Post #3983914
2026-07-21 09:01 UTC
I've found LLM tech to be useful in limited, controlled conditions. Its current mass deployment is hard to support for ethical and environmental reasons. However, I want to keep exploring how best to use it, and of course, when NOT to use it. I'm not a freaking fanboi here. This tech has serious limits!
I've now installed pi.dev so I can work with a local model for small things, an open model for medium things, and a frontier model (which I'd rather not use) for a limited number of high-level tasks. Is this perfect? Of course not; it's a process. As open and local models improve, I'll transition over. IMHO, it's inevitable that I'll eventually be 100% local, but it might take a few years.
This setup allows me to keep working with and learning the pros and cons of the tech while steadily reducing my reliance on frontier models.
Replies (1)
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@dahukanna@mastodon.social 2026-07-21 09:46
@scottjenson@social.coop I’ve taken a “local-first” approach to explore LLM models using ollama. Main difference to frontier & other models is application interface “glue & API” code that takes care of smoothing interactions, managing “so called memory/context window”, Retrieval Augmented Generation (RAG) pipeline, vector databases grounding in recent factual data, etc. For a technology touted as “intelligent”, it requires a huge amount of “tech assistance” to function semi-decently for a human to operate.🤷🏾♀️