Today’s reading list had some good practical examples, and also some thought-provoking ideas. Did any resonate with you too?
[blog] Moneyball with GenAI: Using Vertex AI Search to Find the Next Generation of Baseball Stars. If you want me to read and share your post, just make it about baseball. Well done, Alok. This is an excellent demonstration of how AI can change how we interact with unstructured data.
[blog] 5 ways Service Extensions callouts can improve your Cloud Load Balancing environment. This product update didn’t catch my eye, but a Google Engineering Fellow told me I should give it a second look. Thanks, Anna. Yes, it is a very powerful way to add intelligence and security as part of cloud traffic management. Also mentioned here as part of a cross-cloud strategy.
[article] Enterprises prep for big AI spending, but data woes prevent progress. It looks like most companies are recognizing the importance of a solid data strategy.
[blog] alpine, distroless or scratch? A small, minimum-dependency base image for your containers is a smart bet. This post looks at 4 options, and the implications of each.
[article] What software developers hate. Short post, but Matt looks at three things—scope creep, pace of learning, lack of time to code—that drive developers bonkers.
[article] Platform Engineering for a Mainframe: Design Thinking Drives Change. You can apply modern practices (with varying levels of impact) to nearly any technology stack. I like efforts like this which try to help users of “legacy” systems get a better dev experience.
[article] 4 Common Types of Team Conflict — and How to Resolve Them. Conflict, even temporary, is inevitable in a team. This article identifies each type, and how to respond.
[blog] Build and Deploy a Langchain App With a Vector Database. Wietse wrote a very good walkthrough of the steps for building a generative AI app.
[blog] Does Your Marketing Pass the Duck Test? This is a good read, especially for folks who crave plain-English descriptions that actually tell you something.
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