featured in #506
Developing Rapidly With Generative AI
- Shannon Phu tl;dr: From the engineering team at Discord: “We break down the process of building with LLMs into a few stages. Starting with product ideation and defining requirements, we first need to figure out what we’re building and how it can benefit users. Next, we develop a prototype of our idea, learn from small-scale experiments, and repeat that process until our feature is in a good state. Finally, we fully launch and deploy our product at scale. In this post, we will dive deeper into each stage of this process.”featured in #505
featured in #504
featured in #483
The Scary Thing About Automating Deploys
- Sean McIlroy tl;dr: Sean delves into the complexities and strategies of automating deployments at scale, focusing on how Slack transitioned from manual oversight to using their automated tool for deployment processes in a high-change environment. “When people talk about continuous deployment, they’re often thinking about deploying to systems as soon as changes are ready. They talk about microservices and 2-pizza teams (~8 people). But what does continuous deployment mean when you’re looking at 150 changes on a normal day? That’s a lot of pizzas…"featured in #482
Sensenmann: Code Deletion At Scale
- Phil Norman tl;dr: “What if we could clean up dead code automatically? That was exactly what people started thinking several years ago, during the Zürich Engineering Productivity team's annual hackathon. The Sensenmann project, named after the German word for the embodiment of Death, has been highly successful. It submits over 1000 deletion changelists per week, and has so far deleted nearly 5% of all C++ at Google. Its goal is simple (at least, in principle): automatically identify dead code, and send code review requests to delete it.” Phil discusses its logic.featured in #482
featured in #473
Performance & Compensation (For Eng Execs)
- Will Larson tl;dr: Will discusses: (1) The conflicting goals between those designing, operating, and participating in performance and compensation processes. (2) How to run performance processes, including calibrations, and their challenges. (3) How to participate in a compensation process effectively. (4) How often you should run performance and compensation cycles. (5) Why your goal should be an effective process rather than a perfect one.featured in #446
featured in #446
featured in #445