Daily Reading List – January 7, 2025 (#467)

Today’s reading list happens to have a lot of good material for those planning ahead. How do you avoid overcommitting? Or do a competitive analysis? Refine a strategy? Create OKRs?

[blog] How I built an agent with Pydantic AI and Google Gemini. Karl might have just saved you a few million dollars in consultant fees! He built a SWOT analysis tool using a variety of technologies (including the Gemini API).

[blog] Open Source Discussion Archetypes. You may not personally care about the OSS licensing fracas that’s going on, but somebody does. Steve looks at the groups that are intentionally or unintentionally invested.

[article] My 2025 trends predictions. Tom’s a tech writer at Google, and shares some useful thoughts on AI and how it’s going to impact his field.

[blog] How to effectively refine engineering strategy. Are you doing big strategic exercises, or doing small refinements until a strategy is “ready” for mass deployment? Will has a good post that can help you understand the problems being solved, and which tools to use.

[article] Meta is ditching third-party fact checkers. Good. However well intentioned, centralized moderators inevitably apply unhelpful bias. Community Notes is a useful approach.

[page] 2024 AI timeline. This is a cool way to view all the major LLM releases from last year. It shows both open and AI only (closed) models.

[article] Why You’re Chronically Overcommitted. This will probably resonate with most of you. I’ve fought back against this over the past few years to good effect.

[article] Google maps the future of AI agents: Five lessons for businesses. Are you clear on what agents are, and what you should be doing with them? I’m not sure I am, so you’re better off than me. But this VentureBeat story looks at a recent paper and offers direction.

[blog] Hitting OKRs vs Doing Your Job. OKRs (or however you’re capturing major goals) are for special focus, not the day to day work.

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