Writing Hub
AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
Project Topics
AI Can Write the Code. It Still Cannot Place the Stone.
AI can now write code, patch files, and finish releases. But a real case from an AI-assisted release shows that the harder human work may be deciding what the system should expose, which output belongs to which reader, and how agent-generated work remains inspectable after the code is written.
When the Memory Gate Met a Real Archive: What 90 Experiments Taught Us About Cheap LLM Slop
How to enforce data integrity against AI-generated slop using MICA. Explore a 11-step session-start validator that locks rules, playbooks, and contracts in code before code is ever touched.
The Two Problems No One Talks About in AI Agent Coding Pipelines
AI agent coding pipelines fail not because models are weak, but because verification is structurally broken. This article identifies four empirically documented failure mechanisms — agreement bias, latent entanglement, echoing, and right-for-wrong-reasons — and proposes a concrete architecture: hash-chained audit records, hybrid recurrence scoring, dynamic context budgets, and evidence-first review across three independent axes. Covers multi-agent pipeline design, agentic code review, blueprint indexing, and P0–P4 governance gates.
Stanford. Princeton. A bioRxiv Paper. So Why Did Nobody Ask Where the Data Goes?
BioClaw processes EHR data. Its primary showcase channel is WhatsApp. We audited the repository: 60/100, Tier 2 Caution. Here is what the bioRxiv paper says that the README does not.
The README Was a Protocol. The Entrypoint Was Still Optional.
README-as-Protocol solved explicit invocation at the schema level. It did not solve entry control at the workflow level. This version adds the missing hierarchy: natural, guided, and forced activation.
From Repo Scanner to Audit Architecture: What Changed in STEM BIO-AI Through v1.7.8
A technical look at how STEM BIO-AI v1.7.8 became less Python-shaped, more semantically stable, and more inspectable across real audit output surfaces.
The Meeting Nobody Could Follow -The format of AI output is a design decision. We made it wrong for three years.
How our engineering team stopped sending 200-line Markdown files that nobody read — and what a nine-word post from an Anthropic engineer taught us about AI output format as a design decision. Includes token cost analysis, real prompt templates, and the HTML render layer approach used in production.
STEM-BIO-AI Audit Report: yorkeccak/bio
When a README Claim Meets a Deterministic Scanner
The Alchemy of Ego - How AI Turns Unfinished Thought Into Fluent Certainty
A personal essay on how AI can turn unfinished thoughts into fluent certainty, why internal coherence is not external proof, and why falsifiability, failure conditions, and visible execution matter in AI-assisted thinking.
How Do You Trust the AI Auditor? STEM-AI v1.1.2 and Memory-Contracted Bio-AI Audits
STEM-AI v1.1.2 binds a bio/medical AI repository audit to a machine-checkable memory contract, then demonstrates it on a real open-source bioinformatics repository.
The Sheepwave Has a New Shape: OpenMythos and the Rise of Architecture Hype
A technical-opinion essay on OpenMythos, Claude Mythos, README-driven AI hype, and why architecture claims need source-level verification before becoming public belief.
The Difference Between a Harness and a Leash
A practical essay on why most AI 'harnesses' are still leashes: guides shape behavior, but only justified external measurement creates a real governance boundary.
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