Daily Reading List – August 18, 2026 (#848)

Long day. Not done yet as I host my monthly all-hands calls in both AM and PM times to catch our global team. Fortunately these calls are fun, and it’ll distract me from a day of navigating corporate mazes.

[blog] AI usage patterns in software teams. Quite interesting data about the breadth of roles (and levels) using AI regularly. And what’s NOT changed.

[blog] AI Code Review Best Practices. Every team will do their own thing, but here are some viable techniques that work for this team.

[article] Nobody’s Actually Prioritising ‘Value’. Oooh, I like this take. “Value” is contextual to the recipient, and can only be measured after the value exchange occurs. We’re prioritizing work based on confidence in our hypotheses.

[blog] Build zero-trust AI agents with Google’s Agent Development Kit. If you’re using AI to generate AI agents, your tool might skip over this sort of guidance. Don’t make that mistake. Explicitly feed this in.

[article] A better approach to generative UI. Don’t just render out HTML/JS from your LLM. There’s all kinds of risk with that approach. Without saying so, this article makes the case for A2UI.

[article] A Home for Personal Context. Where does context live? Locally on a laptop? On the web? Or in your pocket? Probably all, in some way.

[blog] Google ADK 2 Graph Workflows: A Complete Guide with Code Examples. Romin goes deep here in a very readable post. Define deterministic steps, but still implement a variety of patterns.

[blog] When the Hard Part Stops Being Hard. AI changes how long things take to do. We’re coming to grips with what that means to publication volume, research value, and our intellectual ambition.

[blog] How I Planned an Italy Trip with an Agentic Workflow. As the AI interfaces get simpler, these types of use cases will explode.

[blog] Stop burning tokens on code review. It’s where you’re using the most tokens today in the SDLC. Use a cheaper (local?) model, create custom linters, or design this process with cost in mind.

[blog] Staying Ahead of Adversarial AI Through Agentic Source Code Review. It’s almost guaranteed that you’re piling up more code now that it’s easy to produce it. How are you scanning it at scale for vulnerabilities?

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