It started out as a fourteen-meeting day. Dropped to twelve and somehow that felt like a huge win. It was, as I had extra time to write some things, and finish a coding demo I’m working on.
[article] Overload Protection: The Missing Pillar of Platform Engineering. This hasn’t been a topic I’ve seen covered a lot when talking about internal platforms. Good coverage.
[article] Why Your CTO Might Start Coding Again. What a super interesting angle. Hire managers instead of individual developers because managers have learned how to orchestrate (AI) workers and can get more done?
[blog] From adoption to impact: Putting the DORA AI Capabilities Model to work. Oooh, a new companion guide to this year’s DORA report. It explores the seven capabilities that give you a better chance of success.
[article] AWS is still chasing a cohesive enterprise AI story after re:Invent. Going from a “do anything you want” infrastructure cloud to an opinionated app or AI cloud is a tough move to make!
[podcast] What world-class GTM looks like in 2026 | Jeanne DeWitt Grosser (Vercel, Stripe, Google). Great episode of Lenny’s Podcast that covers all sorts of modern thinking into go-to-market.
[article] Canonical Extends Kubernetes Long-Term Support to 15 Years. That’s a long time. Maybe for embedded systems that you never touch this makes sense. But if your enterprise is looking to stick on a Kubernetes version for fifteen years, something is broken.
[blog] Tutorial : Getting Started with Google MCP Services. Rarely does a tutorial actually give you everything you need to know. This one does.
[blog] Is Your CI/CD Tool Helping or Hindering Performance? If you generate code faster but can’t ship it, what’s the point? Most engineers recognize that their path-to-production might be the most critical leverage point of software delivery.
[docs] Single-agent AI system using ADK and Cloud Run. Don’t make your life difficult and start every agentic system with a multi-agent architecture. One might be fine.
[blog] FACTS Benchmark Suite: Systematically evaluating the factuality of large language models. Check this out. Here’s a new way to test a model’s ability to give accurate answers.
[blog] Smart Tool Selection: Achieving 34-64% Token Savings with Spring AI’s Dynamic Tool Discovery. I imagine we’ll see more of this as devs want to avoid eating up their whole token budget on tool selection.
[article] OpenAI report reveals a 6x productivity gap between AI power users and everyone else. Hmm. Some users are sending 6x the messages, but does that mean they’re more productive? And we’re talking tasks, not full lifecycle activities. Few are showing THAT improvement!
[blog] Provide Feedback to Google Antigravity. Your agentic coding tool is doing work. Where are you supposed to drop feedback to steer its behavior? This is a good post that identifies the contextual locations and moments.
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Richard Seroter's Architecture Musings 
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