“I insist on a lot of time being spent, almost every day, to just sit and think. That is very uncommon in American business. I read and think. So I do more reading and thinking, and make less impulse decisions than most people in business. I do it because I like this kind of life.” - Warren Buffett
I first read that almost ten years ago. It stuck with me then, and I’ve come back to it more times than I can count.
I’d argue that it matters more now than it ever has, which is an unpopular thing to say in 2026, because at this moment, sitting and thinking looks a lot like falling behind.
Two Kinds of Hurry
AI, or more recently known as SI (Super Intelligence), is moving at a pace that’s creating real anxiety among entrepreneurs.
The anxiety comes in two flavors. The first is fear: the feeling that if you don’t move now, today, you’ll be left behind for good. The second looks like confidence: people who see the money grab so clearly that they’re racing to build the next big thing before anyone else does.
Different emotions, same behavior. Both are rushing. And both tend to skip the step Buffett talks about, which is sitting with a problem long enough to actually understand it.
The Hard Part is the Point
Last month, the one and only David Senra sat down with Alex Taubman, co-founder and CEO of Long Lake, to talk through Long Lake’s $6.3 billion all-cash deal to acquire American Express Global Business Travel, the world’s largest corporate travel platform.
What struck me wasn’t the deal size. It was how obvious it was, listening to Alex, how much time he’d spent understanding the opportunity before pursuing the thesis. It’s not all about AI. It’s a bet on a real business, with real customers, real suppliers and operations, and a specific view of where technology changes the work inside it.
There’s one line from the conversation, that I think, is one of the most important realizations today:
“Deploying technology innovations in the real economy is actually really hard.”
The hype cycle doesn’t want you to hear this. A demo is easy. Changing how work actually gets done inside a real business, with its legacy systems, its people, and its customers who need things done right by Friday, is not.
So how do you execute successfully? Patience, persistence, and a lot of sitting and thinking every day.
Still Here
If I had a nickel for every time I’ve seen or heard someone say CPAs, accounting firms and bookkeepers would be obsolete by now, I’d be sipping Mai Tais on a beach somewhere. It sounds nice. It wouldn’t be anywhere near as fun as what I’m actually doing, which is deploying AI into the real economy. We’re constantly changing how work gets done, but the fact that someone has to own it, has not changed.
How We’re Doing it
It starts in house. Before any client trusts an AI-enabled workflow, we have to trust it ourselves. Inside our own workflows.
For instance, deploying agents into specific systems for specific tasks, such as Accounts Payable, or posting a month end entry. We have agents perform tasks on our behalf where stakes are low. We test, we iterate, we adopt. When you really breakdown how many repeatable, teachable tasks get done daily, there is a tremendous amount of work that can be eliminated. This is just one very high level example of how we’re using Super Intelligence.
As a young and fast-growing firm, we’re in a fortunate and unusual position. We execute in a part of the economy with a tremendous amount of demand. We’re the full accounting infrastructure and backbone for hundreds of small and mid-sized businesses, and the tax planning and compliance team behind those businesses and their founders.
For the smaller and middle-market companies we work with, the benefit of AI shows up as faster, more robust, data-driven insights, obtained with far less friction on their part.
Where it’s getting more interesting is further up market. Plenty of businesses doing $100M+ in revenue carry bloated back-office accounting and finance departments, and they’re struggling to find the right talent to support them. We’ve started partnering with organizations that fit that profile to streamline their back-office workflows. The goal is to shift their long-term cost structure toward the parts of the business that generate revenue, and to take the cost and risk of turnover off the table.
We’re doing this slowly and on purpose. It’s hard, and the only way to do it well is to understand each organization before we try to change anything in it.
Back to the Chair
Here’s the irony of this moment: The technology is fast, and the work of deploying it well is slow. Models are improving quick. Businesses, and the people inside them, change on a very different clock.
The winners of this era won’t necessarily be the ones who moved first. They’ll be the ones who understood the problem best, and then had the patience and persistence to keep working on it after the excitement wore off.
Sit, read, and think, every day.
