Maybe some devs here can help me, I was recently promoted to “head of AI” at my work despite being very outwardly ambivalent towards it. So I’m struggling to figure out what would actually create value instead of just being an expensive waste of time but still satisfy the higher ups AI lust.

My first idea that I thought would actually be useful was just setting up the architecture for an actual analytics database for us and then let them explore it with metabase (then letting them use Claude for their wow factor of exploring it with AI or whatever).

But now I’m somewhat at a loss, so any insight you all have would be really helpful!

  • x1gma@lemmy.world
    16·
    8 hours ago

    Since there’s zero information about what kind of company you’re working at, the following is extremely generalized.

    • integrating with monitoring systems, analytics DBs, ticket systems, whatever is used by management, allowing them to ask questions in natural language
    • process automation using agentic workflows, e.g. pre-analysis of incoming email queue summarizing / sentiment analysis before the customer support sees it
    • provide access to models and model APIs for development workflows and integration into git / ci, allowing to use llm in local development and e.g. setting up something like automated code reviews (not a replacement for human review, only as an addition)
    • set up coaching, responsible use, hallucinations, etc.

    Whatever you do, take security and data security especially into consideration first, not after:

    • consider whether your used provider reuses your data for learning
    • consider whether it’s relevant where it’s located (GDPR customers?)
    • always set spending limits
    • consider your local and your customers data protection laws and regulations that apply to your company (especially in health and financing)
    • saplyng@lemmy.worldOP
      1·
      1 hour ago

      This is wonderful thank you.

      I’m starting to get the idea that the LLM is just a small part of this and what’s really important is instead the bunch of architecture and guardrails around it to form how the humans and ai will act with any given system.