Thursday, February 26.
3:35 pm PST – Jack Dorsey said thank you and goodbye to 4,000 people. Block;s profitability was growing, but the promise of “intelligence tools…paired with flatted teams” enabled a fundamental shift in how the company could be run
4:12 pm PST – He posted his farewell announcement to X for the world to read. In it he wrote, “I know doing it this way might feel awkward. I’d rather feel awkward and human than efficient and cold.”
Is there anything more darkly humorous than a CEO trying to avoid appearing efficient and cold when communicating a decision to make the company more efficient and cold?
Only the moment when your boss calls to ask how your plans to grow the business and going and then informs you that the C-Suite wants a plan “to do what Dorsey just did”
Tuesday, March 10.
Time unknown – The agenda of Amazon’s weekly “This Week in Stores Tech” focused solely on investigating why “the availability of the site and related infrastructure has not been good recently.”
More specifically, why, for SIX HOURS, Amazon customers could not access their accounts, view product prices, or complete checkout. That is nearly $300M in lost revenue assuming the outage only affected North America.
All because, after years of cutting headcount and ramping up AI, junior engineers basically vibe-coded production changes..
As best practices and safeguards are yet to be “concretized,” it’s now the responsibility of senior engineers to review all production changes prepared by junior programmers.
How efficient is that AI looking now?
What we lose when we bet on hype, not proof
Researchers at Oxford have documented companies using AI as justification for cuts they had already planned. A January 2026 survey of 1,006 global executives found that 60% have or will make cuts in anticipation of AI’s impact while 29% plan to slow hiring. Only 2% have laid off staff as a result for actual AI-driven results.
Thousands of people are being laid off based on hype, not proof.
It’s reasonable to expect that, one day, AI will live up to the hype and deliver on all the promises promoters are making. But that’s a long-term bet that only pays out if you survive the inevitable crashes in efficiency, revenue, and institutional knowledge.
When organizations swap out people for “intelligence tools,” they lose institutional memory, the subtle, often unspoken, sometimes subconscious knowledge that makes things work. These are the people who understand your clients, your controls, and why past decisions were made. AI can automate workflows. It cannot replicate that knowledge. And once it’s gone, it’s gone.
And the loss continues even amongst the people who remain.
Research from MIT shows that regular AI use reduces activity in brain networks responsible for creativity and analogical thinking by 55%, and the atrophy persists even after people stop using AI tools. You are not trading people for AI. You are trading people for AI while simultaneously reducing your remaining team’s capacity to think creatively, adapt quickly, and catch mistakes. Operations get fragile. Innovation stalls. And when the AI-assisted work fails, as it did at Amazon, there’s no one left to fix it.
The root of growth is never hype
When the call comes down from on high to “do what Dorsey did” it’s hard to counter with cautionary tales like Amazon or reality checks about the state and capability of the organization.
But you can ask questions:
- Are you cutting based on what AI has delivered or what we expect it to?
- How will we ensure essential institutional knowledge isn’t lost?
- If (when) AI-assisted work fails, who fixes it? Amazon’s answers were still on staff. Will ours be, too?
Growth is essential to every organization. But you can’t cut your way to growth.
AI doesn’t change that fact.
It just makes it easier to believe the hype.