Field notes, essays, and methodology from building software with AI daily.
AI-assisted development is not a trend or a shortcut. It is a fundamental change in how software gets made, and if you are building software right now, you are already in the middle of it whether you have chosen to be or not.
I started writing about this in earnest in mid-2025 after spending six weeks working almost exclusively in agent mode. What I found surprised me. The productivity gains were real, but they were secondary. The bigger story was cognitive: working alongside AI changes how you think about problems, how you scope work, how you evaluate what is worth doing yourself and what is worth delegating. These are not minor adjustments. They are architectural changes to the development process.
The essays collected here are field notes from that ongoing experiment. They cover the workflows that actually work, the failure modes no one warned me about, the cognitive side effects of working at machine speed, and what it looks like when you apply these patterns to real infrastructure, real content pipelines, and real business software, not demos and toy projects.
One consistent theme: AI-assisted development requires more engineering judgment, not less. The models can write code. They cannot decide what to build, catch the architectural mistake that compounds into a rewrite six months later, or know when good enough is actually good enough. That judgment remains human work. The goal is to free up time and cognitive load for it.
Start with the complete series overview if you want the full arc. Or pick any single essay if you have a specific question. They are written to stand alone as well as build on each other.
The full series in one place, from the first shock of working alongside AI to building autonomous agents, infrastructure, content pipelines, and business apps. If you read one thing, start here.
A clear-eyed look at what separates deliberate AI-assisted development from prompting-and-hoping. The distinction matters more as models get more capable, not less.
What happens to your thinking when you work alongside AI for six weeks straight. The cognitive changes are real, unexpected, and worth examining.
The moment everything changed, from using AI as a fancy autocomplete to treating it as a collaborator with its own strengths and failure modes.
The workflow patterns that actually stick. How to structure prompts, manage context, and build a feedback loop that makes AI collaboration sustainable.
AI doesn't just write application code. When you apply the same patterns to infrastructure, Dockerfiles, CDK stacks, CI pipelines, the leverage multiplies.
How AI changes the economics of content creation: OCR pipelines, automation scripts, publishing workflows, and keeping the human voice central.
From trading dashboards to membership platforms, applying AI-assisted development patterns to real business software with production requirements.
Where this is heading. The economic and professional implications of AI-assisted development at scale, for individual developers, teams, and the craft itself.
The techniques that emerge after months of practice: multi-agent orchestration, context management at scale, architectural decision-making with AI.
A Beginner's Companion to the AI Frontier
If you want these ideas in a single readable volume, AgentSpek is the book version. It covers the full arc, from first contact with AI tools to working in full agent mode, with personal stories, practical prompts, and a structure designed for developers who want to actually use this stuff, not just read about it.
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