#32: Contra Citrini7 (Repost)

I have recently begun publishing shorter essays on X/Twitter. My critique of Citrini7’s essay “2028 Global Intelligence Crisis” from one week ago received good pickup there, so I’m re-publishing it for you here. Feel free to skip if you’d already seen it; there are no changes to the content. In due time, all my X essays will also be re-published here on Substack.

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Popular markets commentator Citrini7 recently published a compelling and popular piece of AI doomer fiction, admittedly with some small probability of occurring. But I am old enough to have seen many cycles of economic doomsaying. I want to present a critique of Citrini’s work and show a much likelier, more positive view of the future.

1. Never Underestimate Institutional Momentum

In 2007, people thought the US was geopolitically done under peak oil. In 2008, they thought the US dollar was just shy of collapse. In 2014, they thought AMD and NVIDIA were done. Then came ChatGPT, and they thought Google was done... Every time, existing institutions with momentum have proven themselves far more durable than onlookers thought.

When worried about institutional turnover and rapid labor replacement, it is very funny that Citrini writes:

Even places we thought insulated by the value of human relationships proved fragile. Real estate, where buyers had tolerated 5-6% commissions for decades because of information asymmetry between agent and consumer...

People have been calling for the end of the real estate broker for 20 years! You don’t need superintelligence for this! All you need is Zillow or Redfin or Opendoor. This example actually shows the very opposite of Citrini’s point: we have a type of labor that most people consider obsolete, and yet, market inertia and regulatory capture have made the real estate broker far more resilient than anyone would’ve bet a decade ago.

My wife and I bought a house a few months back. The transaction required us to have an agent, ostensibly for the above reasons. Our buyer’s agent made about $50,000 on the deal, for about ten hours of form-filling and party-coordination that I could’ve done myself. This market will eventually be efficient and price this labor fairly, but it takes a long time to get there. I know a lot about inertia and change management: I built and sold a company that focused on moving insurance brokerages from service to software, and the main thing I learned is the iron rule of dealing with human reality: everything is always more complicated and takes much longer than you think it will, even if you already know about the iron rule. That doesn’t mean that a meaningful change in the world won’t happen, but that the change will be more gradual, giving us the time to respond and adjust.

2. Software Has Infinite Demand for Labor

The software sector has been struggling in recent months as investors fear that companies like Monday, Salesforce, Asana, etc. can now be easily replicated and that the value of their backend systems is indefensible. Citrini and others talk of AI coding as spelling the end of jobs at SaaS companies as (1) the products become obsolete/zero-margin and (2) the jobs themselves disappear.

What everyone seems to be missing is this: these products fucking suck. I can say this, because I’ve actually spent hundreds of thousands of dollars on Salesforce and Monday. Sure, maybe AI enables competition to replicate their products. But more importantly, AI enables competition to deliver better products. It’s no surprise to see the stocks drop: an uncompetitive, sticky lock-in sector filled with dogshit incumbents is becoming competitive again.

More generally, it is uncontroversial that virtually all current software is garbage. Everything I use and pay for is littered with bugs. Some software is so broken that I can’t even pay for it. I have not been able to send a wire using Citibank’s online banking in three years. Most web apps can’t even get mobile vs. desktop right. Nothing has the functionality that you want. Everything is deficient. Silicon Valley darlings like Stripe and Linear have built massive followings just by not being as insanely unusable and horrendous as their competitors. Ask tenured engineers “show me a piece of good software” and you’ll get long silences and blank stares.

There is a deep and important truth here: even if we get something like the Software Singularity, the level of demand for labor here is practically infinite. Famously, it is the last few percent of completion that take the most work, and by that token, virtually every software product could probably scale up its complexity and features by something like 100x before beginning to saturate demand.

I have the feeling that commentators on the imminent demise of software don’t have much intuition for making software. We’ve had software for about fifty years now. Though it has improved meaningfully over the years, it has always been inadequate. As a programmer in 2020 I was able to do what would’ve taken hundreds of man-years in 1970; the leverage gained is incredible, but the results still leave massive space for improvement at every step along the way. People underestimate Jevons Paradox. Importantly, this does not mean that software engineering is a forever-resilient source of jobs. Of course not; nothing is. But my point is that again, the sector has more momentum and ability to absorb labor than people give it credit for, and saturation of this will be a slow process, giving us time to respond and adjust.

3. Re-Industrialization

There will be some labor displacement, of course. Driving stands out. Many types of white-collar work, as Citrini suggests, will undergo some gyration as some jobs disappear and others change meaningfully. AI may be the straw that breaks the camel’s back for jobs like the real estate broker, where the job had actually already disappeared a long time ago, but the pay was still there.

The saving grace here is that in the US, we have a virtually limitless capacity and need for re-industrialization. You may have heard about bringing back manufacturing, but it’s more than that: we largely no longer know how to create, and don’t have the facilities for, making the core building blocks of modern life: batteries, motors, small semiconductors — the whole electric stack is something we are almost entirely dependent on China and other countries for. What if there’s ever a military confrontation? Actually, it’s much worse than that: did you know China makes 90% of the world’s ammonia? If there’s a war, we can barely make fertilizer. We’d just starve.

Once you start looking at the physical world, you see a virtually endless scope for work on job-creating, nation-benefiting, fundamental infrastructural work that is politically bipartisan.

We’ve seen the economic and political milieu slowly make their way in this direction — talking about re-industrializing, manufacturing, deep tech, American dynamism, and so forth. My prediction is that as AI challenges white-collar labor, the political path of least resistance will be funding large-scale re-industrialization in the form of employment megaprojects which, thankfully, are not subject to a singularity but rather move at the friction-heavy speed of getting things done in the physical world. We’ll build bridges again. People will find it gratifying to see the fruits of their labor in the real world, not in digital abstractions. The Senior PM at Salesforce that loses their $180K job might find a new job in the field at the California Desalination Works, to finally, finally, end the 25-year drought. And it shouldn’t be good enough, but excellent. And once it is built, it must be maintained! Once more, Jevons Paradox can apply, if you allow it to.

4. And Beyond

The outcome of industrial megaprojects is of course that we move toward abundance: America will once more be independent, and make things at large scale and low cost. Transcending material scarcity is the key: in the long run, if we do lose almost all the white-collar jobs to AI, we have to be able to provide people with a continued high quality of life. Part of this we get automatically, just because AI taking margins to zero means that those consumer products will become equivalently cheap.

My view is that different parts of the economy will “take off” at varying speeds, and virtually all the areas are slower than a piece like Citrini’s might suggest. To be clear, I am extremely bullish on AI, and expect that one day, my labor too will be obsolete. But it’s going to take a while to get there, and that time gives us the opportunity to make good policy.

On that front, preventing a market meltdown the way Citrini imagines is actually pretty easy, and the federal government’s response during Covid showed how proactive and aggressive it is willing to be. I’d expect large-scale stimulus to kick in quickly once needed. It slightly irks me to say that it won’t be efficient, but that’s also not the point. The point is material prosperity for people in the course of their lives — broad consumer well-being that legitimizes the state and carries forth the social contract — not satisfying the accounting metrics or economic norms of the past. If we are nimble and responsive to this slow but sure technological revolution, then we will be fine.