Truth: The Strength and Weakness of AI Coding

There was a seismic shift in the AI world recently. In case you didn’t know, a Claude Code update was released just before the Christmas break. It could code awesomely and had a bigger context window, which is sort of like memory and attention span. Scott Cunningham wrote a series of posts demonstrating the power of Claude Code in ways that made economists take notice. Then, ChatGPT Codex was updated and released in January as if to say ‘we are still on the frontier’. The battle between Claude Code and Codex is active as we speak.

The differentiation is becoming clearer, depending on who you talk to. Claude Code feels architectural. It designs a project or system and thrives when you hand it the blueprint and say “Design this properly.” It’s your amazingly productive partner. Codex feels like it’s for the specialist. You tell it exactly what you want. No fluff. No ornamental abstraction unless you request it.

Codex flourishes with prompts like “Refactor this function to eliminate recursion”, or “ Take this response data and apply the Bayesian Dawid-Skene method. It does exactly that. It assumes competence on your part and does not attempt to decorate the output. It assumes that you know what you’re doing. It’s like your RA that can do amazing things if you tell it what task you want completed. Having said all of this, I’ve heard the inverse evaluations too. It probably matters a lot what the programmer brings to the table.

Both Claude Code and Codex are remarkably adept at catching code and syntax errors. That is not mysterious. Code is valid or invalid. The AI writes something, and the environment immediately reveals whether it conforms to the rules. Truth is embedded in the logical structure. When a single error appears, correction is often trivial.

When multiple errors appear, the problem becomes combinatorial. Fix A? Fix B? Change the type? Modify the loop? There are potentially infinite branching possibilities. Even then, the space is constrained. The code must run, or time out. That constraint disciplines the search. The reason these models code so well is that the code itself is the truth. So long as the logic isn’t violated, the axioms lead to the result. The AI anchors on the code to be internally consistent. The model can triangulate because the target is stable and verifiable.

AI struggles when the anchor disappears

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Against Eugenics, on its Own Terms

Once upon a time, eugenics was all the rage. It was nascent during the reconstruction era and persisted into the 20th century. It grew out of biological evolutionary theory and emphasized reproductive fitness. In brief, the theory asserted that there are differences in individual fitness and that the more fit living things will survive better and reproduce, eventually becoming a greater part of the population. The ability to compile and evaluate statistics about various human measurements made inferences hard to resist. Of course, researchers were plagued by small sample size, omitted variable bias, and social biases of the day (for example, phrenology inferred fitness characteristics from skull shape).

People employing eugenic thinking, overwhelmingly, supported theories that their own type of person was among the more fit. Eugenicists didn’t promote theories of their own un-fitness. In the progressive era of the early 20th century, eugenics met the prevailing attitude that government could be employed to resolve social and economic ills. This era is when the income tax emerged, prohibition was enacted, the Federal Reserve was formed, and various labor regulations were enacted.

The result was that policy sometimes pursued greater ‘fitness’ among its populations. Rather than systematically encouraging the supposedly more fit with economic incentives, most policy was geared toward reducing the reproductive success of supposedly less fit people. These included forced sterilization, institutionalization, and economic exclusion. Besides rejecting basics individual human dignity, the harm was all the more tragic given that fitness was often poorly specified. That is, policy criteria weren’t dependably related to fitness. Fatal conceit, indeed!

One of my favorite ways to argue is to grant premises and then change details on the margin to see whether the conclusion changes. Let’s do that. Let’s grant that there are innate differences between people that are related to biological success. Since survivability is related to resource acquisition, let’s grant also that economic success overlaps at least somewhat.  Taking that as granted, does pursuit of the historical eugenic policy still follow?

It does not.

There are two mistakes that eugenicists and various sorts of racists and xenophobes made. They assert or imply 1) that fitness characteristics are stable and systematically identifiable, and 2) that policy needed to intentionally select for the fitness characteristics.

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Which Economies Grow with Shrinking Populations?

If you didn’t know, China has had negative population growth for the past 4 years. Japan has had negative population growth for the past 15 years. The public and economists both have some decent intuition that a falling population makes falling total output more likely. Economists, however, maintain that income per capita is not so certain to fall. After all, both the numerator and denominator of GDP per capita can fall such that the net effect on the entire ratio is a wash or even increase. In fact, aggregate real output can still continue to grow *if* labor productivity rises faster than the rate of employment decline.

But this is a big if. After all, some of the thrust of endogenous growth theory emphasizes that population growth corresponds to more human brains, which results in more innovation when those brains engage with economic problems. Therefore, in the long run, smaller populations innovate more slowly than larger populations. Furthermore, given that information can cross borders relatively easily no one on the globe is insulated from the effects of lower global population. Because information crosses borders relatively well, the brains-to-riches model doesn’t tell us who will innovate more or experience greater productivity growth.

What follows is not the only answer. There are certainly multiple. For example, recent Nobel Prize winner Joel Mokyr says that both basic science *and* knowledge about applications must grow together. That’s not the route that I’ll elaborate.

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How to Make a Few Billion Dollars

The title is excellent, given that the author Brad Jacobs did in fact make a few billion dollars.

The book itself is fine to read, but also fine to skip if you aren’t yourself burning to build a billion dollar company through excellent management and mergers and acquisitions. I certainly don’t care to, which Jacobs says would make me a bad hire for one of his companies:

I only hire people who are motivated to make a lot of money…. If an candidate says to me ‘I’m not motivated by money’, I suspect either they’re not being candid or they lack the hunger that’s necessary to succeed

The book has plenty of hard-driving sentiments like this that you’d expect from a self-made billionaire:

Fire C players

For the first time ever, an American company, Exxon, had reported quarterly earnings in excess of $1 billion. The words “obscene profits” flashed on my TV screen, and I remember thinking “That sounds pretty good! Maybe I ought to check out the oil sector.” [This part I agree with, economic theory predicts that entrepreneurs will enter the sectors with the highest profits and its what I’d do if I wanted to make money, though in practice I think it is surprisingly rare for would-be entrepreneurs to choose this way -JB]

“The CEO trait most closely correlated with organizational success is high IQ” [specifically more important than EQ]

But Jacobs balances these ideas with some surprisingly hippy-like attitudes. Jacobs went to Bennington College and almost had a career as a jazz keyboardist. Chapter 1 is titled “How to Rearrange Your Brain”, and emphasizes the importance of meditation. Page 21 is basically “have you ever really looked at your hands, man… do it, it’s a trip”

I don’t want to spend even one hour around people who are unkind. An organization is like a party. You only want to invite people who bring the vibe up

Though perhaps this hippy/anti-hippy balance shouldn’t be surprising for someone who says one of the main things he asks about potential hires is “can this person think dialectically”.

Strongly recommend the book if you want to follow Jacobs’ path; weakly recommend it as a general management/self-help book or way to learn about markets.

Rising Chinese Zombie Firms

Have you ever looked up and wondered where the time went? One moment you’re living your life, and the next moment you realize that you’ve just lost time that you’ll never get back? That’s what happened to Japan’s economy at the turn of the century in an episode that’s known as ‘the lost decades’. It was a period of slow or null economic growth. Economists differ with their explanations. One cause was the prevalence of ‘zombie firms’.

Japan’s Economy

Japan had a current account surplus from 1980-2020, which means that they had more savings than they effectively utilized domestically. Metaphorically, they were so full of savings that they exhausted productive domestic investment opportunities and their savings spilled out into other counties in the form of foreign investments. This was driven by high household savings and slow growth in domestic investment demand. The result was the Japanese firms had easy access to credit. Maybe a little too easy…

Private corporate debt ballooned throughout the 1980s. That’s not intrinsically a problem. In the 1990s, households began saving somewhat less, and most firms began to drastically deleverage… But not all firms. The net effect of the mass deleveraging was that interest rates fell.  The firms that remained in debt were the ones that risked insolvency. Less productive firms had slim profits and their Earnings Before Interest, Taxes, Depreciation, and amortization (EBITDA) was slim. So slim, that they couldn’t pay their debts. Faced with the prospect of insolvency, firms did what was sensible. They refinanced at the lower interest rates. Firms went to their banks and to bond markets and rolled over their debt, which they couldn’t afford, and replaced it with debt that had a lower interest rate. This occurred across industries, but especially in non-tradable goods and services that were insulated from international competition. Crisis averted.

Except this process of refinancing, while avoiding acute defaults and a potential financial crises, ensured that the less productive firms would survive. Not exactly failing and not exactly thriving, they could sort of just hold on to something that looks like life. Well, high debt and low profits aren’t much of a life for a firm. It’s more like being undead – like a zombie. Between 1991 and 1996, the share of non-finance firm assets held by zombie firms ballooned from 3% to 16%. The run-up differed by industry: Manufacturing zombie assets rose from 2% to 12%, from 5% to 33% in real estate, and from 11% to 39% in services.  These zombie firms linger on, tying up valuable resources with low-productivity activities and drag on the economy.

China’s Economy

I’m not prone to China hysteria generally. However, I do have uncertainty about the plans and actions of the Chinese government because I don’t know that domestic economic welfare is its priority. That makes forecasting more political and less economic and outside my expertise. Regardless, the Chinese economy is a constraint on the government, whether they like it or not.  And there are some echoes of the Japanese economy’s lost decades.

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Tariffs Are Not Smart Industrial Policy

Economists overwhelmingly see tariffs as clearly welfare-reducing. Tariffs on imports result in higher prices, fewer imports, less consumption, and more domestic production. In fact, it is the higher prices that solicit and make profitable the greater domestic production. We don’t get the greater domestic output at the pre-tariff price. We can show graphically that domestic welfare is harmed with either export or import tariffs. The basic economics are very clear.

However, the standard model of international trade makes a huge assumption: Peace. That is, the model assumes that there are secure property rights and no threats of violence. All transactions are consensual. This is where the political scientists, who often don’t understand the model in the first place, say ‘Ah ha!. Silly economists…’ They proceed to argue for tariffs on the grounds of national security and the need for emergency manufacturing capacity. But is an intellectual mistake.  

Just as economists have a good idea for how to increase welfare with exchange, we also have good ideas about how to achieve greater or fewer quantities transacted in particular markets. This is not a case of economists knowing the ideal answer that happens to be politically impossible.  Rather, if it pleases politicians, economists can provide a whole menu of methods to increase US manufacturing, vaccine manufacturing, weapons manufacturing… Heck, we can identify multiple ways to achieve more of just about any good or service. Let the politicians choose from the menu of alternatives.

The problem with tariffs is that they reduce consumer welfare a lot, given some amount of increased production in the protected industry. Importantly, this assumes that the tariffs aren’t hitting inputs to those industries and are only being applied to direct foreign competitors. The below argument is even stronger against imperfectly applied tariffs, like the US tariffs of 2025.

What’s the alternative?

The alternative is a more focused tack. If the government wants more missile or ship production, then what should it do? There’s plenty, but here’s a short list of more effective and less harmful alternatives to tariffs:

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Structure Integrated Panels (SIP): The Latest, Greatest (?) Home Construction Method

Last week I drove an hour south to help an acquaintance with constructing his retirement home. I answered a group email request, looking for help in putting up a wall in this house.
I assumed this was a conventional stick-built construction, so I envisioned constructing a studded wall out of two by fours and two by sixes whilst lying flat on the ground, and then needing four or five guys to swing this wall up to a vertical position, like an old-fashioned barn raising.

But that wasn’t it at all. This house was being built from Structure Integrated Panels (SIP). These panels have a styrofoam core, around 5 inches thick, with a facing on each side of thin oriented strandboard (OSB). (OSB is a kind of cheapo plywood).


The edges have a sort of tongue and groove configuration, so they mesh together. Each of the SIP panels was about 9 feet high and between 2 feet and 8 feet long. Two strong guys could manhandle a panel into position. Along the edge of the floor, 2×6’s had been mounted to guide the positioning of the bottom of each wall panel.


We put glue and sealing caulk on the edges to stick them together, and drove 7-inch-long screws through the edges after they were in place, and also a series of  nails through the OSB edges into the 2×6’s at the bottom. Pneumatic nail guns give such a satisfying “thunk” with each trigger pull, you feel quite empowered. Here are a couple photos from that day:


The homeowner told me that he learned about SIP construction from an exhibit in Washington, DC that he attended with his grandson. The exhibit was on building techniques through the ages, starting with mud huts, and ending with SIP as the latest technique. That inspired him.

(As an old guy, I was not of much use lifting the panels. I did drive in some nails and screws. I was not initially aware of the glue/caulk along the edges, so I spent my first 20 minutes on the job wiping off the sticky goo I got all over my gloves and coat when I grabbed my first panel. My chief contribution that day was to keep a guy from toppling backwards off a stepladder who was lifting a heavy panel beam overhead).

We amateurs were pretty slow, but I could see that a practiced crew could go slap slap slap and erect all the exterior walls of a medium sized single-story house in a day or two, without needing advanced carpentry skills. Those walls would come complete with insulation. They would still need weatherproof exterior siding (e.g. vinyl or faux stone) on the outside, and sheetrock on the inside. Holes were pre-drilled in the Styrofoam for running the electrical wiring up through the SIPs.

From my limited reading, it seems that the biggest single advantage of SIP construction is quick on-site assembly. It is ideal for situations where you only have a limited time window for construction, or in an isolated or affluent area where site labor is very expensive and hard to obtain (e.g., a ski resort town). Reportedly, SIP buildings are mechanically stronger than stick-built, handy in case of earthquakes or hurricanes. Also, an SIP wall has very high insulation value, and the construction method is practically airtight.

SIP construction is not cheaper than stick built. It’s around 10% more expensive. You need perfect communication with the manufacturer of the SIP panels; if the delivered panels don’t fit properly on-site, you are hosed. Also, it is tough to modify an SIP house once it is built.

Because it is so airtight, it requires some finesse in designing the HVAC system. You need to be very careful protecting it from the walls from moisture, both inside and out, since the SIP panels can lose strength if they get wet. For that reason, some folks prefer to not use SIP for roofs, but only for walls and first-story flooring.
For more on SIP pros and cons, see here and here.

Fresh observations of Americans working hard

It has been over 100 years since GK Chesterton visited America. I wrote about his observations on the American “enthusiasm for work” for Liberty Fund.

Henry Oliver commented on much the same thing this week in The American art of being busy.

The whole place was as busy as a hive. It went on and on. Everyone was cheerful. No-one fussed and bothered.

And what of the Americans who are not allowed to work because of the government shutdown? Here is a guy who has rapidly found a way to work in DC again and seems “cheerful”: This furloughed IRS lawyer is living out his dream of being a hot dog vendor

This restlessness and energy likely has something to do with us being currently in the lead for the race to AI. Ho hum… building God while still having the equivalent of the GDP of a small country to drop on Halloween trinkets.

Joy on the Anthropic Copyright Settlement

I’m at Econlog this week with:

The Anthropic Settlement: A $1.5 Billion Precedent for AI and Copyright

There are two main questions. Will AI companies need to pay compensation to authors they are currently training off of? Secondly, how important is it for human writing to be a paying career in the future, if AI continues to need good new material to train from?

There is more at the link but here are some quotes:

If human writing ceases to be a viable career due to inadequate compensation, will LLMs lose access to fresh, high-quality training data? Could this create a feedback loop where AI models, trained on degraded outputs, stagnate?

This case also blurs the traditional divide between copyright and patents. Copyrighted material, once seen as static, now drives “follow-on” innovation derived from the original work. That is, the copyright protection in this case affects AI-content influenced by the copyrighted material in a way that previously applied to new technology that built on patented technical inventions. Thus, “access versus incentives” theory applies to copyright as much as it used to apply to patents. The Anthropic settlement signals that intellectual property law, lagging behind AI’s rapid evolution, must adapt.