The Future Is Elsewhere

Six Impossible Things Before Breakfast

mike@tomorrow.asia (Mike Walsh) — Mon, 08 Jun 2026 15:44:11 GMT

Last weekend I found myself sitting in a hotel restaurant facing a surprisingly difficult decision. The breakfast buffet cost $34. Coffee was additional. Juice was extra. Alternatively, I could order à la carte. Eggs were $27. Add coffee, perhaps some fruit, maybe juice, and suddenly the economics became unclear. Was the buffet better value? How much breakfast was I actually planning to consume? At what point did the all inclusive offer become the rational choice? And perhaps most importantly, how much mental effort was I willing to spend answering these questions before I had even had my first coffee? The irony was hard to miss. In an age of AI, I was performing an optimization exercise that felt better suited to an algorithm than a human brain.

Digital Labor Is Different, Not Cheaper

mike@tomorrow.asia (Mike Walsh) — Mon, 25 May 2026 19:50:24 GMT

The latest twist in the AI job replacement debate is not that machines are coming for everyone’s work. It is that, in a growing number of cases, the machines may not be cheaper. That is an awkward development for some. For the past two years, many executives have been encouraged to imagine digital labor as a form of near-frictionless substitution: fewer people, lower costs, faster output. Replace the call-center agent. Replace the analyst. Replace the junior engineer. Replace the back office. But the economics are becoming more complicated.

Leadership LARPing

mike@tomorrow.asia (Mike Walsh) — Fri, 15 May 2026 06:13:16 GMT

What is the difference between a high-performing leader and someone who is simply good at performative leadership? That question is becoming more urgent in the age of AI. The latest game in the surreal, parallel universe of big organizations is tokenmaxxing: the attempt to appear highly AI-enabled by generating, consuming, or reporting large volumes of AI usage. This is not really a story about tokens. It is a story about incentives.

AI Won’t Replace Engineers. It Will Redesign Engineering Firms

mike@tomorrow.asia (Mike Walsh) — Sat, 09 May 2026 22:59:52 GMT

One problem with the way we talk about AI and professional work is that we focus too much on what autonomous systems can achieve, and not enough on what we are willing to trust them with. Just because an AI model can generate a plausible answer, or an agent can complete a workflow, does not mean we have resolved the harder question of responsibility. Who decides when the output is good enough? Who understands the trade-offs? Who is accountable when the system fails? Engineering brings that tension into sharp relief. AI may generate the design, but a human still has to sign.

Headless SaaS: The War for Who Owns Work

mike@tomorrow.asia (Mike Walsh) — Sat, 02 May 2026 23:17:03 GMT

The most important users of enterprise software are no longer human. For decades, the design and economics of enterprise technology have been built around a simple idea: a person logs in, navigates an interface, and performs a task. Revenue scales with the number of users, the time they spend inside the system, and the workflows they complete. That model has produced some of the most valuable companies in the world, from Salesforce to Workday to ServiceNow, and it has shaped how we think about productivity itself. That assumption is now under pressure.

The Rise Of The High Throughput Operator

mike@tomorrow.asia (Mike Walsh) — Sun, 29 Mar 2026 01:17:53 GMT

For most of modern knowledge work, the defining anxiety has been simple and persistent: am I doing enough? Enough hours, enough output, enough visible effort to justify my role and my compensation. Performance was measured in activity, and productivity was largely a function of how effectively human effort could be applied to a problem. But what changes when effort is no longer the constraint? When intelligence itself becomes elastic, abundant, and on demand, the question shifts. The rise of the token economy is often treated as a technical or financial detail, but it is something more revealing. It is emerging as a new measure of productivity, not in terms of effort, but in terms of leverage.

When Work Isn’t a Workflow

mike@tomorrow.asia (Mike Walsh) — Thu, 19 Mar 2026 17:43:00 GMT

The prevailing story about AI and jobs is seductively simple: break work into tasks, measure how many can be automated, and once enough of them are, the job disappears. That logic works well for routine work. But in high-stakes, human-facing roles, especially those performed by agents and advisors, it rests on a fragile assumption: that jobs are just workflows, collections of discrete steps that can be taken apart without changing where value is actually created—or whether it can be created at all.

How Many AI Agents Does It Take To Change A Lightbulb?

mike@tomorrow.asia (Mike Walsh) — Sun, 15 Mar 2026 07:03:14 GMT

With all the discussion about AI agents lately, you might be wondering: how exactly do you count them? If multiple agents collaborate to resolve a customer issue or approve a loan application, does that represent one digital worker or many? The question may sound trivial, but it will soon matter a great deal. Organizations will eventually track digital headcount the same way they track human employees today.

The AI Layoff Illusion

mike@tomorrow.asia (Mike Walsh) — Sun, 08 Mar 2026 09:16:41 GMT

A dangerous new market narrative is spreading through boardrooms and earnings calls: artificial intelligence has made companies so productive that they can slash their workforce and barely notice the difference. Analysts applaud, the stock jumps, and executives describe a future where digital labor replaces the old human-heavy operating model. Unfortunately, the economy is rarely that tidy.

Abundant Intelligence Does Not Have to End in Crisis

mike@tomorrow.asia (Mike Walsh) — Sat, 28 Feb 2026 19:54:29 GMT

There is, perhaps, a small silver lining in the current wave of AI anxiety. Not long ago, the dominant fears revolved around killer robots, runaway superintelligence, and apocalyptic scenarios that ended with data centers being nuked from space. Today the panic is more grounded, and in many ways more sophisticated. We are no longer imagining machines conquering humanity; we are worrying about white-collar unemployment ticking above 10%, mortgage books wobbling in San Francisco, and private credit portfolios unraveling because software agents can write code faster than junior analysts. The monsters have moved from science fiction to the balance sheet.