We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.
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But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.
Here are the articles for the week ending 21 June 2026:
1. Tenneco Automotive: Charlie Munger’s $80 Million Bargain, Part 1 – Tim Isgro
The story of Charlie Munger’s investment in Tenneco Automotive is a fascinating one. And as far as I can tell, it’s only been told in a cursory way before now.
Munger made the investment in 2001 and it likely returned to him somewhere between 4 1/2 to 7 times his money and an annualized return over three years of 65% to 93%…
…What remained at the end was Tenneco’s automotive business, which sold emissions products (exhaust systems) and ride control products (like shocks and struts). It was this business, Tenneco Automotive Inc., that Munger was considering in 2001.
To say the above series of transactions dramatically changed the nature of Tenneco’s business is an understatement. The company went from being a large, diversified conglomerate with $13.2 billion in revenue in 1993 to a smaller single-line automotive businesses with just $3.5 billion in revenue in 2000…
…After all these spinoff transactions were finished, Tenneco was left with approximately $1.5 billion of long-term debt. After reading the history of Tenneco above, I suspect the automotive business was a victim of circumstance with respect to its debt load, being the last business standing after management spun off or sold five others…
…Focus for a moment on the company’s Operating Income (EBIT) and Interest Expense. Prior to the spinoff of Pactiv, the company was doing well, earning $633mn in EBIT in 1998 and spending $240mn in interest payments, but after the spinoff, the company was earning only $115mn in EBIT and spending $186mn in interest payments…
…To add insult to injury, Tenneco’s revenues were also suffering from the 2001 recession.
Tenneco served two broad sets of customers, original equipment manufacturers (auto makers) and the aftermarket (auto repair shops). Both were suffering lower sales…
…Not only were the interest payments on Tenneco’s debt too much for the company to handle in the years after completing its spinoff, but, on top of that, principal payments were starting to come due in 2001. The annual report from 2000 lists those upcoming maturities as $54 million, $109 million, and $99 million for 2001, 2002, and 2003, respectively. From the perspective of a casual analyst or observer, it was not clear at all how Tenneco could make those payments or how likely they were to work with their lenders on renegotiating terms.
2. Tenneco Automotive: Charlie Munger’s $80 Million Bargain, Part 2 – Tim Isgro
Tenneco produced auto products in two business segments: Emission Control and Ride Control. In both of those business segments, it had brand names with an excellent reputation and market share…
…Moreover, Tenneco’s list of original equipment manufacturers was large, including just about every major auto maker in the world. And the largest automaker (GM) accounted for only 16.6% of the company’s sales, indicating the sales were nicely diversified…
…Munger understood the great reputation of Tenneco’s products, as indicated by his brief comments at the Daily Journal meeting, when he stated:
I kind of knew based on experience how sticky some of that auto secondary market was, and how many old cars needed Monroe shock absorbers.
I think this point is critical to understanding Munger’s willingness to purchase these securities. Since customers loved and needed Tenneco’s products, the company still had fundamental value as an ongoing concern…
… Importantly, and perhaps underappreciated by the market, Tenneco was still in the midst of a major transition in its business. It had gone through five major spinoffs or sales of business units since 1993, it was facing its first recession since that time, and it was coping with all the debt it was saddled with after those spinoffs.
But digging in a bit to the company’s annual and quarterly reports makes it clear that management was keenly focused on right-sizing company expenses and running a more efficient organization…
…So, as of the end of 2000, management expected to generate a total of $92 million of savings by right-sizing its workforce and by adopting more efficient processes and practices.
In fact, it was already becoming evident by Q3 of 2001 that those efforts were working better than expected. Figure 10 below (which is Figure 8 reproduced) shows annualized operating costs (plus DD&A) that were $104mn lower than those for the year 2000. And those lower operating costs boosted EBIT by 32% to $152mn…
…I think these positive points are ultimately what caused Munger to believe that the company’s bonds, around a price of 35, and the company’s stock, around a price of $1.55 per share and a market cap of only $59mn, were way too cheap. For reference, the entire enterprise value of the company was $1.1bn, a figure I arrive at by conservatively assuming that the company’s debt is valued at par (apart from the 11 5/8% bonds, which I value at 35 cents).
I think Munger saw a very difficult financial situation for the company, and he probably acknowledged that a further, prolonged downturn in the economy and/or a group of unfriendly bank lenders could have pushed the company into bankruptcy. And in bankruptcy, in the wrong economic environment, it was quite possible that his debt and equity got wiped out.
The fact that Munger did not invest fully in Tenneco’s equity, which was more likely to be wiped out in bankruptcy, and chose to split his investment between bonds and equity, shows that he realized this was a possibility…
…I think Munger likely reasoned about how a potential bankruptcy might play out, and I think this was the most important point of all, prompting him to make his investment.
If Tenneco was forced into bankruptcy, its lenders would then have to decide on the best course of action that might get them a full recovery on their lending amounts. The total amount of long-term debt outstanding was $989mn plus the $500mn of subordinate bonds which Munger would invest in.
Tenneco’s lenders would rightly ask themselves: How are we best off to recover our $989mn?
1. We could force a liquidation of the business and attempt to be paid in full. That would involve a few years of wind-down work, staggered employee layoffs and plant and equipment sales, along with the severance and interim operating costs that come along with it. Plus, we would also need to engage in a process to sell the valuable Walker and Monroe brands, two of the most valuable assets the company had.
Or…
2. We could effectively realize the value of those brands by recapitalizing the company and operating as usual. One way to do that might be to forgive Tenneco’s debt completely, take an equity stake in the new company without debt, and then sell the equity in the new company to make ourselves whole on the lending amounts…
…We also know that Munger made “$80mn” on the investment. But we don’t know specifically how much he invested in either of the securities…
…Assuming Munger invested somewhere between 25% and 75% in Tenneco’s bonds (and stock), he likely made anywhere from 4.5 times to 7.2 times on his investment in three years, from December 2001 to the time the bonds were called in December 2004 (and when he likely sold his stock as well). Those returns imply an annualized return of 65% to 93%…
…I think there is one clear takeaway from Munger’s Tenneco investment.
When you encounter a company with a quality, in-demand product and/or a great brand, and that company is suffering, look twice.
3. Systems of Record Won the SaaS Era – Clearinghouses Will Win the Agents Era – Jamin Ball
In financial markets, the clearinghouse sits between different parties that aren’t able to fully trust each other. The clearinghouse verifies / authorizes / settles trades, and ultimately keeps the receipt. Nobody really loves the clearinghouse, but it’s clear it has to exist for the ecosystem to transact.
Now think about where enterprise software is heading. Agents from tons of different vendors, acting autonomously, touching your most critical data, and even in the future spending real money. Some company has to sit in the middle of all that and decide: which agent is cleared to act? On what data? With what limits? And can you prove what happened after the fact? Whoever holds that seat holds incredibly “strategic real estate.” (and every founder I’ve worked with has probably heard me discuss strategic real estate over and over). That’s the clearinghouse.
This may sound counterintuitive, but owning the clearinghouse for agents (given agent companies themselves will want to be the clearinghouse) may create a deeper moat than the one systems of record had. A system of record controlled your data. It kind of controlled your workflows (but not always, oftentimes someone else controlled the workflows, but the data in the system of record was a critical part of the path). The Clearinghouse controls four things: memory (what your agents know), context (what they see and how it’s served), execution (what they’re allowed to do), and governance (who’s allowed to do what, plus the audit trail behind all of it). If migrating off a system of record was painful, migrating off the thing that holds your policies, your permissions, and your entire audit history is probably harder (especially when the agents start to handle more and more of the work). AND – I think these agent companies that become The Clearinghouse will start to look more and more like systems of record in their own right. Data in systems of record were oftentimes transactional data. Data in agent systems of records (ie Clearinghouses) will be agent traces, agent evals, agent telemetry data, agent A/B data, etc
4. Automation’s Asymptote: Part 2 – Abdullah Al-Rezwan
Tom Reed wrote a very good piece last month arguing that we may be pursuing what he calls “Goodhart Singularity”. Reed’s counter to automation doom is disarmingly simple: you cannot get good at solving problems without access to a source of problems, and the only source of most problems is slow, expensive interaction with the real world. Without that contact, the recursive loop produces something far less impressive than advertised. From Reed’s piece:
“The output of the R&D produced by an isolated datacenter of geniuses would be a mere Goodhart Singularity.4 An isolated AI improving itself against benchmarks would only appear to be approaching superintelligence, while actually optimising for eval performance that fails to generalise beyond the lab.”
Why would self-improvement stall outside the lab? Because models get good at what they practice, and for most economically valuable work, there is nothing to practice on. Reed’s most clarifying observation is about what kind of data exists at all:
“For most tasks in the economy, the pretraining corpus contains writing about the task, but not a record of the task itself. This is of course one of many reasons coding has progressed faster than other domains – code is one of the neat cases for which the task itself is almost entirely reducible to its token trace.”
The internet contains commentary and advice in abundance, but the actual steps of closing an M&A deal or deciding which drone prototype to ship were never serialized into tokens. The natural rebuttal is that a sufficiently smart system can simulate whatever data it lacks. Reed is skeptical that simulation is a viable path:
“Consider that almost half of SWE-Bench submissions accepted by AI auto-graders would be rejected by the actual human maintainers of the relevant repositories. The fact that you can pump SWE-bench scores without increasing actual merge rates is, to me, suggestive of the situation the datacenter-genius will find itself in.
The great Zhengdong makes this point about the progress of AI research itself. Not only are “evals” the only things that models are capable of getting good at, but “the researchers [themselves], they just wanna optimise… they just want an important problem to solve, a clear evaluation that measures progress towards it, and then they just wanna optimise it.” I suggest that AI companies need real-world deployment as a source of problems, or else they will have no good targets for optimisation.”
5. Mao’s economic record wasn’t bad, actually – Arnaud Bertrand
One number for you: under Mao, China’s GDP PPP per capita (meaning per person) was multiplied by about 2.5x from just above $400 in the early 1950s to nearly $1,000 in 1978. These figures aren’t from a “communist source”, they’re taken straight from a report by the Congressional Research Service, the research arm of the U.S. Congress…
…This is confirmed in another report by the extremely serious National Bureau of Economic Research (NBER), one of the most prestigious economic research institutions in the U.S., who found in a report entitled “The Economy of People’s Republic of China from 1953” that “the Chinese economy in 1952-1978 grew rather rapidly” with an average annual growth rate of real GDP of 6%. This equates to the overall Chinese economy being multiplied by 5 over the Mao era, which is consistent with China’s GDP per capita nearly tripling since the Chinese population simultaneously increased by 75% during the period (5 divided by 1.75 equals 2.85)…
…The data is overall clear: during the Mao era, China outperformed both its most comparable peers. It grew roughly 25% faster annually than India (5-6.7% vs ~4%) and modestly faster than Indonesia (5-6.7% vs 4.8-4.9%). Which means that whatever criticisms one might make of Mao’s policies, the prevalent Western narrative that he presided over an “economic catastrophe” is demonstrably false. The reality, confirmed by American research institutions, international databases, and comparative studies alike, is that Mao presided over significant economic expansion that exceeded comparable peer nations.
Sure, it wasn’t all plain-sailing, to say the least. For instance during the Great Leap Forward, according to the Penn World Table data, China’s GDP contracted by 20.8% from its 1959 peak to the 1962 trough – a severe three-year recession that took until 1965 to fully recover from. Similarly, at the beginning of the Cultural Revolution, GDP contracted by 5.9% from 1966 to 1968, with back-to-back annual declines of 3.3% and 2.7% before rebounding strongly with 9.9% growth in 1969…
…We shouldn’t dismiss the human toll that the Great Leap Forward inflicted. It remains the most severe policy failures in modern Chinese history, causing genuine excess mortality and widespread suffering. But we shouldn’t exaggerate the catastrophe either: probably the best way to assess mortality rates during the Great Leap Forward is to look at population numbers and reconcile them with birth rate data (which dropped from 37 per thousand in 1959 to just 21 per thousand in 1960…
…But let’s be clear though: the Great Leap Forward was a largely man-made economic catastrophe stemming from disastrous policies that backfired spectacularly. Mao didn’t intend to cause a famine, but his policies – including unrealistic production quotas and the diversion of agricultural labor to backyard steel furnaces – undoubtedly did. He himself acknowledged some responsibility for the disaster, as did the Party officially, with Liu Shaoqi (then Chairman of the PRC) stating at the Seven Thousand Cadres Conference in 1962 that the famine was attributed to “thirty percent natural disasters, seventy percent man-made problems.”…
…Overall, China’s GDP nearly doubled over the entire 10-year period of the Cultural Revolution and the 1969-1975 period at 6.86% annual growth was the fastest sustained growth period during the Mao years, even exceeding the celebrated First Five-Year Plan period (6.53% average annual growth). This really goes against the widespread perception that the Cultural Revolution was an economic disaster comparable to the Great Leap Forward: not only it wasn’t, but China’s economy was actually booming during the period!…
…This is what resolves an oft-discussed paradox (discussed, for instance, by Branko Milanovic here): How could a “thoroughly inefficient system” create the basis for explosive subsequent growth? The answer is that the Mao era, despite its inefficiencies and disasters, created specific tangible foundations – human capital, physical infrastructure, industrial capacity, organizational systems, and transformed property relations – that made the reform era’s success possible.
You couldn’t have had the TVE explosion without the organizational legacy of communes. You couldn’t have absorbed foreign technology without an educated workforce. You couldn’t have rapidly expanded manufacturing without existing industrial infrastructure and millions of workers with basic industrial skills. You couldn’t have sustained 10% growth rates for three decades without the healthcare improvements that gave China a healthy, productive workforce.
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