My day reflected some of the articles below. My brain can’t hold what it needs to hold, and I need fewer interruptions by technology. There are some suggested fixes in today’s list.
[article] Escape from agentic loop. This proposes that the human-in-the-loop workflow of AI is exhausting and fake productivity. Instead, be on-the-loop and use AI managers that follow your guidance.
[blog] Meet the latest Database Center, now with Gemini-powered fleet intelligence. Can’t just use one database engine? Ok, but now you have a problem trying to manage all these distinct engines. Our Database Center pulls it together.
[article] 12 model-level deep cuts to slash AI training costs. Smart list of ways you can be more efficient with training and make good architectural adjustments in your ML pipeline.
[article] The engineering management memory crisis. Is your brain running out of RAM? Mine is. this is a good lesson about having an LLM that points to personal context.
[article] Your AI Problem Is a Data Problem. Some good data points here, and reminders that AI isn’t a procurement decision; you need a strong data layer.
[blog] Tutorial Series : Gemini Enterprise Agent Platform. Terrific five part series from Romin that lays out how you build, scale, govern, and optimize agents.
[article] Why agent harnesses fail inside cloud-native systems. Can your AI agent harness do real work within distributed systems? Or is the lack of a realistic and isolated test bed giving you false confidence?
[blog] Why Real-Time Authorization Is Best For Agentic AI. Long argument for giving agents short-lived creds and specific access.
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Richard Seroter's Architecture Musings 
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