BTL Topic index
A living archive
AI Governance
Policy, ethics, safety, and the human questions around AI deployment.
The working lens
Look for the system beneath the story.
Ideas earn their place here by being useful after the presentation ends and the real work begins.
01 Follow the consequences
02 Keep people in the system
03 Test it against reality
The working index
Ideas worth carrying into the work.
Start with the lead essay. Then follow whichever question feels most useful now.
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Physical AI Isn’t a Shortlist. It’s a Sequence.
Open article ↗: Physical AI Isn’t a Shortlist. It’s a Sequence.Read or skip? For enterprise architects and delivery leads deciding where physical AI lands first. If you’re tempted to pilot whatever sits at the top of Deloitte’s chart,…
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AI May Make Work Feel Faster Without Making It Faster
Open article ↗: AI May Make Work Feel Faster Without Making It FasterAI can cut the effort a task takes without cutting the time it takes — and that gap quietly distorts how we judge productivity.
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When Networks Become Players
Open article ↗: When Networks Become PlayersA Beta Tester Life review of Sungwook Kim’s Game Theory for Intelligent Network Control Paradigm, and why autonomous infrastructure needs incentive design.
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The Next Workplace Conflict Is Not Human vs AI
Open article ↗: The Next Workplace Conflict Is Not Human vs AIThe real workplace divide forming under AI is not between people and machines. It is between the people who are managed by algorithms and the people who manage…
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Hyperadaptive Is a Blueprint for Rewiring the Enterprise Around AI
Open article ↗: Hyperadaptive Is a Blueprint for Rewiring the Enterprise Around AIA Beta Tester Life review of Melissa M. Reeve’s Hyperadaptive, exploring AI-native operating models, enterprise rewiring, and adaptive leadership.
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AI Coding Has Moved the Bottleneck From Creation to Verification
Open article ↗: AI Coding Has Moved the Bottleneck From Creation to VerificationAI coding assistants speed up creation, but the real engineering bottleneck is now review, correction, testing, and trust.
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From Operators to Orchestrators — The Infrastructure-Value Gap Is Now Visible
Open article ↗: From Operators to Orchestrators — The Infrastructure-Value Gap Is Now Visible📊 Read or skip? Read. If you are still measuring success in uptime, velocity, or tickets closed — you are likely missing where value is actually created. Why…
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Boeing, AI, and the Accountability Model You Haven’t Upgraded Yet
Open article ↗: Boeing, AI, and the Accountability Model You Haven’t Upgraded YetMIT Sloan’s ‘narrative responsibility’ framework uses Boeing’s decade of safety failures to expose why the 1980s accountability playbook is structurally broken in a 2026 AI-enabled organisation — and…
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NIST’s Trustworthy in AI Critical Infrastructure
Open article ↗: NIST’s Trustworthy in AI Critical InfrastructureOn April 7, 2026, NIST released a concept note for an AI RMF Profile on Trustworthy AI Critical Infrastructure. I’ve read the note. I’ve read the coverage. I’ve…
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Why 95% of AI Projects Fail – And the Evaluation Tools Changing That
Open article ↗: Why 95% of AI Projects Fail – And the Evaluation Tools Changing ThatMIT research shows 95% of enterprise AI projects deliver zero returns. Discover how AI evaluation tools like Braintrust, Arize, Galileo, and Fiddler are helping the 5% succeed.
Change the lens
The useful questions refuse to stay in their lane.
Move sideways through the archive. The strongest connections often appear between categories.
Still carrying a question?