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Essays, experiment logs, and technical notes across AI governance, reasoning systems, BioAI, and engineering practice.
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95% of AI Businesses Will Die. Here’s How to Not Be One of Them.
What the data, a founder’s confession, and 70 years of tech history tell us about who actually survives.
Is MCP Really Dead? A History of AI Hype — Told Through the Rise and Fall of a Protocol
When a protocol doesn’t die — it just stops being interesting. A forensic look at MCP, OpenClaw, and the psychology of AI hype cycles.
Beyond AI FOMO — From Tulip Mania to OpenClaw 2026: The Governor That Saves You
The real breach wasn’t in the code. It was in you.
The AI Flight Crash: Why 2026’s Hottest Papers Can’t Take Off — and what actually ships
Langley spent $50,000 and sank — the Wright Brothers flew for <$1,000. Here’s a 4-week build plan I’ve seen actually ship.
AI Isn’t Killing Your Expertise. It’s Just Moving the Paywall.
Why ‘Writing Faster’ Is Worthless When Nobody Can Verify What’s True
When the Michelin Recipe Fails in Your Kitchen
Why 2026 Marks the End of DIY AI — and the Rise of the AI Meal Kit
When AI Becomes a Toy
Why the Current AI Craze Was Inevitable — and Why It Cannot Be the Endgame
2026 AI Adoption from Miracle to Air
AI won’t go mainstream in 2026 because models get smarter. It’ll happen when AI becomes “air” - default, standardized, and liability-owned.
Silence is a Debt. Visibility is Liquidity.
In an AI market flooded with repos, invisibility compounds like debt. Learn the two models that explain why proof alone doesn’t convert into opportunity.
Now Is the “Early, Messy Renaissance” of AI — Reading 2025 from a Florentine Workshop
Is AI a bubble or a renaissance? A practical playbook for founders and AI teams to move beyond hype with metrics, reproducibility, and real results.
🧭 The Path to AGI: 5 Thresholds No One Talks About
AGI isn’t science fiction anymore—discover the five critical thresholds AI systems must cross to evolve from code into true general intelligence.
The AI Bubble and the Builders Who Break It
Why the AI bubble persists — hype, misaligned incentives, and closed research — and how an outsider approach of quantifying ethics, shipping code, and collaborating with AI offers a different path.