[lifeisstillgood]

So, and I may be oversimplifying, you are creating awesome documents and references that I would have loved to have for my different jobs 5-10 years ago (or more).

It’s just that making such docs had next to no ROI 10 years ago. But today they are the difference between success and failure.

It’s fascinating - thank you

(and who writes the wiki / business rules ? Can they be reverse engineered from existing query stack? )

Sounds great - all the best

Edit: don’t take the above as criticism - just trying to fit new ideas into an old dog.

[andreybavt]

Thanks! yes, exactly. But what you described is just half of what ktx does, we call it "wiki" - self organizing collection of ingested markdown files.

The second (equally important) part of ktx is similarly self-organizing executable semantic layer.

It allows agents to send simple declarative "I want X sliced by Y" requests instead of imperative "X sliced by Y that has to be queried this way and joined the other way ..."

To answer your questions:

> who writes the wiki / business rules most is create after `ktx ingest` pulls raw data from your data stack, it can be edited/created manually, but it's rarely necessary. Also if you plug ktx to your agent it allows that agent to send extra memories for ingestion to keep the context up to date

> Can they be reverse engineered from existing query stack Yes, that's the case when we analyze historic SQL queries or scan Looker or Metabase dashboards for example

[lucamrtl]

Just to clarify what semantic layer is: you can think of it as a set of functions

So you define the definitions of metrics like "monthly revenue" once, and that definition is runnable. If an agent asks for "monthly revenue by region", the semantic layer will compile that request into SQL and run it (the same way everytime so that calculation method is consistent)

[lifeisstillgood]

Thank you … one can see how “semantic layer for whole enterprise” is a PowerPoint slide that can make McKinsey drool

[andreybavt]

Hopefully more agents and fewer PowerPoints and McKinsey folks in the future :)