Writing Hub
AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
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What Anthropic’s 81k Survey Reveals About What the AI Market Still Gets Wrong
Users Don’t Want Faster AI — They Want AI That Helps Them Live Better Without Losing Their Humanity.
After Auditing 10 Bio-AI Repositories, I Think We're Scaling the Wrong Layer
After auditing 10 open-source Bio-AI repositories, one pattern stood out: the field is scaling packaging faster than verification. Here is what that gap actually costs.
I Audited 10 Open-Source Bio-AI Repos. Most Could Produce Outputs. Few Could Establish Trust.
I audited 10 visible repositories. Most could produce outputs. Very few could establish what those outputs meant.
Everyone Was Talking About Context Engineering. Nobody Had Solved Governance.
Everyone Was Talking About Context Engineering. Nobody Had Solved Governance.
The Model Already Read the README. MICA v0.1.8 Made It a Protocol
v0.1.7 made scoring a contract with fail-closed gates. v0.1.8 recognized that README-first behavior could serve as invocation — and formalized it as a schema-level protocol. This article uses simplified examples to show how the invocation gap that had existed since v0.0.1 was finally closed
Medical AI Repositories Need More Than Benchmarks. We Built STEM-AI to Audit Trust
STEM-AI is a governance audit framework for public medical AI repositories. It scores README integrity, cross-platform consistency, and code infrastructure — because benchmarks alone don't tell you if a bio-AI tool is safe to trust.
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.
I Built an Ecosystem of 46 AI-Assisted Repos. Then I Realized It Might Be Eating Itself.
An ecosystem of 46 AI-assisted repos can become a closed loop. This article explores structural blind spots, self-validating toolchains, and the need for external validators to create intentional friction.
What AI Changed About Research Code — and What It Didn’t
The old bottleneck was writing the code. The new bottleneck is proving that the code still means what the theory meant.
From Fail-Closed Blocking to Reproducible PASS/BLOCK Separation (EXP-032B)
A validation study showing how EXP-032B achieved reproducible PASS/BLOCK separation across A/B/C control arms by patching false-blocking causes, improving observability, and measuring replay drift under observer-shadow conditions.
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.
When AI Models Fight, Truth Wins: The “Eureka” Moment for Tired Researchers
To the grad student staring at a pLDDT of 90 and wondering why the ligand won’t bind.
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