This is a fantastic interactive tutorial. The content is great, but so is the design and way it’s ut together.

I absolutely love everything about this website.

The fact that MCP is a difference surface from your normal API allows you to ship MUCH faster to MCP. This has been unlocked by inference at runtime

Normal APIs are promises to developers, because developer commit code that relies on those APIs, and then walk away. If you break the API, you break the promise, and you break that code. This means a developer gets woken up at 2am to fix the code

But MCP servers are called by LLMs which dynamically read the spec every time, which allow us to constantly change the MCP server. It doesn’t matter! We haven’t made any promises. The LLM can figure it out afresh every time

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This is really cool

How the best teams avoid comprehension debt The best teams I’ve seen solve this problem before any code gets written.

They spend significant time planning with the AI upfront. Not just giving it a prompt and accepting whatever comes back. But going back and forth on the high-level approach. Thinking through edge cases together. Shaping the implementation before a single line gets generated.

This isn’t about slowing down. It’s about understanding what you’re building.

When you shape the implementation with the AI, two things happen:

First, the AI writes better code. Because you’ve given it more context, thought through the edge cases, and guided it toward a cleaner architecture.

But second, and this is more important, the human engineer actually understands the code. Because they shaped it. They made the key decisions. The AI just handled the mechanical work of typing it out.