Daily Reading List – May 12, 2026 (#782)

I try say “yes” to customer presentation requests whenever possible. It gives me an excuse to try out new messaging, gather new context from real users, and build demo systems. I might have overdone it this week as I’m doing some new types of talks with little notice. What could go wrong?

[blog] The Android Show: I/O Edition 2026. So many cool updates today! From more proactive AI to new Googlebook laptops, we shipped some fun stuff.

[article] The Best Leaders Embrace the Role of Supporting Character. Main-character energy doesn’t help your team. Serve others, be curious, and yes, still inspire and steer the team the right way.

[article] Symptoms of Bad Software Design. Call it tech debt, or maybe just the wrong decisions. Either way, you want to tackle these areas if you hope to scale or reduce operational cost.

[blog] Google Antigravity beats Claude at coding—but only if you stop acting like a programmer. It’s a great tool. They all have merit. But you’ll want to change your workflow, not cram your existing one into these tools.

[article] How do Next Edit Suggestions in AI-integrated IDEs introduce new security risks? We’ve moved beyond tab completion, but this guidance still holds when you’re generating whole swaths of code at once.

[blog] Debugging Event-Driven Systems: 5 Problems Teams Create. Good pattern, but it’s not your whole architecture, as Derek explains here.

[article] How corporate politics actually work. Your situation could be different, but I’d imagine we all have something to take away from the many lessons shared here.

[blog] MCP Configuration for Google Workspace with Gemini CLI. Useful example with instructions I haven’t seen elsewhere. William also uses this newsletter as an example, so how can I not read the post?

[article] Fighting Tool Sprawl: The Case for AI Tool Registries. The solutions aren’t super mature at the moment, but I buy that shared tool registries are important.

[blog] Top 15 CI/CD Metrics: What to Track & Why They Matter. I can’t imagine that too many people are tracking ALL of these, but it’s a good list to pick from.

[article] What happens when engineering teams reorganize around AI agents. This article offers up quick bursts of advice from different teams adopting AI agents.

[blog] If AI Writes Your Code, Why Use Python? Would you? Or something else entirely suited to the specific use case?

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