and talent share is a tendency to work for your competition if you screw up.

The core competency of an RSI-fuelled lab is “raise and deploy money at low cost.” That is a bank, or something in the family of a bank. Welcome to the Insull Era.

the frontier is already a capital-markets desk

Stargate is a financial instrument. Compute-for-equity swaps with hyperscalers? finance. Vendor financed chipmakers funding customers who buy chips? finance. Data centers in SPVs, off-books debt, decade-long gigawatt power purchases, turbines being snatched up across the globe? finance, finance, finance. The 2029 frontier might be a capital desk trading orbital compute derivatives.

Think I’m overstating? OpenAI is hiring a Head of Compute Capital Markets, a person whose entire job is to “build durable financing architecture for hyperscale AI infrastructure” and “reduce cost of capital.” Anthropic is staffing a Capital Markets and Corporate Development team and asking for eight years of investment banking and private equity.

So wherefore the culture of these labs?

what happens to the monastery

If the most important person in the office of Anthropic in 2028 is the person who can site a gigawatt of power, prestige will flow very differently. If Claude writes the papers, the people in finance, energy, law, land acquisition, and government relations start to take over. The median employee of a frontier lab stops being a genius and becomes a project-finance associate, which is a fine thing to be and a completely different culture. Perhaps these jobs will be done by a future Claude?

As an industry we’re organized around genius worship, which lends me hope that the Country of Geniuses in a Datacenter might also site more datacenters. Leverage might flow to Claude, and my concerns are unwarranted; I suppose the outcome of zero Anthropic employees might be preferable to some version of the company where a guy super-connected in local Virginia power company boards is running the show.

I think more likely than that is that there is a gradual downgrade:

engineer->operator->technician.

The blacksmith who forged each piece by eye and hammer gives way to the person who feeds blanks into the stamping press and clears the jams. It’s a badge and a paycheque, but far removed from system design. That press makes ten thousand in the time that it took to make ten; I think that is the move recursive self-improvement runs on the researcher. The model becomes the smith, and the researcher, if he is lucky, becomes the technician who keeps the smith fed and swaps it out when it breaks.

I am concerned to think of what a capital-first organization does when confronted with some of the difficult decisions that have no doubt kept Sam and Dario up at night these past years. A capital-first org cannot routinely refuse cheap capital and survive; cheap capital is the fundamental instrument of AGI progress.

Leveraged compounding machines are fragile things, and they become too big to fail pretty quickly.

the bubble

Insull’s story is a story of both capital and collapse. The pyramid of holding companies worked beautifully when the times were good and the money was cheap, but things turned sour when the market did. AI has survived winters before, but not winters where double digits of the American economy were reliant on datacenter buildouts.

I am not a bubble believer, but I see why it is so concerning to some folks. Training a multi-billion dollar model on a ten-billion dollar cluster and getting back a marginal improvement makes me nervous.

The brilliant folks at Exponential View recently sized the AI economy, and that gave me a lot of hope. What gives me pause is that banks all share one pivotal feature- they don’t tend to go out with a whimper, but with a bang. The morning after a bank collapse is not a pretty sight.

the most regulated thing in the world

A bank is one of the most heavily regulated things our society creates- and for a damn good reason. It has to hold capital against its risks, submit to stress tests, open its books to a supervisor who can walk in any day, and above all it has to accept that once it is large enough to take the whole system down with it, it stops being fully its own.

If the state ever starts understanding AI companies in this lens, the argument for regulation and assertive control becomes a lot easier. Using the toolkit we deployed for the atomic era matches up poorly against a technology like AI, but if labs are banks; legible, addressable, auditable, the control mechanism of a balance sheet becomes digestible by DC.

The Insull Phase may not end in a libertarian utility, but in a very normal Public Utility. The Fed for compute might end up deciding who may get access to that new gigawatt in Utah. This may be a viable way for Washington and Beijing both to get their arms around AI.