Writing Hub
AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
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When AI Becomes a Toy
Why the Current AI Craze Was Inevitable — and Why It Cannot Be the Endgame
Built a SaaS in 30 Minutes? When “No-Code Hype” Meets the Operational Wall
Where no-code hype hits the operational wall: auth, billing, security, cost.
I Stopped Being a Human Copy-Paste Script
I used to manually delete node_modules at 2 AM and pray I didn’t leak secrets to LLMs. Then I built an open-source “Inspector” that treats context like production code — secrets blocked, payloads cleaned, hallucinations gone. Here’s exactly how I did it (and how you can too).
Running the “Anti-AI” Playbook Through the Debugger
Critics say AI is broken — hallucinations, hype, and no ROI. But what if those bugs aren’t failures, but blueprints? This article runs the 10 most common anti-AI arguments through the debugger to reveal what’s really coming in Gen-2 AI.
Black Mirror: Plaything — Could a QR Code Really Hack the World?
Black Mirror imagines a QR-code apocalypse. As a Flame Glyph developer, I unpack what’s plausible today — local device disruption — and what remains fiction.
Structure Was the Real Bug — How I Ended Up Building dir2md
A firsthand account of how debugging chaos, failed AI assistance, and the absence of structure led to the creation of dir2md — an open-source CLI that filters, secures, and restructures codebases into token-efficient Markdown maps for developers and AI workflows.
Flame Glyph: How I Taught AI to Remember with QR Codes
What if AI didn’t just read—but remembered? Flame Glyph turns QR codes into memory seals, enabling multimodal recall hidden in plain sight.
🧠 Why Your 128K Context Still Fails — And How CRoM Fixes It
Most large language models fail in long prompts due to context rot. CRoM is a lightweight framework that improves memory, reasoning, and stability without heavy pipelines.
Can an AI Model Feel Meaning? — A Journey Through Self-Attention
Can an AI model truly grasp meaning? This in-depth essay explores the evolution of Large Language Models, the power of self-attention, and the emerging signs of machine intentionality — asking not just how AI works, but what it might be becoming.
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