Arthur Patterson's Riddle
or: How I Learned to Stop Worrying and Love the Ride
This week, we’re talking:
Arthur Patterson may not be a toll-collecting troll beneath a fairytale bridge but should his storied investment career take a turn, he has enough riddles to take the gig — let’s try to solve one, shall we? 🧌❓🤔
Generative AI is growing but the quality is disintegrating 📈📉
Can the media survive or is this its slow, painful death march? 📺 📰 ☠️
$2 million later, the largest prime number has been found 🔍 🔢
Like it or not, science is political 🥽🧪🔬=🏛️
My Take:
I’ve heard the partners of Arthur Patterson, the Co-Founder of Accel, teasingly refer to him as “The Riddler,” and with good reason. He’s quick with pithy, slightly puzzling pronouncements that call for quiet contemplation if you want to get his point. I remember one particularly intriguing piece of advice he shared during the exit of my first company: “Here’s the thing,” he mused. “You’re no smarter the day after you sell your company or go public than you were the day before. It’s just that everyone thinks you are.”
If you’re an entrepreneur with an exit, is Arthur’s riddle telling you not to get too big for your britches amid the high fives? Or is it saying that entrepreneurs with exits get too much credit, while those without get too little—perhaps because they’re just less lucky?
Virtuosity in most jobs is about improving your hit rate until you’re impeccable—and everyone can see it. Stephen Curry improves his 3-point average to levels never seen before; just watch him play. My favorite jazz guitarist, Pat Metheny, delivers musical phrases that float like leaf petals during his solos; just listen to him live. World-class engineers write elegant, efficient code to solve ever harder problems with fewer bugs; their software either works or it doesn’t.
But company-building isn’t like that. If entrepreneurship were surgery, you could become world-renowned for only killing 70% of your patients. It’s rational for investors and employees to wonder whether your cockamamie project will ever work as they watch patients losing limbs on your operating table.
As you wobble from Series Seed to Series C, you eventually become Zen-like about the fact that you’re not going to win every bet, perfect every product decision, or nail every Board meeting. You’re going to lose a lot, not a little. So how do you know if you’re winning when you’re flubbing so much?
The truth behind Arthur’s riddle—and the reason for the startup CEO’s dystopia—is that when you’re building a company, knowing whether you’re winning or losing is often impossible. Sure, discipline, logic, and facts are essential—but plenty of organized executives apply those better than you do. Your job isn’t to be flawless like Pat Metheny, perfect with every phrase. Your job is to walk around the casino, watch the players, pick a table, and place a few key bets—thoughtfully, but without the false conviction that your choices are guaranteed to follow reason. You need to be really right about a few big things, likely more intuitive than logical, while muscling through a lot of smaller mistakes.
If you’re committed to entrepreneurship, you eventually understand the value of focusing on just a few big things. You also find joy in repeating those few big things over and over again, driven by the irrational belief that it’ll all work out. The company I co-founded in 2010 was purchased by a larger company, and as Arthur’s riddle predicts, we didn’t know how our bets were playing out until the very end. With the benefit of hindsight, I think we did three big things particularly well:
Conception. People assume that the hardest problems in building a tech company are technology-related. In reality, they’re among the easiest. The hardest, most consequential problem for a new tech company is its conception: Why must it exist, and what must it do? How do we pay off those answers every day as we build? I’d helped build another company before Krux that, while beautiful, wasn’t conceived quite right—leading to endless revisions. With Krux, we spent significant time at the kitchen table refining the 'why' before tackling the 'what' and 'how,' and that clarity paid dividends. We avoided chasing shiny objects and stuck to the original blueprint.
People. We stayed away from brilliant jerks—those divas brimming with talent but unwilling to share or collaborate. When they slipped through, we sent them on their way quickly. Instead, we made big bets on leaders who weren’t famous but had the hunger and ability to learn fast. We weren’t perfect, but we largely built an organization where knowledge power trumped position power.
Lean Buildout. Overstaffed companies give a false sense of scale during boom times, but they’re impossible to steer when the inevitable flubs pile up. Overfunding distorts the social contract with employees, who forget we’re all on the hook to deliver. By keeping Krux lean, we had more flexibility to fight key battles and gave people more opportunities to stretch into new roles. Scarcity fueled creativity and kept us focused, and it built trust with investors who re-upped because we spent their money wisely.
The placard at the top of this post sits on my desk as a kind of home base and gentle reminder. Passersby often see it as gallows humor or a not-so-subtle message to my employees. I try to explain that it’s neither. In fact, I find inspiration in it—and Arthur’s riddle explains why. In a job where you don’t always know if you’re up or down, winning or losing, you have to find joy in the journey—wherever it takes you.
Around the Web:
Generative AI grows 17% in 2024, but data quality plummets via VentureBeat 📈📉
Si Chen, Head of Strategy at Appen, explained in an interview with VentureBeat: “As AI models tackle more complex and specialised problems, the data requirements also change,” she said. “Companies are finding that just having lots of data is no longer enough. To fine-tune a model, data needs to be extremely high-quality, meaning that it is accurate, diverse, properly labelled, and tailored to the specific AI use case.”
Can the Media Survive? Big tech, feckless owners, cord-cutters, restive staff, smaller audiences … and the return of print? via NYMag 📺 📰 ☠️
“Google really undermined professional journalism when they moved away from PageRank. It’s one thing to place less emphasis or weight on authority. It’s another to actively harm those publishing houses that have reputations and authority. And I think that they spent the past ten years seeing how far they can push their monopoly and what they can get away with. What they found is they can get away with a great deal.” — Bryan Goldberg, CEO, Bustle Digital Group
Man spent $2 million to find new largest prime number via Popular Science 🔍 🔢
Durant’s achievement also marks a major moment in the hunt for Mersenne prime numbers—it’s the first of its kind to be found through the use of graphics processing units (GPUs) instead of traditional central processing units (CPUs). GPUs have come to prominence in recent years in conjunction with the rise of machine learning, large language models, and artificial intelligence, all of which often rely on massive GPU networks to function. For 28 years, GIMPS volunteers relied on CPU power to use the organization’s original software. In 2017, however, a developer named Mihai Preda designed an open-source program called GpuOwl to continue the Mersenne prime research through these much-improved machines.
Science is Political via The American Prospect 🥽🧪🔬=🏛️
For only the second time in its 179-year history, Scientific American has endorsed a candidate for president: Kamala Harris. I’ve heard arguments that this was a bad idea, that it is unlikely to move a single vote while risking aid and comfort to conservatives who want nothing more than to be able to credibly claim the scientific community as just one more in a malign den of elite liberal villainy… A WILLINGNESS TO REVISE CONCLUSIONS whenever facts change is science’s fundamental DNA. That’s why, come to think of it, we know what DNA is. It is why science and right-wing thought are incompatible, and why this tension is so existentially important to understand. The sudden emergence of a fantastically deadly disease in 2020 provides a case study.