Some good content on the interwebs today, and some spicy perspectives floating around social media. I don’t put much stock in flame-bait perspectives about “product X was a a huge mistake” or “I can never trust vendor Y”, so you’ll hopefully always see more measured takes in the content I share here each day!
[article] Businesses are too slow to embrace emerging tech, employees say. Are key technologies out of date by the time they get fully adopted? Many say yes, but it’s a hard problem to solve!
[blog] Migrating Critical Traffic At Scale with No Downtime — Part 2. Here’s a good post from the Netflix Engineering team that explains some techniques they use to cutover to new systems.
[article] Google Cloud Launches Anti-Money-Laundering Tool for Banks, Betting on the Power of AI. WSJ article that stood out to me because it talks about moving away from hard-coded rules and more into learning-based platforms.
[article] Harness Brings Generative AI Capabilities to DevOps Workflows. Like with above, it’s less about the model, and more about the experiences you wrap around it. More.
[blog] Bringing Transparency to Confidential Computing with SLSA. I think I understand what’s going on here. You’ll likely continue to see SLSA show up in places where artifact security is in play.
[blog] Experimenting at Scale, the Spotify Home Way. Some advice from the Spotify Engineering team on the topic of running experiments.
[blog] Exploring WebAssembly outside the browser. Will WebAssembly ever really take off? Maybe if more use cases become mainstream, including those outside the browser.
[article] Total addressable market: Why it’s important, and how to calculate it. TAM is interesting, but if you use it to justify product development or a GTM plan, you’re cheating. Leverage more realistic numbers like SAM and SOM.
[article] The five new foundational qualities of effective leadership. Most of these circle around the question of “how do you handle complexity?” From what I’ve observed, being effective at working in complex situations is what separates good leaders from average ones.
[blog] Estimation Isn’t for Everyone. Check out this post from the tech team at the New York Times and learn about how they think of estimating agile projects.
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Richard Seroter's Architecture Musings 
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