There are many data from large factories

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When will the product manager of the jump? This stage: IGC → Copilot → Insight → Gent (Automation) understands user intentions by taking a beggar version of the product, and then gives the customer's best practice and successful manual, delivery case, customer service knowledge base for the past few years ... See if you can give the user's operating plan. To sum up, it is probably this ability: understanding user intentions, providing user operation plan suggestions, generating marketing creativity, automated execution, automated supervision, and automation attribution. Second, the data is not a barrier, feed the data as Context to the big model, so that the big model understands you better, and the differentiated experience is the beginning of the bar barrier. It starts from the perspective of the user. It is a data that can see the data that users have precipitated in a variety of scenarios, such as the videos, articles, and asking questions that have been seen. These are the private data of users who do not have users in LLM.


From the past experience, the data is definitely not a barrier, but after data, it is passed on to LLM as Context to make this LLM better understand you. This differentiated experience is a barrier. For example, let LLM help you start with a title, but give the prod Armenia WhatsApp Number uct information to LLM together, the effect is different. All applications that are not willing to do only I tools need to consider i assets set by data, so that products can serve users based on assets and more personalizedly serve users. Third, what data should be precipitated to make i products? The data that needs to be precipitated is not a transaction amount, but the user is solving a certain scene in a certain period of time (such as a month). ——The Q & A that requires enough best practice. So in the end, I may not be a company selling software systems. It may be an operator of an intelligent operation system. Through the summary of countless best practices and best practice, it is continuously entered and operated. .



but not really strong. Many data are not structured and cannot be used directly for large models. Then, the problem of making i products today is how to use your product design to allow users to produce models to use data? How to rely on the cycle of data and the accumulation of unique data to complete the product design? The first is the general model. The user's use data has not improved much for general models, and it is still the ability of the general model of the general model. This part is mainly used to understand the user's intention and meet the basis of the score. Second, the industry field is generally generalized.