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.
Box created 13 new AI roles, one to market to industries it couldn't staff before. The question isn't what AI lets you cut. It's what marketing it makes possible.
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.
Anthropic shipped Opus 4.8 with Dynamic Workflows: hundreds of parallel subagents that check each other. The one thing that doesn't parallelize is judgment.
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