4 articles tagged “LLMs”.
Open Perplexity, run a query, look at the Sources panel. The architecture is recognisable: retrieve, rerank, summarise, cite. The system has moved; the engineering hasn’t. A bridge piece between the observational posts and the next phase of this series.
SID AI’s SID-1 is the first retrieval model trained end-to-end with RL. Some observations through a search-and-IR lens: the middle of the retrieval pipeline collapses into one trained model, the NDCG reward gets deliberately bent toward recall, and the agentic-retrieval loop becomes a subagent you hand to a larger system.
Laurie Voss says applied-AI iteration has moved off the model and into "the harness". He’s right - and once you strip the new vocabulary, the harness is mostly a retrieval system.
Agentic search looks like a clean break from classical IR. Look closer and the architectural instincts are the ones backend engineers have used for decades - the components are new, the rules are not.
