For decades, almost no one did that better or more consistently that Charlie and Warren Buffett. But when Munger gave Greg Abel his highest praise—calling him a "tremendous learning machine" who is "as good at some things as Warren is, and better at some things"—he signaled something profound about Berkshire Hathaway’s succession plan.
Of course Abel is smart and hard-working—but then, Berkshire has hundreds if not thousands of people richly possessed of those qualities. I think the thing that separated him from everyone else in the conglomerate is his distinct kind of cognitive capacity—he’s an unparalleled learning machine.
If Buffett’s learning engine is optimized for Capital Allocation, Abel’s is engineered for Operational Complexity. Understanding the distinction between these two modes reveals not only why Berkshire’s moat remains intact, but how functional, multi-domain learning actually works in practice.
Capital Allocation Learning vs. Operational Learning
CrossFit's definition of physical fitness through broad modal domain capacity is useful—the truly fit person has the ability to perform well across any task, known or unknown. Munger applied that exact ethos to worldly wisdom: building a lattice of mental models to navigate market complexity.
However, the inputs, feedback loops, and risks of learning change dramatically depending on where you operate in the corporate ecosystem.
Capital allocation learning—the discipline honed by Buffett—operates at a high level of abstraction. Its inputs are annual reports, financial statements, and historical data, consumed via broad, passive observation. Because capital allocation is judged by long-term returns, its feedback loops are notoriously delayed; years or even decades can pass between deploying capital and discovering if the thesis was sound. The primary risk here isn't operational mistake, but narrative bias—miscalculating intrinsic value or overestimating the durability of a business moat.
Operational learning, by contrast, is engineered for deep structural integration. Its inputs are non-abstract and messy: complex supply chain bottlenecks, regulatory filings, labor contracts, and capital expenditure models. Because an operational learner like Abel deals with real-world infrastructure—grid reliability, margin compression, and throughput efficiency—the feedback loops arrive far faster. Consequently, the primary risks shift from narrative errors to concrete ones: operational drift, regulatory friction, and execution bottlenecks that quietly bleed capital.
The Architecture of Abel's Engine
I’m not sure new Berkshire Hathaway Chairman Howard Buffett ever called his dad a book with legs the way Charlie Munger’s kids did to him, but if he did, it would be justified. Buffett famously spent 80% of his day sitting in a room reading balance sheets, acting as an intellectual filtering mechanism for capital deployment. Abel's background—rising through MidAmerican Energy and eventually overseeing all of Berkshire’s non-insurance subsidiaries—required a rather different deployment of his skills and abilities as a "learning machine".
Abel’s cognitive engine operates through three key mechanisms:
1. Micro-Mechanics Over Macro-Abstraction
A capital allocator can look at a utility company through a discounted cash flow lens and evaluate its moat based on regulatory return-on-equity caps. An operational learner like Abel must understand why those regulatory caps exist, the exact capital cost of grid modernization, the supply chain lead times for high-voltage transformers, and how local political dynamics impact rate-case approvals. It is learning driven by first-principles mechanics rather than top-down financial theory.
2. Cross-Domain Transferability
Managing dozens of decentralized businesses—ranging from BNSF Railway to Precision Castparts and Berkshire Hathaway Energy—demands a supple, acute mental agility. Abel didn't, obviously, need to run every company, but he did have to learn the key leverage points of completely disparate industries nearly as well and likely even faster than the specialists running them. How is this possible? Being a learning machine with a mind stocked with Charlie Munger’s "Lattice of Mental Models". That’s what lets Abel transfer operational lessons from freight rail scheduling directly into energy grid load balancing.
3. High-Bandwidth Pattern Recognition
When Munger noted that Abel is "better at some things" than Warren, he may have been pointing to Abel's hands-on grip on operational friction. Buffett deliberately avoided managing people or operations, preferring a completely clean slate. Abel, by contrast, built his learning capacity by engaging directly with complex, real-world systems under real-world constraints—learning how complex systems break and where efficiency leaks out.
The Moat is the Learning Rate
Most people think that the key to Berkshire Hathaway’s success began and ended with the unique, unrepeatable genius of two legendary stock-pickers. It’s certainly what made the company’s completely unprecedented and wholly unrepeatable cult following and Woodstock-like annual meetings work. (I promise it wasn’t Omaha, as nice as that city is). With Abel having run the corporation’s day-to-day operations for nearly a year now, it’s become clear that Berkshire's real advantage isn't a stock-picking strategy—it’s an institutional system that prizes and rewards adaptive learning.
Whether applied to reading financial reports at a quiet desk in Omaha or untangling a multi-billion-dollar energy infrastructure pipeline, the underlying principle remains unchanged: The entities that outrun the field are the ones built to learn faster, adapt deeper, and compound knowledge relentlessly.
One Big Question: Can he Wait for the Fat Pitch
For all of Abel’s proven intellectual power, a critical question regarding his transition to being what George W. Bush called ‘The Decider’: can he be patient enough? Will Abel be able to match Buffett’s legendary ability to be comfortable sitting and doing nothing (when there are no good opportunities)?
Buffett famously drew on Ted Williams’ The Science of Hitting to articulate his investing strategy. Williams had an incredibly simple hitting philosophy that he *never* deviated from: Get a good pitch to hit. Williams knew success in the batter’s box came from waiting exclusively for pitches in the heart of the strike zone. Buffett latched onto this philosophy in the arena of investing—he was every bit as scrupulous as Williams was in taking swings only at "fat” pitches.
Of course, in this, Buffett and Munger had a massive advantage: investing money and allocating capital doesn’t require you to take any more swings that you’re comfortable with. Three strikes in any given at-bat and Williams would have to trot back to the dugout a failure (however temporary). He didn’t have the luxury of waiting for truly fat pitches. But there are no called strikes in capital allocation[1]. You can watch thousands of ‘pitches’ go by until the perfect opportunity arrives. Williams’ legendary discipline produced a .482 career on-base percentage, the highest in Major League Baseball history. Buffett built Berkshire by applying that exact discipline to capital.
What Kind of Engine: Williams vs DiMaggio
Abel is unquestionably brilliant. What remains to be seen is he’s more like Ted Williams or Joe DiMaggio. DiMaggio was a sublime hitter—one of only a handful of players to play a MLB season the same year as Ted Williams and finish with a higher batting average that season more than once (excepting Williams’s single poor season in his age-40 year in 1959, the following players had higher batting averages higher than Williams over a full season more than once: Stan Musial, 1946, 1948, 1950, 1951, 1958, and 1959; Willie Mays, 1954, 1958, 1960; George Kell, 1949, 1950, 1951, Richie Ashburn, 1951, 1958; and Jackie Robinson, 1950, 1951 are the only players on that exclusive list) 19. DiMaggio did it twice officially, in Williams’s first two seasons and once unofficially in 1949, when he didn’t qualify for season award due to times missed to injury but hit .346 vs Williams’s .343 to lead the Yankees to the pennant over Williams’s Red Sox. Williams had to settle for the MVP and Sporting News’s MLB Player of the Year individual awards.
If Berkshire is getting either Ted Williams or Joe DiMaggio, it’ll continue to do fine. After all, Joe D and his iconic 56-game hitting streak is not only one of the most unbreakable records in sports, it also led to him being immortalized in song—famously in Paul Simon’s lyric “the nation turns her lonely eyes to you”. As good as he was—he hit 361 career home runs and struck out an incredible 369 times, the .978 home run to strikeout ratio is by far the best in MLB history for anyone who hit at least 300 home runs (Williams is 8th on that list at .735), his offensive production is dwarfed by Williams’s. Despite being nearly Williams’s equal as a hitter—in addition to the paltry strikeout total, DiMaggio’s career batting average was .325, fewer than 20 points lower than Williams’s—the Yankee great was a far lesser offensive engine than his Red Sox counterpart because of his relative inability to get on base without making contact with the ball. DiMaggio’s on-base percentage was ‘only’ .398 compared to Williams’s MLB best .482. Obviously, a 20+ percent differential in success rate is nothing to sneeze at in investing or baseball. Over the course of a season, if a player had 600 plate appearances, Williams’s on-base percentage would yield 50! extra times on base. The main attribute that separated DiMaggio from Williams as an offensive player was patience—an obsessive refusal to swing at pitches outside his personal sweet spot.
Investor Michael Burry sees more DiMaggio than Williams in Abel. Earlier this year, he tweeted, “My biggest fear for Berkshire Hathaway was that when Warren finally stepped down, the successor would be too old and otherwise not Warren, so would not have his patience for the fat pitch.” Even more critically, he noted that he did “not find Berkshire an attractive investment going forward.”
Assessing a Learning Machine: Experience & Disposition
What to make of Burry’s critique? It’s too early to tell. Abel’s track record has been impressive. But there is at least a kernel of truth to Burry’s concern that merits consideration. Abel was in operations—he spent decades fixing problems, optimizing systems, and actively driving throughput. For anyone with this kind of experience, sitting on a quarter-trillion-dollar cash pile in an ebullient market demands an entirely different kind of discipline.
Operational minds are wired to act, to optimize, to solve. Capital allocation often demands the exact opposite: radical, uncomfortable inaction. It’s understandable that DiMaggio would be taken by the adulation that accompanied getting a hit in (far) more consecutive games than any other MLB player had. Hitters have a natural bias toward action. Even Williams expressed frustration at pitchers pitching around him and not giving him opportunities to swing the bat. He once said, “The most fun I ever had in my life was hitting a baseball. And the best sound I ever heard in my life was a ball hit with a bat.” Despite his natural inclination—and the heavy criticism he got from writers and fans for not swinging more—to hit the ball hard, his incredible discipline allowed him to lay off pitches he didn’t like.
Buffett no doubt admired Williams for being able to tune out exterior noise. Williams took heat like Boston sportswriter Dave Egan’s complaint that Williams refused to protect his teammates by swinging at pitches even slightly outside his ideal zone, writing, "He is a selfish hitter... Williams would rather take a walk with the bases loaded in the ninth inning than swing at a pitch two inches off the plate to hit a sacrifice fly or a game-winning single." Egan argued that Williams' obsessive refusal to swing unless a pitch was dead-center in his sweet spot hurt the team, calling Williams "the prime minister of self-preservation".
Famous managers and players frequently contrasted Williams' refusal to swing with Joe DiMaggio's willingness to go after anything reachable, often in unfavorable terms. Williams’s own teammate Vern Stephens noted, "Ted won't swing at a bad ball to save his own mother. He'll take the walk and leave it to the next guy.”
Catches and later MLB manager Birdie Tebbetts summed up the fundamental difference between Williams and other legends: "DiMaggio believed that if he could reach a pitch, he was supposed to hit it—no matter where it was. Williams believed if it wasn't a strike, he had no business swinging at it. Pitchers hated DiMaggio, but they respected Ted's eyes because he'd just leave the bat on his shoulder."
While we won’t know how Abel will react to public criticism or how his long-term approach will be similar or different than Buffett’s, Michael Burry was not impressed with the early returns. Burry was critical of Berkshire's and Abel’s capital deployments, writing, "My biggest fear for Berkshire Hathaway was that when Warren finally stepped down, the successor would be too old and otherwise not Warren, so would not have his patience for the fat pitch. I believe this fear has come true. I do not find Berkshire an attractive investment going forward."
Whether Burry’s indictment proves premature or prophetic, it highlights the fundamental fork in the road for Abel. Learning how a business works is an operational skill; learning when not to buy it is a psychological discipline. Abel has proved beyond doubt that he is a master learner of systems. The ultimate test of his legacy may be whether he has learned the single most difficult lesson in finance: how to keep his bat on his shoulder until the fat pitch arrives.
[1] Interestingly, the few blemishes against Williams’s case as baseball’s greatest
hitter are instructive to Buffett’s, Munger’s and Abel’s investing practice. Those
who conclude Williams wasn’t as great as his numbers suggest cite 1) his lack
of quality competition—he played most of his career in a mostly segregated
league; 2) that he faced pitchers who didn’t have screwballs and other
difficult pitches in their repertoires; 3) that he faced the same stock of
pitchers too frequently—with only a few teams, he saw the same guys over and
over and 3a) faced the same pitchers more times in each game—including late in
the contest then he’d seen their best stuff and they’d gotten tired; 4) that he
didn’t have to face many lefties; 5) that he didn’t have to play many night
games.
For Buffett & Munger, none of these are problems. Any sector they don’t
fully understand gets put in the ‘Too Hard’ pile. Williams made a living
hitting some of the greatest power pitchers in the game—his numbers against Bob
Feller—the pitcher Williams said was the best he ever faced, so
good that Williams started preparing to face him three days in advance!—for
example, are: .344 batting average, .474 on-base percentage, .675 slugging
percentage, and 1.149 on-base plus slugging percentage (OPS). The batting
average against Feller is his exact career batting average against the rest of
the league. His on-base percentage against Feller is lower than William’s
career mark, but is equal to Babe Ruth’s, and better than any other MLB player
in history. And Williams’s slugging percentage against Feller sits almost
exactly halfway between Williams’s and Ruth’s career marks—and is better than every
other MLB player’s ever.
