- Joined
- May 22, 2001
- Messages
- 2,019
Background: Been working in the industry since ~2004. Solid two decades in all sorts of things orbiting data.
The past few months I've been leveraging VSCode/Claude Code to handle myriad data modeling, architecture, engineering, bi developer, documentation author, tasks. Some large projects, others one off. I think it's gone very well, quite successful with outcomes.
What's running through my head, as organizations roll these things out, is who is best suited to take real advantage of LLMs. My anecdotal observation is that experiences, seasoned people are more effective.
It makes sense - but I don't have a sense my own organization, and others, are looking at it like this. A company rolls out an LLM, it can go wide. Massive platform in the hands of people who don't yet have the capacity to understand the broader implications of their work. They don't have the experience of managing teams, structuring large chunks of work, prioritizing steps in order to achieve good results. All the things we pick up along the way that influence our ability to identify problems, work through and implement solutions.
edit: The other facet of this is ensuring a good pipeline of juniors, succession planning and the like. And I'm in this state of uncertainty on what is truly necessary for someone to learn and understand in order to do their work. And my comparison would be when I started off, the tools I had, being abstracted away from what people in the 70s or 80s would need to do. To write software, work with a database, it was much lower-level. We abstracted that away over time, and people didn't become incapable of understanding data, how it relates or drawing conclusions from it. The how changed.
So is it okay if someone is an effective prompter but doesn't understand the fundamentals of a star schema? I don't know.
There's no point here other than opening up for thoughts. I want to solidify something on this though, as it impacts some decisions I'm considering across the business. So your discussion here would be helpful.
Happy Friday!
The past few months I've been leveraging VSCode/Claude Code to handle myriad data modeling, architecture, engineering, bi developer, documentation author, tasks. Some large projects, others one off. I think it's gone very well, quite successful with outcomes.
What's running through my head, as organizations roll these things out, is who is best suited to take real advantage of LLMs. My anecdotal observation is that experiences, seasoned people are more effective.
It makes sense - but I don't have a sense my own organization, and others, are looking at it like this. A company rolls out an LLM, it can go wide. Massive platform in the hands of people who don't yet have the capacity to understand the broader implications of their work. They don't have the experience of managing teams, structuring large chunks of work, prioritizing steps in order to achieve good results. All the things we pick up along the way that influence our ability to identify problems, work through and implement solutions.
edit: The other facet of this is ensuring a good pipeline of juniors, succession planning and the like. And I'm in this state of uncertainty on what is truly necessary for someone to learn and understand in order to do their work. And my comparison would be when I started off, the tools I had, being abstracted away from what people in the 70s or 80s would need to do. To write software, work with a database, it was much lower-level. We abstracted that away over time, and people didn't become incapable of understanding data, how it relates or drawing conclusions from it. The how changed.
So is it okay if someone is an effective prompter but doesn't understand the fundamentals of a star schema? I don't know.
There's no point here other than opening up for thoughts. I want to solidify something on this though, as it impacts some decisions I'm considering across the business. So your discussion here would be helpful.
Happy Friday!