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AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
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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.
The Repo Is Right There. Why Are You Checking Their CV?
In 2026, AI researchers and engineers use the same words to mean opposite things. This is not a communication problem. It is an incentive problem with a vocabulary leak and it's where most AI projects actually fail.
My LLM Kept Forgetting My Project. So I Built a Governance Schema.
Session loss isn't a UX inconvenience — it's a structural failure with compounding consequences for long-running AI projects. This post defines the problem precisely and introduces MICA, a governance schema for AI context management.
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.
How do you know when your entire AI pipeline is wrong — not just one model? (EXP-033)
EXP-033 shows how to validate an entire AI pipeline, not just one model, using five-gate checkpoints, reproducible PASS/BLOCK parity, AlphaGenome on/off testing, and fully traceable governance decisions.
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.
What an AI Reasoning Engine Built for Alzheimer's Metabolic Research: A Code Walkthrough
A code walkthrough of an AI reasoning engine for Alzheimer’s metabolic research, showing how literature ingestion, causal inference, and executable biomarker scaffolds generate falsifiable pre-validation hypotheses.
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.
Prompt, Pray & Push: Why Your AI Agent Keeps Failing You
The one concept that turns expensive spaghetti into great agentic engineering.
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