OP-ED - How solo sailors sleep
Solo sailors don't forecast the ocean. They set an alarm and pay attention. In the age of AI disruption, that pragmatic sensibility turns out to be rarer and more valuable than anyone is admitting.
There is a question that always comes up when people learn someone sails alone across oceans: how do you sleep?
The answer, offered recently by solo sailor and content creator Noa Hopper navigating between Lisbon and Tenerife, is instructive well beyond the sea. Turns out you don’t get eight hours. You don’t get the recommended rest. Instead, what you get is a new rhythm, calibrated not to your preferences but to your actual circumstances.
In a busy shipping lane, Hopper sleeps on deck in twenty-minute bursts. In open ocean, where he has not seen another vessel for three days, he allows himself forty minutes below. The interval isn’t arbitrary. It’s calculated from a simple fact: his visible horizon is 8 miles (12.87 kilometres).
At ten knots, he reaches that horizon in roughly an hour. But if another vessel is doing the same speed toward him on a direct collision course, both ships become visible to each other only twenty to thirty minutes before impact. So twenty minutes it is. Not a prediction. A calibration.
While tracking the volume of AI disruption commentary flooding my feeds over recent months, I’ve been looking for ways to make sense of all the data, insights and speculation swirling about me in what often leaves me feeling like I have my mouth attached to the end of a firehose on full blast. For the most part, the issue isn’t so much that the commentary is wrong, but it is almost uniformly doing the wrong thing. It's trying to predict. Almost never calibrating.
A fortnight that tells the whole story
Consider what a single fortnight produced. In New Delhi, Reliance Industries Limited chairman and managing director Mukesh Ambani (who also happens to be India's wealthiest man) took the stage at the India AI Impact Summit to announce that Reliance Jio, India's largest mobile network operator, having connected India to the internet era, would now connect it to the intelligence era, backed by a commitment of roughly USD 110 billion over seven years to build sovereign AI infrastructure from the ground up. He framed it explicitly as a template for the Global South. "India cannot afford to rent intelligence," he said.
Days earlier in Kigali, Anthropic formalised a partnership with Rwanda's government and ALX to deploy an AI learning companion to hundreds of thousands of learners across Africa — one of the continent's most substantive AI public-private education initiatives to date.
Two Global South nations. Two very different scales of ambition. Both operating from the same basic conviction: that the intelligence era is not something that will happen to them, but something they intend to shape.
When the cheerleaders start doing the maths
Meanwhile, on the All-In podcast, American media maven, internet entrepreneur and investor Jason Calacanis described running Claude-based AI agents at roughly USD 300 per day in token costs per agent — an annualised cost of USD 100,000. Calacanis’ Canadian-American co-host, venture capitalist and entrepreneur Chamath Palihapitiya concluded that organisations needed AI to be at least twice as productive as an equivalent employee to justify the economics.
This is the smartest counter I’ve seen to ai taking over jobs, in the short term.
— Mark Cuban (@mcuban) February 19, 2026
Is the ((aggregate tokens cost to do what an employee does + plus fully encumbered developer and maintenance costs ) / (fully encumbered employee cost ) )<= productivity ?
If it takes 8 Claude… https://t.co/ukYZ2aEm8G
US businessman and television personality Mark Cuban did the maths publicly and put the required productivity ratio at closer to 2.16 to one.
These chaps aren't cheerleaders for human employment. They’re the same voices who have spent years insisting that AI will hollow out services-sector work entirely and annihilate Software as a Service (SaaS) business models that have been all the rage in Silicon Valley. The fact that their own calculations give them pause is worth noting.
Separately, a speculative macro scenario published by independent investment research firm Citrini Research last week imagined a June 2028 global economy in which white-collar employment has collapsed, private credit markets have seized up around defaulting software company debt, and mortgage delinquencies are rising in area codes dominated by tech and finance workers.
It was written with impressive analytical discipline and clearly labelled as speculative. It was also shared, discussed, and absorbed as though it were either inevitable or entirely possible, depending on one's priors.
I reckon both responses miss the point. The scenario is not a forecast. It is a visible horizon calculation. That is, someone doing the maths of what happens if every assumption currently holding the system together fails simultaneously, in a particular sequence. It’s worth grappling with, sure, but not worth treating as prophecy.
Three kinds of blindness
The AI disruption conversation is almost entirely populated by three kinds of people. Those staring at the six-hour horizon, producing scenarios so elaborate and internally consistent that they acquire the texture of inevitability. Those refusing to look up at all, dismissing the entire discourse as hype and returning to business as usual. And those who have simply thrown themselves at the wave — not because they have calculated the odds, but because everyone around them appears to be paddling and the fear of missing the boat outweighs any discernment about what they are actually boarding. The breathless adopters. The AI à la OpenClaw maximalists. The ones whose AI strategy begins and ends with a licence key, an announcement to the all-hands and a press release.
All three are navigating blind. Typically, only one of them knows it.
I should be transparent: my own read of where things are heading is not an especially comforting one. But that is precisely the point. This isn’t about pessimism versus optimism. It’s about the quality of attention and level of stewardship we bring to what is actually in front of us.
The sailor does not spend his twenty-minute alarm intervals trying to forecast where every vessel in the Atlantic will be in six hours. He wakes up, scans his actual horizon, checks his Automatic Identification System (AIS) display for live boat locations, notes what is genuinely close, and adjusts his heading if necessary. Then he goes back to sleep.
What is scarce, and what I find myself genuinely hungry for, is more of us engaging that twenty-minute interval ritual. The discipline to ask not what the world will look like when the AI revolution is complete, but what is actually visible from where I am standing right now, and what adjustment that warrants. That’s a trickier question than it sounds. It is also, as we will see next week, one that history has already answered (badly) at least once before.
This is the first of a three-part series. Part 2 entitled, The Mine, The Machine, and The Intern, publishes next Tuesday.
Editorial Note: A version of this opinion editorial was first published by Business Report on 24 February 2026.