As AI models get better at handling tools, and as context windows get bigger without as much rot, you can start to design agents more similar to how people work instead of having to mitigate the model limitations with weird hacks. For instance, even a year ago, if you were to build an agent to process large amounts of documents, the state of the art was to do embeddings on the data, then do a similarity search and pull out the chunks of content that matched (as well as surrounding chunks).…