In the previous post, I covered the five dimensions of evaluating AI-generated code: correctness, fitness, security, performance, and maintainability. Understanding these dimensions is essential. But understanding is not enough. Under time pressure, even experienced developers skip evaluation steps. They focus on the dimensions they find most interesting or most familiar, and they neglect the others….
You Don’t Want a Claude Code Guru
The job posting practically writes itself these days. “Looking for a senior developer proficient with AI coding tools. Must be comfortable using Claude Code, Cursor, or Copilot to rapidly produce production-ready code. We need someone who can 10x our output.” I have seen variations of this everywhere over the past year. Companies scrambling to find…
An Honest Take on Deploying Rails with Kamal: What Works and What Doesn’t
Kamal has been positioned as the answer to a question Rails developers have asked for years: how do you deploy to your own servers without the overhead of Kubernetes or the cost of a managed platform? And in many ways, it delivers. But the gap between what Kamal promises and what it actually requires in…
The New Bottleneck: Why Clarity Matters More Than Code
For two decades, the fastest engineers were the ones who could write code quickly. They knew the shortcuts, the patterns, the frameworks. Their fingers moved faster than their competitors. That era is ending. The new bottleneck isn’t your typing speed or your syntax recall. It’s your clarity. I’ve spent twenty years building software, leading teams,…
Evaluate: Why Human Judgment Is Non-Negotiable
We have arrived at the phase of ADD where the most important human skill comes into play. You have written a specification. You have generated code using appropriate context and patterns. Now you must determine whether that code is actually correct. This is not a formality. AI-generated code can be syntactically correct, pass basic tests,…
Prompt Patterns Catalog, Part 2: Iteration, Verification, and Persona
In the previous post, I introduced three foundational prompt patterns: Decomposition for breaking complex tasks into manageable units, Exemplar for teaching by example, and Constraint for defining boundaries. These patterns address the most common generation challenges. This post completes the catalog with three more patterns, then addresses the practical question of building and maintaining a…
Prompt Patterns Catalog: Decomposition, Exemplar, Constraint
Software developers are familiar with design patterns. The Gang of Four cataloged reusable solutions to recurring problems in object-oriented design. You learn patterns like Strategy, Observer, and Factory not because they are theoretically interesting but because they solve problems you encounter repeatedly. Once you know the pattern, you recognize the problem and reach for a…
Generate: The Art of Effective AI Collaboration
Generation is where the visible work happens. You provide input, and the AI produces code. This is the moment most developers think of when they imagine AI-assisted development. It is also where most developers start, jumping directly to generation without the specification work that should precede it. In the ADD cycle, generation is the second…
Specification Templates: A Practical Library for AI Development
In the previous post, I made the case that specification is the highest-leverage skill in AI-driven development. A precise specification produces better output, requires less iteration, and surfaces ambiguity before it becomes a bug. But writing detailed specifications from scratch is cognitively demanding. You must simultaneously consider functional requirements, constraints, context, edge cases, and integration…
The Quiet Builders: A History of Introverts in Engineering and What AI Means for the Future
Throughout human history, there has always been a place where the quiet ones could excel. A domain where deep thinking mattered more than small talk, where careful analysis outweighed charisma, and where the quality of your work spoke louder than the volume of your voice. That place has been engineering. From the mathematicians of ancient…