Cognition raised $1B at a $26B valuation for an autonomous coding agent. In production, autonomy is the first thing that breaks. How much should you give it?
Box created 13 new AI roles, one to market to industries it could not staff before. The question is not what AI lets you cut, but what 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.
Gumloop's founder told his team to stop automating everything with AI. The expensive failure of agentic AI isn't cost, it's the slop that loses customers.
Business AI token spend is up 13x since January 2025. Marketing is the second-heaviest user and the worst at measuring it. Build a FinOps layer first.
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