When intelligent customer service has no basis, it is necessary to let humans continue to deal with the same service problem. Users should not re-describe the entire context, and manual handovers should distinguish between facts provided by users and suggestions generated by the model. The handover content should be clear and traceable.
AI requests may fail during the retrieval, model or tool stages. The request identifier can connect each step, and the log can support troubleshooting without repeatedly saving the complete text. The field design should give priority to answering the failure location, time consumption and reasons.
Model substitution affects return formats, tool requests, and unexpected behavior. The unified business interface helps reduce page migration costs, but just because the page can display text does not mean that tool calls and source references still comply with the original rules, and replacement requires independent verification.
A successful demonstration answer does not mean that the large model application covers all businesses. Assessment samples need to include wording changes, insufficient information, and confusing objects, and the judgment criteria need to be clear before the test to avoid showing only smooth questions and answers.
Large model data permissions need to be implemented at the retrieval and caching layer. The front-end hidden document list cannot prevent the backend from returning restricted content, and the shared cache cannot be read by all accounts by default. Answers and references need to follow the current identity scope.
Agent calling tools may change orders or create tasks. The execution service should independently verify the identity, target record and parameters. The actions proposed by the model cannot be directly regarded as the authorization result. The execution record must also indicate whether it is actually completed.
Answers with quotes do not mean that every sentence is supported by the source. RAG application needs to check the relationship between key conclusions and specific paragraphs. When the source only covers part of the business, the scope of the answer should also be limited and cannot be extended to conclusions for all situations.
The basis of knowledge base Q&A is usable and locatable documents. Duplicate data, a mix of old and new versions, or a lack of directories will affect the search scope; sources, applicable times, and access permissions need to be sorted out before accessing the model.
OA handover data should support maintenance personnel to independently locate problems. Only the system name and administrator account cannot be used to explain process configuration, interface dependencies or backup and recovery methods. The document needs to be organized according to the actual troubleshooting path.
Mobile office needs to make to-do viewing, attachment reading and submission smooth. Long forms, weak networks, and login timeouts affect high-frequency operations. Pages should be arranged around the order in which employees complete a task, rather than shrinking computer pages.
A project consists of multiple tasks, and the number of tasks to be done does not equal the degree of completion. The reason for blocking should be displayed when waiting for external data. Repeatedly extending the date cannot help the team resolve dependencies. The task status needs to point to the next action.
A knowledge base description may be used by multiple departments. Copying the text and then modifying it separately will result in conflicting versions. Therefore, classification entries and controlled sources should be organized separately, and search and attachment downloads should also follow the access scope.