I see this sentiment of using AI to improve itself a lot but it never seems to work well in practice. At best you end up with a very verbose context that covers all the random edge cases encountered during tasks.
For this to work the way people expect you’d need to somehow feed this info back into fine tuning rather than just appending to context. Otherwise the model never actually “learns”, you’re just applying heavy handed fudge factors to existing weights through context.
For this to work the way people expect you’d need to somehow feed this info back into fine tuning rather than just appending to context. Otherwise the model never actually “learns”, you’re just applying heavy handed fudge factors to existing weights through context.