Writing

Thoughts on AI, software engineering, and how systems are becoming intelligent.

I write to understand ideas better — and to make them clearer for others working with or around these systems.

Choose Your Path

Start with the reader path closest to what brought you here.

Path 01

New to AI concepts

Start with plain-English foundations for AI, machine learning, LLM systems, and the wider AI ecosystem.

Path 02

Using AI coding assistants

Follow the ordered software engineering series on context, repositories, review, agents, and orchestration.

Path 03

Leading AI adoption

Read about context, knowledge debt, process, evidence, and the operating model changes behind useful AI adoption.

Path 04

Exploring practical systems

Jump to system stories, workflow experiments, demos, and practical builds connected to the writing.

Start With the Main Series

A structured reading path for software engineers working with AI assistants.

Practical guide

AI-Assisted Software Engineering

Context, codebases, work systems, reviews, agents, and orchestration — a practical path through AI-assisted software engineering.

9 articles · Software engineering · AI-assisted era

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Recommended Starting Points

A manually curated set of strong entry points for first-time readers before going deeper into the clusters below.

AI and Software Engineering

Business Rules as Context: The Missing Layer in AI-Assisted Development

AI assistants can read the code. They can read the ticket. That still may not tell them what the software is allowed to do.

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AI and Software Engineering

Knowledge Debt Is the New Technical Debt

Technical debt makes code harder to change. Knowledge debt makes the system harder to understand.

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AI and Software Engineering

Documentation Is Becoming Executable Context

How AI-assisted software work is changing documentation from a passive reference into an active part of delivery.

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Topic Clusters

Browse the writing by theme. These are topic groupings, not date-based feeds or separate series.

Topic cluster

AI Foundations

Begin here if you want the concepts behind AI, machine learning, data science, and LLM systems explained without hype.

Topic cluster

AI-Assisted Software Engineering

Practical essays on the context, repository structure, prompts, and review habits that make AI-assisted delivery more reliable.

Topic cluster

Engineering Context and Knowledge

How business rules, documentation, standards, and organizational knowledge become usable context for humans and AI assistants.

Topic cluster

AI Agents and Review

Practical judgment for using AI assistants, reviewing generated work, assigning tasks, and coordinating agent-like workflows.

Topic cluster

Review and Governance

How teams review AI-assisted work, evaluate evidence, scale scrutiny with risk, and keep human accountability visible.

Topic cluster

Agile, Process, and Engineering Leadership

For architects and leaders thinking about AI adoption, delivery systems, process quality, evidence, and engineering standards.

Topic cluster

Systems and Experiments

Articles connected to practical builds, workflow experiments, and system-level explorations. The deeper build notes and demos live in Systems.

Writing to systems

Looking for the practical builds?

The Writing page explains the ideas and tradeoffs. The Systems section shows applied experiments, demos, architecture notes, and working examples.

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Latest Writing

Recent articles for returning readers, listed by publication date.