Storage and retrieval mechanisms for knowledge artifacts acquired and applicable across conversations

A system comprising:

• one or more processing systems;
• and
• one or more computer-readable media storing instructions which, when executed by the one or more processing systems, cause the system to perform operations comprising:
• receiving, at a digital assistant, a natural language utterance from a user during a session between the user and the digital assistant;
• obtaining a topic context instance for the natural language utterance, wherein the obtaining comprises:
• executing, based on the natural language utterance, a search on a current session context instance, a data store, or both,
• based on the search, determining whether the natural language utterance satisfies a threshold level of similarity with one or more topics represented in the current session context instance, the data store, or both,
• responsive to determining the natural language utterance satisfies the threshold level of similarity with the one or more topics, identifying the topic context instance associated with the one or more topics, and
• associating the natural language utterance with the topic context instance;
• generating, by a first generative artificial intelligence model, a list comprising one or more executable actions based on one or more candidate actions associated with the topic context instance;
• creating, based on the list, an execution plan comprising the one or more executable actions;
• generating an updated topic context instance by updating the topic context instance to include the execution plan;
• executing the execution plan based on the updated topic context instance, wherein the executing comprises executing the executable action using an asset to obtain an output;
• and
• sending the output or a communication derived from the output to the user.

One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause a system to perform operations comprising:

• receiving, at a digital assistant, a natural language utterance from a user during a session between the user and the digital assistant;
• obtaining a topic context instance for the natural language utterance, wherein the obtaining comprises:
• executing, based on the natural language utterance, a search on a current session context instance, a data store, or both,
• based on the search, determining whether the natural language utterance satisfies a threshold level of similarity with one or more topics represented in the current session context instance, the data store, or both,
• responsive to determining the natural language utterance satisfies the threshold level of similarity with the one or more topics, identifying the topic context instance associated with the one or more topics, and
• associating the natural language utterance with the topic context instance;
• generating, by a first generative artificial intelligence model, a list comprising one or more executable actions based on one or more candidate actions associated with the topic context instance;
• creating, based on the list, an execution plan comprising the one or more executable actions;
• generating an updated topic context instance by updating the topic context instance to include the execution plan;
• executing the execution plan based on the updated topic context instance, wherein the executing comprises executing the executable action using an asset to obtain an output;
• and
• sending the output or a communication derived from the output to the user.