Daily Reading List – April 30, 2026 (#774)

Back on vacation and had a day-date with my wife. A bunch of fresh crazy kicks in at work next week, so I’m thrilled to get a breather before we run at full speed again.

[blog] Long-running Agents. Another killer post from Addy. What changes when you move from single-turn stateless agents to agents that need memories and coordination over time? This post has the patterns and solution options.

[blog] How ADK Agents Remember: Sessions, Events, and Scoped-State. Speaking of memories and agent state, here’s some details on how to do it in practice.

[blog] AI evals are becoming the new compute bottleneck. Evaluation costs are scaling non-linearly and we’re going to need to come up with new approaches. Or so says this Hugging Face post.

[blog] I attempted to build a team of agents to help do my job on Google Cloud Agent Platform with the agents-cli. This is what I learnt. Great experience report. Not everything worked as anticipated, and Esther had some smart recommendations at the end.

[article] AI productivity gains: More modest than expected. So far. But as the agentic operating model takes hold, team shapes change, and better platforms stretch from build-to-prod, you’ll see these gains skyrocket.

[blog] 50+ fully managed MCP servers now available for Google Cloud services. Terrific. Google Cloud speaks MCP, which means agents can easily interact with all the key services to get work done.

[blog] Zig Anti-AI. Few open source projects have direct a stance against AI as this one. I respect the principles.

[blog] Popular Go Web Frameworks: A Practical Guide for Developers. You can do most everything with our base libraries. That’s on purpose. But there are still great 3P web frameworks you can add to the mix.

[blog] Firestore levels up: Bringing the power of search and JOINs to NoSQL. This has really become quite the powerful database.

[blog] You can now easily generate files in Gemini. Amazing. Now you don’t even need to leave the app to do Office stuff.

[article] GitHub shifts Copilot to usage-based billing, signaling a new cost model for enterprise AI tools. Free lunch is over. Consumption pricing is taking hold over a straight-up per-seat pricing approach. More here.

[article] Google Cloud surpasses $20B, but says growth was capacity-constrained. Massive demand, and we still can’t satisfy it all. Yet.

[blog] Speeding Up AI: Bringing Google Colossus to PyTorch via GCSFS and Rapid Bucket. When you’re paying a ton for capacity, you want to use it to the max and be done. This high-performing storage reduces your wait time.

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