Writing Hub
AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
Project Topics
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.
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.
From 97% Model Accuracy to 74% Clinical Reliability: Building RSN-NNSL-GATE-001
Learn how RSN-NNSL-GATE-001 turns high model accuracy into system-level clinical reliability by blocking unsafe AI pipeline decisions, measuring end-to-end risk, and enforcing fail-closed governance.
When Adding Chai-1 and Boltz-2 Exposed Hidden Model Disagreement(Trinity Protocol Part)
See how adding Chai-1 and Boltz-2 to an AlphaFold workflow exposed hidden model disagreement, increased drift, and revealed why failed convergence can be the most valuable signal in computational biology.
Orchestrating AlphaFold 3 & 2 with Python: Handling AI Hallucinations using Adapter Patter (Trinity Protocol Part 1)
Learn how to orchestrate AlphaFold 3 and AlphaFold 2 with Python using the Adapter Pattern to detect AI hallucinations, measure structural drift, and improve protein prediction reliability.
When the Michelin Recipe Fails in Your Kitchen
Why 2026 Marks the End of DIY AI — and the Rise of the AI Meal Kit
Turning a Research Paper into a Runnable System
Turn a research paper into a runnable system. This article shows how HRPO’s core equations were implemented with bounded policy lag, KL rejection, and execution checks to test real-world fidelity.
My Code Fixed Itself at 11PM
A “Quantum Engine” is a dramatic name. Here’s the un-dramatic story.
The Paper That Runs Itself: Why AI-Era Research Must Be Code-Native
Literate Programming, DevOps for Research, Research Infrastructure, Continuous Integration, AI Transparency, Scientific Publishing, arXiv Culture
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