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  • I've always hated interfaces that try to complete my sentences for me. It started with suggested replies in email and IM apps. I sure noticed it when they started showing up in the llm chat interfaces and it really bugs me.
    by Cyan488
  • The weird thing I notice is that these suggestions are always in all lower-case, even though I don’t type that way.
    by munchler
  • So..they don't have to show you a a prefilled prompt to evaluate the accuracy of their guesses...in fact it biases the user's response toward the prediction, making it less independent. If anything, that they are showing it indicates that they feel they've reached a prediction accuracy already at a level useful to users.
    by SubiculumCode
  • How does showing the suggested answers to the user make the conversation better for model training?

    They could take any conversation without suggested answers, truncate it to just before a user message, have the model predict suggested answers and then train it on the difference between predicted and actual answers, right?

    by bugos
  • I work on Claude Code. Prompt suggestions aren't being used to collect preference signals. We built this feature purely to help you stay in the flow, or for people who are returning to the session after a while and may need a little reminder on what a next step could be. We do see how many suggestions are accepted, but that's only so we know how helpful this feature is overall! (We tried to strike a balance by not making it "autocorrect", so it's more of a grayed out suggestion that can be typed over. It can always be toggled on/off in settings if you don't like it.)
    by edwinarbus
  • This isn't really convincing, since you can do this even without showing the prediction at all. Simply ask the model to predict what the user will send, then show the actual next prompt, and done. The only reason to show this would be to influence the user's next prompt, which the article doesn't touch on.
    by stavros
  • If you've played around with 'raw' LLM interactions you've already seen this: feeding a prompt into an LLM which ends with a 'start of user' prompt will produce a plausible query into the agent. Which makes perfect sense because the LLMs are already trained on many examples of this and the 'predict the next token' loss function does not particularly distinguish between the sides of the conversation. I highly doubt they need this feature to get better training data, more likely they got this feature for free from the way that the training works and only recently decided to actually expose it to the user.
    by rcxdude
  • I had to laugh yesterday when Claude went and changed a feature I didnt want or ask to be changed and the suggested message was something along the lines of revert the change to it. Like it knew I wouldnt like it but did it anyway
    by tripleee

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