Daily Reading List – August 28, 2023 (#152)

I’m in San Francisco for Google Cloud Next, which officially starts tomorrow. Today I had a few more rehearsals and enjoyed bumping into folks in person. Even if you’re not in our universe (yet), it’s worth watching tomorrow’s keynote! In the meantime, here are the things I read through today.

[blog] Build Flutter application in python to chat in ANY language with Google Cloud LLMs available on Vertex AI. It’s great seeing demos like this that bring generative AI to developers in the languages, frameworks, and platforms they already know.

[blog] Sometimes, Product Managers Need to Say “Yes”. It’s easy to rotate to saying “no” to everything to protect your time or keep things on track. But this post is a lovely reminder that saying “yes” is a powerful thing.

[blog] Let’s kill all frameworks at once. Can AI-generated code replace the need for stack-upon-stack of programming frameworks? I feel skeptical, but this post makes the argument.

[repo] AI on Kubernetes examples. The GKE team put a consolidated repo together that includes blueprints and best practices for folks running AI/ML workloads on Kubernetes.

[blog] How to learn from incidents and propel your engineering career? Observing and learning from failures is how most of us grow. This post looks at what we can learn from incidents.

[article] Why We Glorify Overwork and Refuse to Rest. We’d prefer to be overwhelmed instead of underwhelmed. Here’s why, and what to do about it.

[article] A brief guide to LangChain for software developers. Jani offers a useful summary of this SDK that’s become a popular tool for devs connecting to large language models.

[blog] Hemingway is now Hemingw-AI! My favourite writing tool just got an AI upgrade and it’s great. I haven’t been using it as much lately, but the Hemingway app improved my writing for the better. If you’re trying to become a more effective writer, use the web or paid app version.

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