52,000 tech workers have lost jobs so far in 2026. Block just cut 40% of its workforce. Morgan Stanley slashed 2,500 roles — while posting record revenue. Everyone says the same thing: AI is taking jobs.
I think that narrative is dangerously incomplete.
A landmark Anthropic study dropped last week — the first to use actual Claude usage data mapped against 800 real occupations. The headlines ran with "75% of programming tasks are covered by AI." Here's the number nobody ran: there is currently little systematic increase in unemployment for the most AI-exposed workers. The study's own authors called for "humility."
The displacement story assumes a fixed pool of work being divided between humans and machines. But the pool has never been fixed. Not with electricity. Not with the PC. Not with the internet.
What AI is actually doing — right now, at scale — is enabling work that simply wasn't happening before. The financial model that never got built. The competitive intelligence that never got done. The analysis permanently deferred because the economics of execution never penciled out.
Clay Christensen called it "competing against non-consumption." It's the most powerful and invisible force in the AI and jobs debate — and it's getting almost zero attention.
Yes, the layoffs are real. Yes, the human cost deserves to be taken seriously. But Jack Dorsey didn't cut 40% of Block because AI automated his workforce. He cut it because Wall Street has spent three years rewarding efficiency over growth, and AI handed him the narrative.
The story of what's being created is still loading. We're making major policy and career judgments at the worst possible moment in the data cycle.
My latest piece breaks this down in full — including what the Anthropic data actually shows, why the productivity paradox is hiding non-consumption gains in plain sight, and why this time may not be as different as the headlines suggest.
Would love to hear your read on it.
https://t.co/l4KskQsRct
@NostalgiaGalaxy XP IMO was the biggest jump from “unstable “- not windows native - to “pretty stable”, windows native for all. That’s what makes us look back on it with a smile!
The "AI will kill SaaS" narrative has a fundamental problem. It treats SaaS as if it were one thing. It isn't.
SaaS is a delivery and business model — not a product category. When people say AI will kill it, they're actually asking two very different questions:
- Will AI change how enterprise software is delivered and priced? Probably yes. Consumption-based models and agent-driven interfaces are already reshaping that layer.
- Will AI eliminate the need for the applications themselves? This is where the argument gets sloppy.
After nearly four decades watching technology markets get called wrong at the moment of maximum noise — the mainframe, client-server, on-premises — I've learned to treat peak disruption panic as a signal. Not to ignore the threat. But to ask a more precise question.
The survivability of any enterprise software company right now comes down to one thing: what kind of moat have they built?
Horizontal workflow tools with no proprietary data and no network effects? Harder road.
Vertical data powerhouses sitting on irreplaceable industry-specific data? AI doesn't threaten that moat — it deepens it.
Systems of record embedded in compliance and governance workflows? These don't get replaced by systems that might hallucinate.
And if SaaS is really being disrupted — where is the revenue going? We don't have a clear winner outside the existing ecosystem yet - and may not for a while.
I've written up the full framework in my latest Substack https://t.co/WC8PkdVgGc. The question isn't will AI kill SaaS. It's which SaaS companies built something worth keeping.
I have noticed many of the Winter Olympic events have been modernized or added. It’s time to modernize ski jumping. I propose flying squirrel suits. Any takers?