I love exploring new tools and writing about the ones that actually solve problems. Like my recent piece on Developer Tools That Actually Matter in 2026, this article covers a subset of the open-source LLM tooling landscape from model selection and inference to fine-tuning and security. This time, I am going deeper into the security layer, because shipping an LLM without it is like opening a port without a firewall. You can read my previously posted articles on my website. This article comes from months of research and exploration of multiple tools.
If you have been building with large language models for a while, you know the frustration. Pick a model, wire up a call, stare at the output, hoping it looks like what you asked for. Sometimes it does. Often it does not. And if you are running locally, there is a whole separate problem: which model will your machine even handle?