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1. irasigman · 1790795068 · focus · HN ↗

   How do you weight the value of semantic layers when all of the labs are chasing shell usage benchmarks like TerminalBench?

   Aside from the enterprise stuff like consistent metrics I’m not convinced semantic layers improve agent performance. Case in point is Snowflake Analyst has been routing 90%+ of queries to traditional SQL as opposed to their own semantic SQL dialect.

   A semantic layer is a concept from 2018 in the BI world. Metadata is one thing but semantic layer implies an abstraction from physical data with lossy translations.

   1. ajoski9 · 1790862938 · focus · HN ↗

      Great question. Semantic layer has been around before I was even in the industry. Probably late 90's. Innovation on this layer has gone backwards actually. Simpler and less capable (Looker vs Strategy for example).

      It does however improve on agent performance in one important way: rejects plausible queries that are invalid. Agents writing sql are more likely to be inventive in unexpected ways. Business users won't know the difference. It is definitely not useful for developers/data engineers anymore. But quite a good tool as part of analytics harness for business users.

      The one issue with Snowflake semantic dialect is the lack of expressiveness. Agents have to route to sql for many common scenarios. What do you think?

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