LLMs generate code on demand, but they do not replace maintainers, communities, or years of shared learning. This piece explores how AI-assisted coding risks fragmenting logic, increasing technical debt, and slowly eroding the open source ecosystem.
AI adoption fails when treated as a tool rollout. This guide covers the decision framework, team dynamics, economics, and mistakes from 150+ technical audits.
Vibe coding or AI-assisted development? The choice isn't binary, but getting it wrong at the wrong stage will cost you. This piece breaks down when to embrace speed over architecture, when to take back control, and why the best teams don't pick sides.
AI coding agents draft code, write tests, and open pull requests autonomously. This guide covers the tool landscape, readiness signals, a phased rollout plan, and the team dynamics that make or break adoption.
AI code review catches what humans miss and misses what humans catch. This guide compares the tools, shows what each catches, and walks through setup without replacing human judgment.
If you believe what you see on LinkedIn, startups don't need employees anymore, real founders just have agents building their companies. You write a prompt, fire off the agent, and wait for customers. In reality, you get a vague workflow that produces a mediocre demo at best.
In the first of a series exploring infrastructure fundamentals, Brenden addresses the most frequently asked questions about what's really happening under the hood with complex pipelines and AI/data systems, bringing the cloud to life.
What will the state of AI be like in a year's time? Here are Mike Veerman's predictions of what major things will happen next in AI
I switched from Cursor's BugBot ($40/month) to Claude Code for code reviews. Setup is straightforward in VS Code, and Claude's bug detection has been notably better. While it still flags null reference checks like most AI reviewers, the difference in catching actual bugs is significant.