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Essays, experiment logs, and technical notes across AI governance, reasoning systems, BioAI, and engineering practice.
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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.
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.
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.
Chaos Engineering for AI: Validating a Fail-Closed Pipeline with Fake Data and Math
A case study in AI governance showing how synthetic invalid inputs, structural disagreement, SIDRCE ethics checks, and end-to-end reliability scoring triggered a safe BLOCK verdict in a biomedical pipeline.
The Pull Request Illusion: How AI Is Hollowing Out Software’s Last Line of Defense
GitHub Just Added a Switch to Turn Off Pull Requests. That’s Not a Feature. It’s a Warning.
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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