AI didn't change the economics of software engineering
AI made writing code faster, but the real economics of software engineering were never about typing code in the first place.
Team dynamics
111 posts
A founder's commitment to their engineering team
Founders juggle endless demands, investors, sales, suppliers, and employees, all while building the plane mid-flight. But with engineering often being your biggest expense, there's one responsibility you can't delegate: ensuring your team builds the right thing.
Communicate or be micromanaged - the CTO edition
CTOs often come from engineering backgrounds and, particularly when newly promoted, tend to focus on what they know best, the technology. While this is understandable given their previous success, technology is rarely the hardest part of the CTO role.
The full-stack enigma
Early-stage startups want full-stack unicorns who can do it all on a tight budget, but asking one dev to wear every hat is less strategic hiring and more duct-taping a rocket and hoping for the best.
A guide to vibe coding vs AI-assisted development
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.
Your startup does not need more engineers, it needs fewer mistakes
Hiring to fix velocity often multiplies your problems. Reduce avoidable mistakes first: tighten decision-making, align product and engineering, and put foundations in place that make a small team dangerous in the right way.
Stereotypes: are these the biggest misconceptions about software engineers?
Outdated myths about developers—like “they hate meetings” or “only care about code”—create friction, missed context, and rework. Learn how to build healthier collaboration across engineering and product.
AI isn't optional anymore: Why developers without AI are falling behind
AI is not replacing developers, but it is replacing developers who refuse to use it. The real skill lies in how well you steer, validate, and challenge the model. Fundamentals matter, but today’s best engineers treat AI as an amplifier, not a crutch.
Legacy vs technical debt: how investors can spot hidden risks in software products
What can investors do about legacy code to prevent your startup from failure? What is the difference between legacy and technical debt?