A week ago my blog post got noticed by developers. I got so many messages and there was a recurring theme. They feel helpless and anxious with the ever growing AI dominance in writing code that might not be perfect but it is almost good enough in many cases. But one question stood out more…
Category: Software Engineering
The Training Data Paradox: What Happens When AI Replaces the Engineers Who Trained It
There is a question hiding in plain sight behind every celebration of AI-generated code, every prediction that developers are obsolete, every LinkedIn post about building an app 100x faster with a prompt. It is a question that almost nobody in the current hype cycle is asking, and it may be the most important question of…
Software Companies Are Dead. Just Nobody Told Them.
Software companies are dead. Just nobody told them. Or so everyone keeps saying. LinkedIn is flooded with Claude Code hype. Cursor is “changing everything.” Every founder on your feed is screaming that developers will be redundant by Q2. The revolution is here, they say. Pack your bags. This is now the third consecutive year of…
ADD in Context: Greenfield, Legacy, Refactoring, and Testing
The ADD cycle is consistent across contexts: Specify, Generate, Evaluate, Integrate. But how you apply each phase changes depending on what you are building and where you are building it. Greenfield projects offer freedom that legacy codebases do not. Refactoring has constraints that new feature development lacks. Test generation inverts the typical flow. This post…
No, Average People Will Not Build Their Own Software With AI
There is a narrative gaining traction in tech circles, on social media, and in breathless conference keynotes that goes something like this: AI will soon let anyone build their own software. Need a budgeting app? Just describe it to an AI and it will create one for you. Want a custom CRM for your small…
Architect or Extinct: Why Software Developers Must Evolve Beyond Writing Code
A house architect does not lay bricks. They do not mix concrete, install plumbing, or wire electrical panels. They design the building. They decide how spaces connect, where light enters, how loads distribute, and how the structure will age over decades of use. The actual construction is performed by skilled tradespeople following the architect’s plans….
Integrate: Completing the ADD Cycle for AI-Driven Development
Code that passes evaluation is ready for integration. This is the final phase of the ADD cycle, where generated code becomes part of your system. But integration is more than merging a pull request. It is where AI-generated code meets the full reality of your codebase, your testing infrastructure, your deployment pipeline, and your team’s…
Evaluation Checklists: Building Your Quality Gate for AI Code
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…
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…