The best automation is the script you wrote once and forgot about. Until you realize you’d be miserable without it. That’s the bar I hold every workflow script to: will this save me more time than it took to write? Most “productivity automation” content you find online fails that test. The scripts look clever in a conference talk, end up in your dotfiles, and collect dust. They solve hypothetical problems, not real ones. ...
This post continues “The Centaur’s Toolkit” series on practical human-AI collaboration in technical work. The error showed up in production on a Wednesday afternoon. sqlalchemy.exc.OperationalError: (psycopg2.OperationalError) SSL SYSCALL error: EOF detected I knew this error. Or thought I did. Stack Overflow had dozens of answers: upgrade psycopg2, check your SSL certificates, adjust your connection timeout. I’d even hit this error two years earlier on a different project, and the fix had been a connection pool configuration change. ...
This is Part 5 of “The Centaur’s Toolkit” series, where we explore practical strategies for human-AI collaboration in technical work. A new AI coding tool launches every week. Actually, that’s an understatement. Multiple tools launch every week, each promising to revolutionize your workflow. Each one has a Twitter thread explaining why it’s better than what you’re using now. If you tried to evaluate every new tool, you’d never write any code. ...
This is Part 4 of “The Centaur’s Toolkit” series, the finale. We’ve covered collaboration fundamentals, security applications, and calibrating trust. Now we tackle the question that ties it all together: is this actually working? You’ve been using AI as your coding partner for three months. You feel faster. More productive. Like you’re getting more done in less time. But feelings lie. That sense of productivity might be real. Or it might be the satisfaction of constant activity masking the fact that you’re shipping buggier code, accumulating technical debt, or slowly losing skills you used to have. ...
This is Part 3 of “The Centaur’s Toolkit” series. We’ve covered AI pair programming fundamentals and building AI-assisted security tools. Now we tackle the hardest skill: knowing when to trust what AI tells you. Last week, I asked an AI to help me understand a library I’d never used. It gave me a confident, detailed explanation of the validateSchema() method, complete with parameter descriptions and example usage. The method doesn’t exist. The AI invented it. The explanation was coherent, the examples looked plausible, and if I hadn’t tried to actually use the code, I might have wasted hours debugging a function call to something that was never real. ...