Silvia Adlesic said it plainly: willingness to pay measures what the customer believes, not what you built. And in the AI era, belief gets corrected in 48 hours.
Anthropic says Claude writes most of its merged code and its engineers ship 8x more per quarter. The new line isn't who uses AI, but who can prove output.
Uber capped AI spend at $1,500 per person and one company burned $500M on Claude in a month. The cap treats the symptom. The cause is agents turned loose with no scope.
Building AI has never been cheaper, so the bet is to build. But 95% of pilots move no P&L, and in most companies nobody owns the downslope of the curve.
Cognition raised $1B at a $26B valuation for an autonomous coding agent. In production, autonomy is the first thing that breaks. The real call is how much to give it.
A sales agent wrote a flawless $0.00 invoice for a 14-seat deal. The pricing API was correct. Every log was clean. Only the full execution trace explained it.
The 'AI consultant' title expires. What stays is a discipline: start with a deterministic workflow and climb to an agent only when the problem demands it.
Kirkland & Ellis is putting $500M into AI and half of LinkedIn misread it: they aren't training a model, they're building the layer that sits on top of it.
Two 2026 court rulings confirmed it: what your team types into ChatGPT or Claude is discoverable evidence. The problem isn't AI. It's having no policy.
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