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 (https://addyosmani.com/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 (https://medium.com/google-cloud/how-adk-agents-remember-sessions-events-and-persistent-state-742e06e9568c). 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 (https://huggingface.co/blog/evaleval/eval-costs-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 (https://medium.com/google-cloud/i-attempted-to-build-a-team-of-agents-to-help-do-my-job-on-google-cloud-agent-platform-with-the-dc99ff03205f). 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 (https://newsletter.getdx.com/p/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 (https://cloud.google.com/blog/products/ai-machine-learning/google-managed-mcp-servers-are-available-for-everyone/). Terrific. Google Cloud speaks MCP, which means agents can easily interact with all the key services to get work done.

[blog] Zig Anti-AI (https://simonwillison.net/2026/Apr/30/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 (https://blog.jetbrains.com/go/2026/04/28/popular-golang-web-frameworks/). 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 (https://firebase.blog/posts/2026/04/firestore-pipelines-ga/). This has really become quite the powerful database.

[blog] You can now easily generate files in Gemini (https://blog.google/innovation-and-ai/products/gemini-app/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 (https://www.infoworld.com/article/4164236/github-shifts-copilot-to-usage-based-billing-signaling-new-cost-model-for-enterprise-ai-tools.html). Free lunch is over. Consumption pricing is taking hold over a straight-up per-seat pricing approach. More here (https://thenewstack.io/github-copilot-usage-billing/).

[article] Google Cloud surpasses $20B, but says growth was capacity-constrained (https://techcrunch.com/2026/04/29/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 (https://developers.googleblog.com/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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