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Title: When to use AI
Date: 2025-06-05 20:00
Modified: 2025-06-06 08:00
Category: AI, Data
Tags: ai, python
Slug: when-to-use-ai
Authors: Andrew Ridgway
Summary: Should we be using AI for ALL THE THINGS!?
# Human Introduction
Well.. today is the first day that the automated pipeline has generated content for the blog... still a bit of work to do including
1. establishing a permanent vectordb solution (chromadb? pg_vector?)
2. Notification to Matrix that something has happened
3. Updating Trilium so that the note is marked as blog_written=true
BUT it can take a note from trilium, generate drafts with mulitple agents, and then use RAG to have an editor go over those drafts.
I'm particularly proud of the randomness I've applied to temperature, top_p and top_k for the different draft agents. This means that each pass is giving me quite different "creativity" (as much as that can be applied to an algorithm that is essentially munging letters together that have a high probability of being together) It has created some really interesting variation for the editor to work with and getting some really interesting results.
Anyways, without further ado, I present to you the first, pipeline written, AI content for this blog
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# When to Use AI: Navigating the Right Scenarios
Okay, so I've been getting this question a lot lately: "When should we use AI?" or even more frustratingly, "Why can't AI do this?" It's like asking when to use a hammer versus a screwdriver. Sometimes AI is the perfect tool, other times it's better left in the toolbox. Let me break down some scenarios where AI shines and where it might not be the best bet.