Thoughts on motivation; AI sabotage; purer mathematics: Newsletter 3 June 2026
Newsletter 154. One thing gets the most of our people in the workplace: a commitment to those around them. Plus, how the government is holding science back, AI embraces our romanic word fetish, three people to follow and three books to read.
Team > talent
I’ve worked for a lot of companies. I’ve put in long hours working alongside other hard workers. I’ve also been in situations where it felt like I was phoning it in.
Consider a fundamental question every business leader must answer: What is it about your workplace that gets people to feel total commitment and exert maximum useful effort?
It could be any of these things:
- High compensation.
- The promise of making stock or options much more valuable, as in a startup company.
- Great benefits.
- A truly empathetic and inspirational supervisor.
- Inspiring leadership from the top.
- Transparency about the business.
- A clear understanding of the task at hand and how you are contributing.
- Flexible working conditions, for example, the ability to work from home.
- Working on something that matters.
- Making the world better.
- Making an impact that’s visible to a lot of people.
- Personal glory or awards.
All of those are great things for a company to have. They all contribute.
But when I think about the places where I worked the hardest and accomplished the most, one thing mattered more than anything else.
The team.
When I was working alongside others on a shared goal that we all believed in, that mattered.
When I respected their talent and their abilities and they felt the same about me, that mattered.
When I didn’t want to let people down, that really mattered.
This is culture, of course. But it’s a lot more than that. If you look around at the eight people you interact with most frequently at work — including your boss, of course, but the whole team you work with — how do you feel? Are these people you can count on? Do they appreciate you? Do you want them to succeed? Do you want their work to be meaningful?
Why do startups attract workers that work so hard? Conventional wisdom says that happens because the founder and early staff are hoping to get a huge payoff when the organization goes public or gets acquired. That matters, but people only work so hard for money. They work a lot harder because, in a startup, a very small band of people are working together for a clearly defined goal, and they can see each others’ efforts and contributions.
Military commanders certainly know this truth — it’s why their hard-working soldiers work together in tightly committed units towards incredibly difficult and dangerous goals.
Most of us are not in combat, but we certainly know whether the people alongside us are worthy of our efforts.
What does this mean?
It means that hiring for cultural fit may be more important than any other activity the organization does.
It means that a single super-talented asshole can irreparably destroy the work ethic of a team and the company’s ability to succeed.
It means that benefits and pay and stock and improved working conditions can attempt to make up for lack of team cohesion, but they will be both expensive and limited in effectiveness.
It means manipulative management techniques are far more likely to backfire than be effective in the long run.
And it means that laying people off in the hopes that the ones that remain can do their jobs with AI is a self-inflicted wound from which few companies can recover.
People want to do work that matters alongside other people who share their commitment. When that happens, they accomplish amazing and inconceivable things.
When it doesn’t happen, no amount of technology, compensation, cheerleading, and “leadership” can fix it.
News for writers and others who think
A new paper examines the narrative tells of AI writing (not stylistic tics like em dashes, but the way it structures narratives). For example, it over-explains its themes and has less diversity in narrative styles.
The American anti-AI movement is tipping into occasional violence, as documented in an article in The Atlantic (gift link). I’m reminded of the original anti-industrial activists who chucked wooden shoes (sabots) into the machinery, the origin of the word “sabotage.”
Prominent mathematicians have published a new thesis, “The Leiden Declaration on Artificial Intelligence and Mathematics,” that suggests that AI in the sciences be used to support, not supplant, the creative work of mathematical thinkers.
The Trump Administration announced a new policy for vetting government grants to ensure that they adhere to American (that is, Trumpian) values (gift link, New York Times). Research should come from varied viewpoints and explore diverse and sometimes radical ideas. This administration’s policy is a continuing step towards ensuring the US loses its leadership in science and engineering research.
From The Washington Post: “In his 1946 essay ‘Politics and the English Language,’ George Orwell argued that bad writers ‘are nearly always haunted by the notion that Latin or Greek words are grander than Saxon ones.’ Today, artificial intelligence chatbots have fallen victim to the same blunder.” (gift link)
Three people to follow
Tiago Forte , expert on how to be most effective with design thinking
Srinivas Rao , exploring what comes after chatbots for personal productivity
Shane Parrish , producer of the fascinating Knowledge Project podcast
Three books to read
The Art in Marketing: Why We Need Less Science and More Art in Marketing by Anthony “Tas” Tasgal (Lid, 2026). Have we gone too far in turning marketing into a math exercise?
Don’t Call It Art: 10 Ways to Create Like a Kid Again by Austin Kleon (Tarcher, 2026). Discard the limits and be creative once more.
In Trees: An Exploration by Robert Moor (Simon & Schuster, 2026). Spanning ten years and countless countries, what trees can teach us about time, growth, and endurance.