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…
Category: Software Development
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…
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…
From Waterfall to ADD: Why AI Demands Its Own Methodology
Software development methodologies do not emerge from academic theory or conference talks. They emerge from pain. Practitioners encounter problems that existing approaches cannot solve, and they develop new disciplines to address those problems. Understanding this history matters because AI-assisted development is at an inflection point. The unstructured approaches I described in my previous post are…
The Unstructured AI Problem: Why Most Teams Are Using AI Wrong
Every developer I know uses AI tools now. Copilot suggestions appear mid-keystroke. ChatGPT tabs stay permanently open. Claude conversations stretch across multiple projects. The adoption curve was vertical, faster than any technology shift I have witnessed in two decades of software engineering. But here is the uncomfortable truth: most of us are using these tools…
The Future Engineer: What Software Development Looks Like When AI Handles the Code
The software industry has entered a period of genuine transformation. After decades of incremental tooling improvements, AI-assisted development is introducing changes that feel qualitatively different from what came before. Code completion, automated testing, and intelligent refactoring are no longer experimental features but daily realities for many developers. This shift raises uncomfortable questions about the future…
Code Is for Humans, Not Machines: Why AI Will Not Make Syntax Obsolete
With AI, “everybody is a programmer.” You do not need to learn syntax anymore. Just describe what you want, and the machine will write the code for you. If you have spent any meaningful time in this profession, you are probably laughing right now. Or at least shaking your head. This narrative has become extraordinarily…
The Eternal Promise: A History of Attempts to Eliminate Programmers
When I look back at the history of software, one pattern emerges with remarkable consistency: the promise to simplify software creation, to make it cheaper, and ultimately to eliminate the need for programmers altogether. This is not a new idea. It has been the driving ambition of our industry since the 1960s. And while each…
AI-Powered Fixed-Cost Development: A New Model for Agencies
Software development has always carried an uncomfortable truth: nobody really knows how long it will take. Clients want certainty. They want a number, a deadline, a budget they can plan around. Agencies and independent consultants want to deliver that certainty, but they have learned through painful experience that software estimation is more art than science….