I came across a good mix of content today that you’ll find referenced below. There are some solid pieces that touch on how we work, and how we measure impact.
[article] Adopting Asynchronous Collaboration in Distributed Software Teams. It looks like many developers aren’t getting the desired amount of “deep work” done because of interruptions. This proposes a more async, less meeting-focused, model.
[blog] Developer Friendly Networking that keeps up with your development velocity. is there such a thing as “developer friendly networking”? I dunno. But this post looks at ways to get security benefits while empowering devs.
[blog] Fighting money launderers with artificial intelligence at HSBC. I like the specific examples offered here. Using AI for more accurate risk detection, reducing processing time, and finding criminal patterns seems practical and valuable.
[blog] Part 3: Draft Content That’s Accurate, Consistent, And Concise. Good post that emphasizes the importance of quality content in your tech docs, not just flashy titles and formatting.
[article] AI Will Drive Streaming Data Use — But Not Yet, Report Says. Somehow everything is attached to AI nowadays. This analysis looks at a recent survey about the growth of streaming data.
[blog] Nobl9’s Reliability AI, Powered by Google. I enjoy seeing innovative platforms built atop innovative platforms. The Nobl9 crew do some leading work helping companies manage with SLOs, and their newest product is powered by Google Cloud’s Vertex AI.
[blog] The Developer Ecosystem in 2023: Key Trends for C#. This offers a deeper dive into one part of the survey I linked to a couple days ago. .NET devs seem to stay up to date on tools, which is good.
[blog] Introducing sample GenAI Databases Retrieval App – augment your LLMs with Google Cloud databases. I learn a lot better from reference code than from reading piles of whitepapers. This is a terrific sample app that shows off a few key ideas for generative AI.
[article] Measuring the Impact of Your Platform Engineering Strategy. Platform engineering could risk becoming a short-lived fad in the enterprise unless teams find the right metrics that demonstrate crisp value and impact.
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Richard Seroter's Architecture Musings 
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