How LLMs Are Reshaping Recommendation Systems

News feeds and recommendation systems have long relied on deep learning architectures that score each candidate item independently. As LLMs have matured, they have opened up a fundamentally different approach, where a system can reason about content the way it reasons about language. However, that power comes with a fresh set of engineering challenges around cost, scale, and evaluation. LinkedIn recently rebuilt its news feed to treat content recommendation as a sequence modeling problem. The general approach is to predict what a user will want next, much like an LLM predicts the next token in