Crucially, this distribution of border points is agnostic of routing speed profiles. It’s based only on whether a road is passable or not. This means the same set of clusters and border points can be used for all car routing profiles (default, shortest, fuel-efficient) and all bicycle profiles (default, prefer flat terrain, etc.). Only the travel time/cost values of the shortcuts between these points change based on the profile. This is a massive factor in keeping storage down – map data only increased by about 0.5% per profile to store this HH-Routing structure!
Moment of introspection aside, I’m not sure what the future holds for agents and generative AI. My use of agents has proven to have significant utility (for myself at the least) and I have more-than-enough high-impact projects in the pipeline to occupy me for a few months. Although certainly I will use LLMs more for coding apps which benefit from this optimization, that doesn’t imply I will use LLMs more elsewhere: I still don’t use LLMs for writing — in fact I have intentionally made my writing voice more sardonic to specifically fend off AI accusations.
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