Margaret Atwood says the problem with AI is ‘garbage in, garbage out’
THE SO WHAT
When a mainstream literary figure reduces AI to ‘garbage in, garbage out,’ it reinforces that data quality and provenance are now a brand and trust issue, not just a technical one. If you’re training or deploying models on messy or dubious corpora, assume reputational blowback is part of the risk surface.
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Applied AIThe rapid pace of AI progress has created a pervasive fear of missing out across Silicon Valley, fueling anxiety among founders, executives, employees, and VCs
If founders and operators are literally losing sleep to Claude Code, you're looking at a classic over-rotation risk—burnout and bad bets made from FOMO rather than fit. Use this as a forcing function to narrow: define 1–2 AI bets tied to revenue or margin and explicitly ignore the rest for the next 90 days.
Applied AIBig AI Had a Point When It Said It Needed to Be Told What Is Not Okay
The governance bottleneck is no longer model capability but clarity on what society considers out-of-bounds. If you're deploying frontier models at scale, you need your own explicit red-line doctrine this quarter — not a vague reliance on vendor defaults or future regulation.
Applied AIClaude Code turned every engineer into three. Now companies need more product thinkers
If Claude Code is effectively tripling engineering output, the constraint shifts from code to conviction—roadmaps, specs, and prioritization become the scarce resource. Teams that don’t rebalance toward product management and tighter discovery will just ship three times more half-baked features.
Applied AIExpect Claude Fable 5 to Be Turned Back on in a Matter of Days, Report Says
If the White House is the venue for turning Claude Fable 5 back on, model gating is now a political and regulatory theater as much as a product decision. Operators should assume frontier capability access can be toggled by policy events, not just vendor roadmaps.