The librarian in the loop
A developer gave Claude Code access to 100 books and a simple command: "find something interesting." What came back wasn't summaries. It was connections no hand-tuned pipeline could find.
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At CES 2026, Samsung's TM Roh promised AI in everything. Twelve days earlier, he told Reuters price hikes were unavoidable. That gap between keynote and confession defines a memory shortage manufacturers have no intention of fixing anytime soon.
AI transcription tools promise to eliminate typing forever. The accuracy has genuinely improved. So why do professionals still reach for their keyboards when it matters? The answer involves hidden trade-offs most vendors won't mention.
A Fortune 500 engineer deleted 47,000 lines of code, replaced them with 212 lines of YAML. AI costs dropped 63%. The routing layer between enterprises and their AI models is quietly becoming the most strategic chokepoint in tech.
Your employees paste customer records and source code into AI tools you've never approved, dozens of times daily. Bans don't stop them—IBM found the habit adds $670,000 to breach costs. The companies winning aren't building higher walls.
Enterprises are spending billions on AI pilots, but MIT's research shows most deliver no return. It's not the technology failing. The gap between impressive demos and working systems comes down to data quality, technical debt, and organizational readiness.
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