Q2 bank earnings confirm AI is generating record returns at the capital formation layer — not the operational efficiency layer — and the only concrete productivity claim from any CEO this week contained no function, no EBIT figure, and no audit trail.
Uber blew its annual AI budget in four months. Microsoft cancelled Claude Code licenses mid-year. The culprit is not model prices — it’s a structural mismatch between consumption-based AI billing and enterprise fixed-cost planning.
AI recommendation poisoning is already in production across 31 companies and 14 industries. Here’s what prompt engineers need to understand before their enterprise AI deployments are compromised.
Context engineering is replacing traditional prompt engineering as AI professionals shift from crafting clever prompts to designing comprehensive information ecosystems for AI agents.
Microsoft just committed $25B to AI infrastructure in one week, while a prompt optimization startup raised $6.5M—enterprise is going all-in on AI agents.
Enterprise prompt engineering is evolving from art to systematic discipline with sophisticated management systems, versioning, performance analytics, and prompt specialists working alongside developers to optimize AI accuracy and efficiency.
