Daily Reading List – April 29, 2025 (#541)

Today’s edition is chock-full of fascinating items to read. How do you measure collaboration within a team? Or run AI developer tool experiments? How should you roll out AI tools to a team? What’s reinforcement learning all about in modern LLMs? Dig in.

[article] Software Development Is a Team Sport. Here’s some new research that measures collaboration quality between members of a team.

[article] How to Run a Generative AI Developer Tooling Experiment. This looks at AI coding results when Cursor and Copilot go head to head.

[blog] NotebookLM Audio Overviews are now available in over 50 languages. Get this magical experience in the language of your choice.

[article] Superpowers in the AI Age (and how to develop them). Read this piece from Brian to increase your confidence that you too can use AI to learn and do better work.

[blog] Waze’s journey to Infrastructure as Code with Google Cloud’s KCC. It hasn’t caught on as much as I hoped, but the Kubernetes Resource Model is a great way to deploy and reconcile infrastructure.

[blog] The dawn of agentic AI in security operations. We’re bringing some new AI agents to security scenarios, and these look genuinely helpful.

[article] It Depends: 7 viral Engineering Management dilemmas. There doesn’t seem to be much training for new managers. Unless you have a great mentor, you’re stuck learning as you go. These are some scenarios you should prepare for.

[blog] MCP Toolbox for Databases. Excellent walkthrough from Abi that helps you learn how to run this MCP server for easier access to databases from your AI apps.

[blog] Google Cloud named a Leader in the 2025 Forrester Wave™: Data Management for Analytics Platforms. Speaking of data, this eval from Forrester shows that one hyperscaler is clearly stronger than the rest.

[article] The State of Reinforcement Learning for LLM Reasoning. If you’re into data science and ML engineering, you’ll like Sebastian’s latest piece on reasoning models and their various approaches.

[article] Building an API rate limiter using Valkey. Have you taken a look at Valkey yet? This Redis replacement is evolving at a great clip, and this tutorial shows you one use case for it.

[blog] How It’s Made: Little Language Lessons uses Gemini’s multilingual capabilities to personalize language learning. AI seems like a perfect tool for helping folks learn a new language. Personalized help is the key and this experiment plays with that idea.

[article] Driving AI tool adoption — Lessons from Microsoft. You can’t just shove AI tools into your engineering team and tell them to be more productive. Big anti-pattern. I like the lessons learned in this post.

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