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.
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.
Shiny frameworks promise magic, but like cheap non-stick pans, they scratch, peel, and end up in the bin. Boring technology, like stainless steel, isn’t sexy, but it lasts for decades if treated well. The lesson? Build for the long haul, not the quick thrill.
What can investors do about legacy code to prevent your startup from failure? What is the difference between legacy and technical debt?
Evaluating the cost of rebuilding software from scratch involves more than counting development hours; it requires recognising the invisible value of user feedback, lessons learned, and embedded experience.
Should engineers fear messy AI code or embrace it as a tool for fast product validation? This story reveals why your cleanest code might not be your most valuable contribution. Why founders will use AI generated code more and more for MVPs and prototyping and why engineers should embrace this.
Why do engineering teams keep rewriting frontends? Let’s explore the leadership bias and tech churn that makes refactors feel harder—yet ultimately more sustainable.
Forced API migrations without a rollback plan? That’s how businesses lose trust—and money.
Balancing innovation with stability is key in managing SaaS legacy code. You explore phased implementations, leveraging existing assets, and continuous learning to maximize legacy code potential. Ideal for tech leads and founders.