Why Perception of Productivity Matters as Much as Actual Productivity
Technical improvements fail when teams don’t perceive productivity gains. Great teams align actual productivity with perception of productivity through disciplined practices.
The Discipline Dividend: Why Boring Discipline beats Exciting Tools
Software engineering chases exciting tools over boring measurement discipline. But organizations achieving sustainable productivity gains embrace systematic practices that generate reliable data and build institutional knowledge. The competitive advantage isn’t the most innovative tools—it’s consistently measuring what matters in your specific context while competitors chase trends.
What 160 Minutes of AI Debugging Taught Me About AI-Coding tools
Este articlulo es una mirada al aprendizaje de trabajar un mes codificando con AI.
The Bias Problem: Why We Can't Trust AI Productivity Claims
When observing AI productivity claims, we need to be able to judge the objectivity and skin in the game of our sources.
The Math Behind AI Code Assistants: Why 50% Productivity Gains Don't Add Up
AI code assistants promise revolutionary productivity gains, with some vendors claiming 50% or higher improvements in developer output.
In this post I do a simple sanity chack ROI to show that the numbers do not add up!
The $12 Billion Tools Paradox: More Tools Don't Equal More Prodcutivty
The Code generation tool market is projected to grow to $12 billion by the end of 2028.
But what is the real impact on productivity?
Welcome to the Age of tools
The post reflects on the evolution of software development, highlighting three key eras: the Age of Process, the Age of People, and the current Age of Tools. It emphasizes the importance of discipline and a balanced approach, combining people, processes, and tools, to navigate challenges and achieve high-quality software development effectively.