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Was on a few of these as a consultant, all major F500 companies. Most recent was a few months ago. Every instance was some variation of RAG chat/langgraph thin
by nyarlathotep_ 1y ago
Was on a few of these as a consultant, all major F500 companies. Most recent was a few months ago.
Every instance was some variation of RAG chat/langgraph thing. On multiple occasions, I heard "I don't see what value this has over ChatGPT", except they now had 5-6 figure cloud bills with it.
Technical users really weren't thrilled with it (i.e they wanted usable insights from their data (something best served by a db query), but ended up with LLM copypasta of internal docs) and seemed to expect significant functionality and utility on top of "regular" LLM use.
Stakeholders constantly complained (rightfully so) about issues with inaccuracy in responses, or "why is this presented in this fashion", resulting in hours of the data team folks coming up with new prompts and crossing fingers.
- pragmatic 1y agoSo right back to basic data engineering/analytics? “Why is this dashboard showing this number?” That’s my concern with any data “insight” magic. How do you debug what it’s telling the users?
- asudhakar11 1y agoIt should be able to tell you what assumptions it made. “Sales is $X because I assumed ARR and calendar year”. You’re then able to say great that’s what I wanted or “no I want bookings and fiscal year”.
- asudhakar11 1y agoWhy weren’t you able to show usable insights from data?