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.
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.
Building a thriving remote-first culture takes more than allowing people to work from home. Discover how hiring for ownership, embracing asynchronous work, and saying no to misaligned projects creates a sustainable remote future.
What can investors do about legacy code to prevent your startup from failure? What is the difference between legacy and technical debt?
As AI becomes a standard part of every developer’s toolkit, tech hiring needs to evolve from policing its use to understanding how candidates apply, evaluate, and collaborate with it.
Most technical due diligence audits focus on code quality and tooling, but the real risk lies in invisible processes, fragile teams, and product chaos, which is why madewithlove audits the full stack of your organisation, from code to culture.
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.
AI agents shouldn’t become CAPTCHA solvers: discover how monetisation-driven UX patterns have turned the web into a hostile environment and what honest design can do to reverse the trend.
Discover the five most common technical-due-diligence red flags—from undersized or misaligned teams to “just-about-working” codebases—that VCs must spot before writing a cheque.
