Strava (and I assume to some extent Garmin) apply some smoothing to these raw GPX traces to try and improve the path, or remove some of the noise.

You'd be missing out on this post-processing by taking the data raw. Ofc you can implement something similar yourself, but I wanted to point out that these platforms are doing a little bit more than just displaying the GPX trace.

Analogies about 'students and exams' that don't quite fit. The sentences ending in artificially punchy short phrases. The 'correction' and dash-as-reveal in "they can't answer it - no one can".

It's not good, or a compelling read, and I think it's lazy not to have swept through and fixed these things.

This is classic Claude, and makes me think the author didn't read, edit, or invest in their own words.

When you make an LLM call, if you use the streaming responses (typical of token streaming into applications) then the response from the LLM provider comes in a specific format; mostly made up of individual json events, one for each text-delta or token generated, and some framing around start/stop. That API format differs across different LLM providers, and also isn't that convenient to process for what you actually want to show in the client/browser.

The backend portion of these sdks (AI-SDK) are an abstraction over the LLM provider, and re-write the 'events' that you get back from the LLM provider into an abstracted json format that's a little bit easier to work with. And not coupled to a specific provider.

The frontend portion of these SDKs (AI UI SDK) helps you to render those message into a frontend interface, and uses the same abstracted format that the backend uses.

There's one big missing piece though, and that's the fact that the transport between frontend and backend is over a single HTTP+SSE stream. If that connection fails, all the work that the backend is doing cannot be transported to the frontend anymore. The HTTP connection also doesn't allow for useful features like cancellation, steering, interruption, and multiple devices.

If you want those, checkout Ably AI Transport, which targeting the _transport_ section between backend and frontend, to make sure you get reliable experiences in the UI regardless of which AI provider or SDKs you use.

Disclaimer, I work for ably on this product:

https://ably.com/docs/ai-transport

I think they really missed the opportunity to add in resumable streaming after a dropped SSE connection, or multi-device support. Because these SDKs are easy to drop-in to your applications, but hard once you actually try and build resilient systems on top of them. Systems that can heal from dropped connections, or support multiple users or multiple devices.

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There's a lazy habit from some folks to say something they either disagree with or don't understand was "written by AI" without backing up that statement.

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So you can be notified by the database, but you can't (with the stateless HTTP + loadbalancer design explained in the article) get that notification back to the client. Because the client isn't connected anymore; so how does the client know that there's new information?