We’ve all been there. You click a button in a modern web app, and you’re immediately greeted by a generic loading spinner. You sit there, staring at it for 10 or 15 seconds while some heavy LLM pipeline runs in the background. It’s a frustrating user experience, and honestly, it’s usually the result of a lazy architectural pattern.
When you're building complex, multi-step AI features (like a resume optimization engine that needs to parse text, check formatting, evaluate metrics, and then generate tips), waiting for the entire chain to finish before returning data feels painfully slow.
Instead of forcing your users to stare blindly at a loading screen, you can build a live, interactive pipeline experience. Let's look at how to orchestrate a serverless AI pipeline using Firebase Genkit
and Gemini 3.5 Flash, streaming real-time progress telemetry milestones directly down to a reactive Angular Signals architecture in the browser.
The Telemetry Architecture
