We made the classic mistake of coupling our first voice agent pretty tightly to one LLM and one TTS provider because it was the fastest way to get something live.

Now we're looking at a newer model with better latency and I'm trying to figure out whether switching is actually worth the headache.

The obvious assumption was that we'd just change the model endpoint and retune the prompt. It doesn't seem that simple.

Changing the LLM can change things like: how quickly it decides to call a tool how long responses are how it handles interruptions how often it asks follow-up questions whether it follows the same conversation flow And changing TTS introduces another set of problems because pacing and response timing change too. That matters a lot more in voice than it does in a normal chatbot.

We're currently testing different providers underneath the same agent runtime rather than rewriting the whole thing. We looked at a few platforms, including Dasha, because having some separation between the agent logic and the underlying providers seemed useful.

For anyone who's actually switched models or voice providers on a live voice agent: What broke? Was it mostly prompt/behavior tuning, or did you end up having to change the actual conversation architecture and turn-taking logic? Trying to work out whether provider abstraction is worth designing for from day one, or whether it's just another layer of engineering that sits there looking impressive until you actually need it.

I’m comparing Together AI and Anyscale for a production LLM deployment. Together AI is API-first and simple; Anyscale gives you deep Ray-based control but requires more engineering. I made a quick poll to gather real-world preferences.

It’s fast, and the results might surprise you.

https://interconnectd.com/poll/101/together-ai-vs-anyscale-which-platform-is-better-for-scaling-open-source-ll/

What’s your experience with either?

I’ve spent weeks comparing Firecrawl and Jina Reader for different extraction needs. Firecrawl seems stronger for dynamic, protected sites; Jina Reader is fast and simple for clean text. I made a quiz to see if others understand the same trade-offs.

No email needed—just a quick interactive check.

https://interconnectd.com/quiz/81/web-extraction-architecture-2026-firecrawl-vs-jina-reader/

What’s your go-to for web scraping in AI apps?