Hey, have you heard about the latest development in the world of Large Language Models (LLMs)? With the launch of GPT-5, we’re seeing a new level of abstraction, where multiple OpenAI models are being brought together under the hood, controlled by a real-time router. But what’s really interesting is that this router is trained on user preferences, not just benchmarks. This approach has the potential to revolutionize the way we interact with LLMs.
But here’s the thing: we didn’t have to wait for GPT-5 to get this functionality. Back in June, a team of researchers published a preference-aligned routing model and framework that allows developers to build their own experiences with the models they care about. This means that you can create a customized router that works with any set of LLMs, tailored to your specific needs.
I wanted to share this research and project again, as it might be helpful to developers looking for similar tools. It’s an exciting time for AI development, and I’m curious to see where this technology takes us. Will we see more personalized AI assistants that can learn our preferences and adapt to our needs? Only time will tell.
What do you think about this development? Are you excited about the potential of custom routers for LLMs?