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AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
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My AI Maintainer Kept Making Wrong Calls. So I Made It Report Its State Before Touching Anything.
Part 6 moves from landscape to operation. This is what MICA looks like when it is actually running inside a real maintenance workflow — session report, self-test, drift, invariants, and operator judgment.
Prompt → RAG → MCP → Agent → Harness, and What?
Why the next layer in AI may be governance infrastructure, not just better agents.
The Harness Is the Product: What the Claude Code Leak Actually Revealed About AI Agent Architecture
The Claude Code leak exposed more than source. It revealed that modern AI agent performance depends heavily on the harness around the model.
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.
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.
Bio-AI Repository Audit 2026: A Technical Report on 10 Open-Source Systems
We audited 10 prominent open-source Bio-AI repositories using code inspection and STEM-AI trust scoring. 8 of 10 scored T0: trust not established. Here is what the code actually shows.
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
The Stake Was Governance Outside the Schema. MICA v0.1.5 Pulled It In
v0.1.0 through v0.1.4 made the schema more implementable. v0.1.5 was the first version to ask a different question — what if governance itself belongs inside the schema? Here is what that looked like, and what it still could not do.
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.
The Schema Existed. The Model Had No Way to Know.
v0.0.1 proved that context could be structured. It did not prove that the structure could govern what shaped the session. Three failures — and why only one made the others meaningless.
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.
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