Built To Last: The Best Way to Measure and Improve Your Product Velocity

Welcome to this week’s edition of my weekly newsletter “Built To Last”, where I am sharing valuable insights on building high-quality products.

Each week, I curate articles and podcasts that caught my attention – resources that I believe are relevant and insightful for everyone looking to build a great product.

This Week’s Picks

• Introducing Core 4: The best way to measure and improve your product velocity – Core 4 is a new developer productivity framework designed to measure and improve product velocity by integrating insights from DORA, SPACE, and DevEx. It provides a structured approach to balancing speed, quality, impact, and effectiveness without compromising developer experience.

• Linear’s secret to building beloved B2B products | Nan Yu (Head of Product) – another great one from Lenny’s Newsletter this week – speed and quality often go hand in hand – experts work quickly because of their competence, not by cutting corners. Linear prevents software bloat by rejecting unnecessary customization and focusing on high-quality, core solutions. And many other great insights.

• Inside Stripe’s Engineering Culture – Part 1 – there are some great insights into Stripe’s engineering culture including how much time engineers spend with customers. This deep engagement is a direct reflection of Stripe’s “users first” principle, ensuring engineers understand real-world needs firsthand. It’s a great reminder that true customer focus starts at the core of a company’s culture.

• AI-Based Automated Testing: Is It Really the Future of Testing? – this article examines the capabilities and limitations of a few current AI-based automated testing solutions. Tl;dr: While AI-driven testing reduces manual regression efforts and enables tests to adapt dynamically to software changes, its probabilistic nature presents challenges for reliability in traditional regression testing. I appreciated the list of key AI technologies at the end of the post – understanding these concepts is essential for anyone looking to learn how AI works and how to apply it effectively in testing.

• Observability: the present and future, with Charity Majors (Co-founder and CTO of Honeycomb) – an important topic for Woo right now – DevOps is fading as engineers increasingly own their code in production. Static dashboards fall short – teams need dynamic tools to truly understand their systems. With AI-generated code on the rise, observability is more crucial than ever for debugging and reliability.

• 3-2-1: On the power of inputs, what holds quiet power over you, and the one habit that matters most – this piece is aspirational but including it here to end on the high note – just as high-quality inputs lead to high-quality thinking, high-quality materials, processes, and data lead to high-quality products. Businesses that carefully select the right raw materials, user feedback, and design inspirations produce superior products.