When culture is a fuzzy concept, it’s open to interpretation. People unwittingly wield their interpretations like shields or swords. Well-documented cultures, on the other hand, are open to scrutiny yet transparent and easier to govern and co-own.

If AI commoditises outputs, then skilful, tasteful people will matter more than ever. Salary is the fundamental way corporations value such people. In addition to standard HR indicators, we need human ways to determine fair compensation.

By viewing rest as only a means to recharge ourselves for work, we undermine its role in living a deep life. Rest is valuable in and of itself.

When defining corporate cultures, too much emphasis goes to the values poster or the employer value proposition. Attractive, credible cultures however, ground their messaging in strong corporate theories.

Cybernetic collaboration with AI is making us conflate speed and productivity. There’s no alternative to deep focus, even if AI promises to create outputs at “warp speed.” In 2026, leaders will serve their teams best by creating a work environment conducive to deep work.

In the last few years, I’ve made minor tweaks to my life, to live a deeper life. A couple of months back, when my dad passed away, I reflected on the compounding benefits of these changes and how they’ve helped me savour life just a wee bit more.

AI is a now a significant contributor to the broader trend of enshittification. The market is full of AI-powered products, features and code that are costlier to use and run and often counter productive for the end users.

Most executives are reaching for ways to become an AI-first organisation, but many of them are missing the productivity power up that’s hidden in plain sight – asynchronous collaboration. Not only does asynchronous collaboration free up unproductive time for workers, it helps create the digital exhaust of knowledge that LLMs can feed on.

Taste and discernment are more important than ever, in the age of AI.

The unpredictable nature of generative AI can often feel as addictive as gambling. Addictive services often get enshittified, and can also be candidates for a classic bait-and-switch.

As the circular funding economy of AI becomes more transparent, innovation slows and costs increase, it may help us all to temper our AI enthusiasm. There are many indications that the current state of generative AI is neither essential nor as transformative as the frontier AI companies will have us believe. If anything we could make the case that generative AI is a net negative for most stakeholders.

Modern workplaces increasingly reward visibility (“restaurateur” roles) over deep work (“chef” roles), especially during turbulent times. If AI-driven disruption and organisational thrashing favour those who are present and highly visible, what should deep workers do?

The larger the company, the harder it is for them to express dissent, especially under authoritarian regimes. If employees expect their C-suite to be their protest comrades, they’re likely to be disappointed. Our employers cannot be vehicles for our activism.

I’m “AI bipolar” - an enthusiast and a sceptic. Here are some of the reasons I blow hot and cold with AI.

Enterprise AI pilots have a 95% rate of failure. Could it be that people have experiment fatigue and that companies are taking a piecemeal approach to AI innovation?

AI has many productivity benefits, but those benefits may only accrue towards corporations who now have new tools to exploit workers.

AI is coming for many jobs. Bullshit jobs will be the first to go. Those of us with a real job must cultivate a few characteristics to be AI-first in the way we work and stay relevant in the job market.

We often derive satisfaction from difficult activities, even if they aren’t pleasurable. Does this effort paradox hold any learning for us all?

In teams, no one is, or should be, indispensable.

Before companies seize productivity advantages through agentic AI, they’ll have to contend with a messy period of agent sprawl, poor design choices and inefficient workflows. When the dust settles, success won’t just be about the ease of agent building. The companies that succeed will most likely prioritise thoughtful design and problem solving, and find clever ways to balance bottom-up innovation with lightweight governance.