In addition to traditional adaptive-hypermedia approaches, developers could use modern artificial-intelligence systems to generate document or content variations for users, using their provided adaptation parameters, precomputing and caching these for later reuse.
That is, Web servers could receive HTTP GET requests – with adaptation parameters specified using HTTP request headers – and determine whether precomputed, cached versions existed for the adaptation parameters (or sufficiently proximate points or regions in adaptation-parameter space). If so, Web servers could serve the precomputed and cached content. If not, Web servers could serve the user a wait screen, use artificial intelligence to generate document variations for the users' adaptation parameters, send that generated content to those users awaiting it, and then cache the content for later reuse.
This suggests a few points:
Firstly, a representation format can be selected or designed for developers to utilize to represent their documents' contents in audience-independent ways such that these could be sent to artificial-intelligence systems for them to rewrite or rephrase them for described audiences.
Secondly, categories of software can be considered which process input data – such as audience-independent representations of documents' contents alongside sets of values for adaptation parameters describing intended audiences – to create prompts or agentic workflows for artificial-intelligence systems.
In addition to traditional adaptive-hypermedia approaches, developers could use modern artificial-intelligence systems to generate document or content variations for users, using their provided adaptation parameters, precomputing and caching these for later reuse.
That is, Web servers could receive HTTP GET requests – with adaptation parameters specified using HTTP request headers – and determine whether precomputed, cached versions existed for the adaptation parameters (or sufficiently proximate points or regions in adaptation-parameter space). If so, Web servers could serve the precomputed and cached content. If not, Web servers could serve the user a wait screen, use artificial intelligence to generate document variations for the users' adaptation parameters, send that generated content to those users awaiting it, and then cache the content for later reuse.
This suggests a few points:
Firstly, a representation format can be selected or designed for developers to utilize to represent their documents' contents in audience-independent ways such that these could be sent to artificial-intelligence systems for them to rewrite or rephrase them for described audiences.
Secondly, categories of software can be considered which process input data – such as audience-independent representations of documents' contents alongside sets of values for adaptation parameters describing intended audiences – to create prompts or agentic workflows for artificial-intelligence systems.