AARP measured it: the first technology that gives the experienced worker more job security than the young one. Losing them to early retirement is losing your asset.
Meta's own leaders now call morale the worst in company history after years of ruthless efficiency. The lesson for how you bring AI into your org is blunt.
Aaron Levie says it's all evals. Garrett Lord refounded Handshake around evals after talking to hundreds of executives whose AI programs stall at the pilot stage. The reason they stall is always the same: the company can't define what good looks like.
Satya Nadella says there should be as many AI models as firms in the world. The logic: competitive advantage comes from embedding your accumulated tacit knowledge in weights you own, not borrowing it from a vendor.
Paul Bakaus, backed by a16z, names the distinction most enterprise AI discussions miss. Delegation: you use AI to get where you decided to go faster. Surrender: you let AI decide where to go. One serves you. The other doesn't.
Alex Lieberman mapped 14 stages of AI adoption after 14 months with executives. Most companies skip the first ten and start by building. That is where they stall.
Gemini 3 Flash is listed 80% cheaper than GPT-5.4 and costs 38% more to run. The list price is marketing. The bill depends on how many tokens each model burns.
Altman said the most credible scientists held AI back through certainty. The same thing happens in your company: the surest person is often the biggest brake.
Joe Pine puts it bluntly: you are what you charge for. Charge for the tool and you're in the tool business. Charging for the outcome forces the change to actually happen.
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