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Writing

agents

Prosecuting the Gates

I practiced what I preach and aimed the lifecycle's own prosecution phase at the toolkit that enforces it. Hardening my own gates surfaced the builder blind spots that normal testing missed—and proved why multi-layered structures, not trust, are the only way to ship reliable agentic software.

· 7 min
llm

Adversarial Review: For All, By All

adversarial-review brings skeptical, model-agnostic code review to your harness as the /adversarial-review skill, and to CI as a zero-dependency CLI. Either way, an independent LLM closes the loop the creator agent cannot close for itself.

· 8 min
agents

Skill Mining: Extracting What Your Codebase Already Knows

Your codebase already encodes how your team builds. Skill mining extracts that latent know-how into reusable agent skills. Here is the loop.

· 14 min
llm

Code Review Is Not Visual Review

AI coding agents are very good at producing working code quickly. The harder problem is whether that code has the right visual shape. I built gemini-plugin-cc to bring Gemini into the workflow as a design-review companion for Claude Code and agent skills.

· 5 min
llm

The Missing Quality Toolkit for Agent Skills

skill-versions solved staleness. But staleness was just the first symptom. Every package ecosystem — CPAN, RubyGems, PyPI, npm, Cargo — eventually builds the same quality infrastructure. Agent skills are just the next language. Meet skills-check.

· 10 min
llm

Your Agent's Knowledge Has a Shelf Life

Your Agent's Knowledge Has a Shelf Life and every day you ignore it, your agents and skills are likely drifting into error land or worse, silent failures. But we have seen this play before and I propose a fix for it. Meet skill-versions.com

· 6 min

The Much Needed Revolution in Machine Learning: Beyond Incremental Improvements

Python's GIL and reference counting can't be solved incrementally. The real revolution in ML infrastructure comes from Rust and Mojo — languages that rethink safety, parallelism, and performance from first principles.

· 8 min

Understanding the Bottlenecks: Python's GIL and the Limitations of Current ML Infrastructure

The Hidden Roadblock in Python's Core At the heart of Python's architecture lies a mechanism that most developers rarely think about until it becomes a performance bottleneck: the Global Interpreter Lock (GIL). This seemingly innocuous component has profound implications for machine learning worklo...

· 8 min
data

The Evolution of Machine Learning: Why Performance Now Matters More Than Ever

As machine learning models grow to trillion-parameter scale, performance optimization becomes critical. Traditional tools like Python now create bottlenecks, driving the shift toward High-Performance Machine Learning.

· 4 min
digital-transformation

The Reality of Generative AI: How Poor Data Practices Are The Real Roadblock to Digital Transformation

Unlock business innovation with generative AI by overcoming data challenges. Learn key strategies for effective data management, quality, and governance to enhance decision-making and drive success. Dive into our guide on building a solid data foundation for AI transformation.

· 7 min

Why an AI Strategy is the Game-Changer for Small and Medium-Sized Businesses

The digital revolution of the 21st century has amplified the capabilities of businesses across the board. But a new era is upon us—the AI revolution—and it's reshaping the competitive landscape in a way that overwhelmingly favors small and medium-sized businesses (SMBs) over their enterprise behemot...

· 9 min

Optimizing PostgreSQL for Scale: An In-Depth Guide for Developers

Introduction In today's digital landscape, data is the new gold. It's not only about how much data you have, but how efficiently you can manage, retrieve, and analyze it. At the heart of this data revolution is the database, and PostgreSQL, often affectionately termed "Postgres," stands tall as on...

· 39 min