Daily Reading List – February 5, 2025 (#487)

Big tech day for Google with some new models out. Tomorrow I head out to India, and will do my best to keep the reading lists flowing while I’m half a world away.

[article] The End of Programming as We Know It. If you read one item from this list today, make it this. Read the others too, but this one feels important to digest.

[blog] Gemini 2.0 is now available to everyone. Big, big news. GA models, new models, and wide availability. This post has benchmarks, which shows you’re getting better models at great prices.

[blog] Improving Agentic SQL Generation. AI that generates code or SQL is so helpful. But it doesn’t magically know about your tables. Shane shows how metadata makes the predictions better.

[article] Introduction to Data Streaming. Here’s another one of The New Stack’s foundational tech articles. Get the scoop on what data streaming is really about and why it matters.

[article] Abandoned AWS S3 buckets can be reused in supply-chain attacks that would make SolarWinds look ‘insignificant’. This can apply to any object storage service. But of course, S3 is a wildly popular one, and likely a rich target.

[article] How not to waste a senior engineering hire. Make sure your experienced folks have assignments that fit their level.

[blog] What is Ollama and how to use it: a quick guide [part 1]. This tool may have flown past you without notice. But lots of folks like using it to run LLMs locally.

[article] 5 Signs a Remote Worker Is Burning Out. How to sense it, and what to do about it. Good advice for managers, and for all of us who also spend time working remotely.

[article] Enterprises lean on container solutions to deploy generative AI. Are AI workloads the trigger for mass adoption of container runtimes beyond what we’ve done thus far? Maybe so.

[blog] How I use LLMs as a staff engineer. All of these make sense to me, and are part of my own workflow with AI.

[blog] Secure by Design: Google’s Blueprint for a High-Assurance Web Framework. Read this if you ship web apps and want to eliminate exploitable vulnerabilities.

[ebook] How to Scale Your Model. This is basically Google’s own internal handbook, shared with everyone. Some fantastic content here for ML engineers and data scientists.

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