Daily Reading List – May 1, 2026 (#775)

Happy May! I’m expecting another exciting month of tech updates and real-world stories of people learning the best ways to do modern work. Buckle up.

[blog] Databases Were Not Designed For This. Predictable queries and deterministic code? That’s not what databases encounter today. Are defensively designing your data layer for agents? This piece has specific advice.

[blog] How to correctly use MCP servers with your AI Agents. We’re getting smarter on how to best load the right tools when we need them.

[blog] Lessons on Building MCP Servers. More MCP lessons, especially around which tools to expose and and how to chain activities together.

[article] Build To Learn FAQ. Great follow-up from Marty that answers questions about what a product manager really does now.

[blog] One Map Key, One Lookup. It’s a small waste, but you’re still wasting CPU cycles if your code uses maps this way.

[article] How can engineering leaders calculate the return on their AI investments? Very good analysis, and a killer quote you should share with your manager. Find the one about this being a systems decision, not a tooling decision.

[blog] Google Cloud Next 2026: The End Of The AI Pilot Era. Forrester Research takes a look at this important next step. Let’s get to work.

[article] AI agents are forcing enterprises to overhaul their operations. We’ve got a ways to go to land on autonomous ops, but the journey will trigger some important conversations.

[article] Are we ready to give AI agents the keys to the cloud? Cloudflare thinks so. Agents can do any commercial transaction on Cloudflare. Bold. Once the guardrails are truly in place, this likely becomes more acceptable.

[blog] The Journey Begins: Meet the 2026 GSoC Contributors! Wonderful program, glad to see this season get rolling.

[article] The Psychological Costs of Adopting AI. Let’s ensure we intentionally build the human infrastructure needed to get the most value from these AI tools.

[blog] Building with Gemini Embedding 2: Agentic multimodal RAG and beyond. Regardless of your media type, you can use this single Embeddings model. How amazing is that?

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