Dump The Golden Dataset: Switch To Random Sampling
- Nishant Shukla tl;dr: Golden Datasets have long been a reliable method for measuring AI prompt performance. But as AI innovation moves fast, companies need a more agile, flexible, and cost-effective solution to stay ahead of their competition. Enter random sampling of AI prompt performance—a cutting-edge approach that adapts to real-world data and drives scalable performance for QA Wolf customers. Stay ahead of the curve—watch the webinar now.featured in #574
Tying Engineering Metrics To Business Metrics
- Iccha Sethi tl;dr: “Most engineering organizations I’ve worked in or led have tracked some form of engineering metrics. These range from simple metrics like uptime and incident count to more complex frameworks like DORA. As an engineering leader, you’ve probably been asked, either by someone within or outside of engineering: Why do these metrics matter? or How do they align with our business goals?”featured in #573
The 6 Mistakes You’re Going To Make As A New Manager
- Matheus Lima tl;dr: “Reflecting on my first couple of years as an Engineering Manager, I realized that the lessons I learned are not unique to me; many new managers face similar experiences. That’s why I want to share these insights with you. My goal is to support and connect with other new managers who are going through this exciting yet demanding transition.”featured in #573
Dump The Golden Dataset: Switch To Random Sampling
- Nishant Shukla tl;dr: Golden Datasets have long been a reliable method for measuring AI prompt performance. But as AI innovation moves fast, companies need a more agile, flexible, and cost-effective solution to stay ahead of their competition. Enter random sampling of AI prompt performance—a cutting-edge approach that adapts to real-world data and drives scalable performance for QA Wolf customers. Stay ahead of the curve—watch the webinar now.featured in #573
Product Management Is Broken. Engineers Can Fix It.
- James Hawkins tl;dr: “When Tim and I first started PostHog in 2020, I was adamant we would never hire a product manager. I wanted engineers to wrestle with hard product problems. Product managers, I believed, would just get in the way. Four years on, I admit I was (partially) wrong. We need product managers. But I was right about one thing: there is a better way. Over the past two years, we've redefined how PMs and engineers work together, and optimized everything we do for speed and autonomy. Here's our exact playbook.”featured in #573
Grifters, Believers, Grinders, And Coasters
- Sean Goedecke tl;dr: “Why do engineers get mad at each other so often? I think a lot of programmer arguments bottom out in a cultural clash between different kinds of engineers: believers vs grifters, or coasters vs grinders. I’m going to argue that good companies actually have a healthy mix of all four types of engineer, so it’s probably sensible to figure out how to work with them.”featured in #573
An Introduction To Thinking About Risk
- Jacob Kaplan-Moss tl;dr: “How dangerous is it to launch this new feature if it hasn’t gotten a proper security review yet? How much risk is left after we do that review?” So welcome to a new series about how to think about risk. This series is a crash course, a high-level introduction to the most important concepts and risk frameworks. It’s intended for people who encounter risk from time to time and need some basic tools, but don’t want to make a deep study of it.featured in #572
The Developer's Guide To Notification System Tooling In 2025
- Chris Bell tl;dr: “If you opened this blog post, you’re probably about to wade into the complicated ecosystem of notification and customer engagement tooling. It can feel like a daunting task. Not to fear, in this post we’re here to walk you through the basics of notification systems and the ecosystem of tools, frameworks, and vendors that surround them.”featured in #572
Grifters, Believers, Grinders, And Coasters
- Sean Goedecke tl;dr: “Why do engineers get mad at each other so often? I think a lot of programmer arguments bottom out in a cultural clash between different kinds of engineers: believers vs grifters, or coasters vs grinders. I’m going to argue that good companies actually have a healthy mix of all four types of engineer, so it’s probably sensible to figure out how to work with them.”featured in #572
featured in #571