Unlike with semantic indexes, an index for regular expression search also needs to be very fresh, particularly when it comes to the model reading its own writes. We don't have to continuously update our semantic index because re-computing the embeddings for a file after it is modified does not cause the new embedding to significantly displace itself in the multi-dimensional space. The nearest-neighbor search we perform will still send the Agent in the right direction. However, if the agent is searching for specific text and it does not find it, it'll often go into a wild goose chase, waste tokens, and defeat the purpose of our performance optimization in the first place.
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