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Amazon built a competitive advantage around forcing clear thinking through mandatory memo writing — six-page documents that executives had to read silently before discussing. Now that AI can generate those memos instantly, people skip the thinking step entirely, and the author argues this is eroding decision quality and trust across the company.
- Amazon's writing ritual (30-minute silent reading sessions, red-pen feedback) forced rigorous thinking before wasting colleagues' time; AI-generated documents bypass this filter, leading to half-baked decisions that compound over time.
- Performance reviews have devolved into managers copy-pasting AI summaries of AI summaries, turning what used to drive career growth conversations into "a conversation between two prompts" with humans as intermediaries.
- The author proposes a practical rule: use AI freely for reversible "two-way door" decisions (status updates, code reviews, routine tasks), but require humans to write and read for irreversible "one-way door" decisions (strategy, hiring, major architecture changes).
Census Bureau surveys tracking business AI use from 2023 to 2026 show that even as AI adoption tripled, firms report almost no net employment changes. About 95% of businesses say AI hasn't affected their headcount either way.
- AI adoption jumped from 3.7% of firms in September 2023 to 10% by late 2025 (18% when counting any AI use), but employment impact remained flat: roughly 2-3% reported job increases, 2% reported decreases, and 95%+ reported no change across both survey periods.
- Among firms actually using AI, 44% say it supplements existing work, 10% say it replaced employee tasks, and 11% say it created new tasks—but most firms (64%) made no business changes to implement AI and only 1% hired new AI-skilled workers.
- Task substitution is growing within the small subset of firms where it's happening: the share reporting AI took over "a large number" of tasks jumped from 2.4% to 7.1%, but this group still represents only about 2% of all firms.
Meta’s leadership shifted from a “move-fast-with-stable-infra” model to enforcing mandatory AI tools, tracking engineers’ every keystroke and click without opt-outs. This aggressive push has turned its once-prized engineering org into a monitored cost center, sparking outages and internal chaos.
- Meta shifted from "move fast with stable infra" to mandatory, surveillance-heavy AI tool adoption, tracking engineers' keystrokes and clicks with no opt-out.
- The AI push turned engineering from a profit-driving function into a monitored cost center, causing outages and internal chaos.
- Massive AI spending (Llama models, $14.8B for 49% of Scale AI, a failed $2B Manus AI bid) coincides with mass reorgs and plummeting engineer morale.
- Leadership exhibits "AI psychosis," demanding AI-driven fixes for problems that don't actually exist, further alienating core engineers.
Many companies are struggling to get employees to adopt AI tools. The initial promise of AI streamlining tasks and freeing up time for more valuable work is not being realized. Instead, it appears that AI may be increasing the workload for many workers.
- AI tools meant to cut workload often add a learning-curve burden, leaving employees managing systems instead of saving time.
- Pressure to adopt AI quickly is fueling burnout, as workers juggle old responsibilities alongside mastering new tech.
- Companies expecting AI to streamline workflows are finding the opposite—it's making work more complex, not less.
- Success requires better training and support, not just deployment of the tools themselves.