If you have ever shipped a backend service without a debugger, a hot-reload dev server, or decent logs, you remember how painful it was. Now imagine doing it in a world where your "function" is a non-deterministic black box that can rewrite its own output every time you call it. Welcome to building generative AI (GenAI) applications.
The single biggest productivity multiplier I have found in the last two years of shipping AI apps is a good local debugging tool. Not a hosted dashboard. Not a cloud trace viewer with a 30-second propagation delay. A local tool that runs next to your code, picks up your edits, lets you replay a request with a tweaked prompt, and shows the full trace, tool call by tool call. We will get into the local-vs-hosted trade-off later in the article.
One of the core conceits of ForensicDbg was that if we build a significantly improved crash debugging core, that value would carry through, regardless of the final…
Introduction In my previous comparison of Genkit Go and ADK Go 2.0, I covered the everyday tasks. This article is about the agent layer, and instead of comparing…
A Genkit flow is an excellent unit of AI work. It is typed, traced, testable, and genkit.DefineFlow gives you something you can call from anywhere. What a flow is not…
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