Meeting minutes
Symbols
matatk: I am ready to move the Symbols explainer forward this week
Lionel_Wolberger: We'll try and get you some time back for that
Destinations
<matatk> General progress update: https://
Lionel_Wolberger: Is look and feel the same?
matatk: May go with sidebar rather than popup.
Well-known destinations and machine-readable semantics
<matatk> rrsagnet, make minutes
Abhinav: I am considering how agentic AI would interpret our destinations
<matatk> https://
Abhinav: in my experience with recent LLM models and their reasoning
… take for example a flight booking: I have some conditions, an overall travel time and a date range
… an LLM can parse that out into source, destination, date range and constraints
… it likely has a toolkit that it then draws upon, for example an API to a flight information service
… and then another tool that takes that data, compares and filters as to the conditions it received
… the filtering may be iterative: one filter for price range, one for flight duration
… followed by another layer that may be able to use my credit card to book it
<matatk> janina: *mentions https://
janina: Innosearch is an example of such a service, it uses expedia on its backend
matatk: While we will likely implement semantics to aid in machine readability
… but I note that visual LLMs are available to do the job without semantics - i.e. more like browsing sites visually
Lionel_Wolberger: These visual presentations are coherent, typically thanks to underlying semantics
<matatk> matatk: MCP that Abhinav mentioned: https://
Abhinav: Model context protocol was put forward by Anthropic, and is commonly used by these types of agents
… it is a method to expose your LLM to such external services
… it enables an Agent to select the proper tool. The MCP exposes the tools to the Agents
… the previous generation of web agents, that use APIs to a website, can also use this MCP
… and these web agents can be called via MCP
… the MCP requires authorization
… Our approach to destinations is very much required in this context.
… Consider (a) AI Agents (b) tools (c) MCP interface
… these agents are struggling to find the relevant pages, via DOM parsing or visual inspection to find the navigation
… In my example, if a WKD clarifies that a website has an endpoint for flight search, the agent will go to that endpoint to get its results
janina: We should chase this at TPAC.
Abhinav: In summary, this WKD concept is supporting the current transition to Generative AI optimization
janina: Because we are making the URLs declarative
janina: Accessibility is more and more important, as accessibility relies on semantics and regularities that also benefit the LLMs
matatk: The 'destination' is the linkset
… checkout is more of an action than a destination
… it's a thing that you do, rather than a place that you go
… Abhinav explained this as dependent on whether you have something
… so we may need to revisit action v destination
… also, janina brought up payments
… there's payment for the final item, what you are buying; there's also paying for API usage
… web payments is for the former not the latter
Lionel_Wolberger: I like it that 'actions' would be useful for LLMs. that could motivate us to tackle that next
Abhinav: Should we add this LLM agentic consideration to the explainer?
matatk: +1
Lionel_Wolberger: +1
matatk: A short addition to the use cases section is a good place to start