It is definitely an idea discussed quite a bit on X (and in the broader AI community) as i read around.
The core argument is that no single LLM is truly best-in-class at absolutely everything and never can it be (in the short/medium term).
Different models have relative strengths (e.g., one excels at reasoning, another at creative writing, coding, fact-checking, or domain-specific tasks like DeFi or medical analysis).
So, routing tasks to specialized LLMs (or combining/ensembling them) often beats forcing one generalist "do-it-all" model to handle every step.
Exactly. The difference we’re exploring is collaboration instead of pure routing: multiple specialized LLMs sharing the same context and memory, reasoning together in real time.
Specialization becomes a strength once models stop working in isolation.
Great stuff!!
It is definitely an idea discussed quite a bit on X (and in the broader AI community) as i read around.
The core argument is that no single LLM is truly best-in-class at absolutely everything and never can it be (in the short/medium term).
Different models have relative strengths (e.g., one excels at reasoning, another at creative writing, coding, fact-checking, or domain-specific tasks like DeFi or medical analysis).
So, routing tasks to specialized LLMs (or combining/ensembling them) often beats forcing one generalist "do-it-all" model to handle every step.
Exactly. The difference we’re exploring is collaboration instead of pure routing: multiple specialized LLMs sharing the same context and memory, reasoning together in real time.
Specialization becomes a strength once models stop working in isolation.
this is incredibly powerful
Thanks Davide!