Most people's perception of AI is limited by exposure to its most basic forms, leading to a narrow and often inaccurate understanding.

Actual productivity gains, from AI, won’t come from simply multiplying the number of tasks agents do. Real value will come when AI systems understand your priorities, constraints, and working style at a deep level. Although those AI agents are not fully here yet, you can start preparing by building a knowledge base that captures the essential context of your work (the current beneath the surface). This foundation will enable future AI to make decisions you can trust.

The free ride is ending. If you have been using AI tools heavily over the past two years, you have benefited from one of the most aggressive subsidy campaigns in the history of consumer technology. Companies were burning capital to get you hooked, to gather data, to win market share. Inference was expensive, and they were eating the cost. That era is winding down.

There is something almost reflexively defensive about admitting you watch short clips at all. Like you owe someone an explanation — that you also read long articles, that you listened to a three-hour podcast last week, that you are, in fact, a serious person. I know that guilt. I have felt it too, usually right after losing forty minutes to nothing I can actually remember.

There is a lot of talk about how AI makes you faster — faster at writing emails, faster at summarizing documents, faster at producing the things you already produce. Maybe it does. But I keep coming back to a question that Cal Newport and others have pushed: in the knowledge economy, is faster actually better? A salesperson who sends ten thousand emails a day and books no meetings hasn't improved anything. Speed applied to the wrong thing is just efficient waste.

I have heard a few discussions lately about whether AI will turn out to be humanity's biggest Pyrrhic victory. A Pyrrhic victory, for those unfamiliar, is a win that costs so much it is effectively a defeat. You achieved the objective — but at what price?

AI is changing not only what people learn but how they learn. This is not the first time a technology has caused us to question whether something is still worth knowing. Think about all the math formulas you were forced to memorize as a child. At some point, most of us either forgot them or quietly decided a calculator was good enough. The question AI is now forcing us to ask, more broadly, is the same one: if a machine can do it better than you, is it still worth learning?

How much should you know about AI? The answer, I'd argue, depends entirely on who you are and what you need from it — but for some it'll be more than they think, and for others, the risk is getting so deep you  lose the forest for the trees.

I find AI incredibly promising and use it in my professional endeavours. But at least for now, I am unsure of the value proposition these tools offer in the personal realm. This may mean that, eventually, frontier-model development companies will shift their priorities away from the personal altogether and focus only on the enterprise. We may already be seeing this

The Eisenhower decision matrix is a useful framework, but it will need to be rethought for the age of AI. The matrix is essentially a tool for deciding whether to do, schedule, delegate, or delete a specific task.

Most people can mentally map spaces. Say you’re heading to the grocery store—you picture the route: milk aisle, cereal aisle, cash register, exit. There’s a debate over whether AI models possess a similar understanding of the environment, especially about whether reading is the same as real experience. But could world models bring this understanding? 

I don’t know what it is about AI videos that immediately makes me question the validity and value of the content. At first, these videos were fun, quirky, and novel. But now that they are inundating more of my life, and the consequences of this synthetic media are becoming apparent, it is more vital than ever for people to know how to parse through this media.

People have been found to hold a negative perception of outsourcing socio-relational tasks. Yet people love to find and continue to seek efficiency. AI promises to keep the proverbial efficiency train rolling, but at great cost to our relationships. When it comes to interpersonal relationships, there is no substitute for investing time and energy.

In Greek mythology, Ulysses has his men tie him down to hear — yet not fall for — the calls of the sirens. The sirens alluringly promised knowledge, wisdom, and pleasure — if only he would stop and divert the direction of his ship. Meanwhile, the other people onboard put wax in their ears and stayed on course despite Ulysses' pleas. As you navigate the choppy waters of AI, I hope to offer you potential strategies to create your very own contract. So that you can tie yourself to the mast (e.g., ground yourself) so that you can hear the seductive calls from the sirens yet stay afloat and on course.

AI agents have the potential to be a democratizing force for good, giving us all more free time. But there are also many risks with these tools that must be considered. These risks are not the overblown doom or prosperity that may occur sometime in the future. Instead, they are the current risks that are not getting the airtime they deserve.

The expression “the cart before the horse” provides a useful framework for examining the current state of artificial intelligence (AI) development. Currently, those developing frontier models are trying to build a tool that is both impactful (in terms of automation and economic stimulus) and profitable for their business. In my view, using the above idiom, the horse (or the first thing companies should be concerned with is impact). Followed by the cart, which I view as profitability. Unfortunately, it seems many of these companies are shifting gears away from developing better, more impactful models and are instead looking for a quick buck.

Loneliness is rising, and some see AI as a solution to our intimacy gap. AI companions—often chatbots paired with avatars—promise to fill our need for connection. These companions are not new and have been widely reported on over the years. Alas, as with everything in the modern era, concern over this suite of technologies has subsided, replaced by other worries. Yet, the trend towards artificial intimacy continues.

AI agents are cool and promise great things — but do not succumb to the rapid rise in cognitive deskilling across the labour market. I have outlined a few ideas for you to consider and adopt if they suit your needs.

The first whole week of January has come and gone, and with it has come the usual hum of the knowledge worker. The return to normalcy has meant emails, meetings, and instant messenger notifications galore. But what if there was a better way? What if this new year, we, as knowledge workers in the digital age, sought out a better, deeper way to engage with our work?

To kick off 2026, this weekend, I sought out some of the simplicity described in Henry David Thoreau’s Walden.