# We all start somewhere > Source: > Published: 2026-06-29 10:17:45+00:00 After many years of coding small projects and experimenting with GitHub, mainly around development and pentesting, I’ve found myself increasingly drawn into the AI world. The speed at which AI is evolving is honestly fascinating. I’m now looking beyond simply using AI tools and want to properly understand how to build with them from better prompting techniques, to running models locally, to understanding how these systems actually work. One of my biggest interests is creating a truly offline AI setup. I’ve been exploring local models, GGUF and abiliterated formats, running models on desktop hardware or even from portable USB/SSD setups, and finding practical alternatives to constantly relying on API keys (especially when experimenting with larger or more capable models can quickly become expensive). So looking for new models to run, or potentially learn to build. There is so much happening right now across: local LLMs coding models image/video generation text-to-image and text-to-video workflows multimodal models fine tuning and custom models RAG systems and private knowledge bases The amount of choice is both exciting and overwhelming. A little background: I’ve been developing for 25+ years across a range of technologies, including: Python PHP / Laravel Vue.js / jQuery LAMP stack MySQL NoSQL databases Elasticsearch / Lucene legacy web systems and application development I’m now looking to add AI engineering to that skill-set not just as a user, but by learning how to build, evaluate, run, and optimise models. My current goals are: understanding the best ways to instruct models learning when to use prompting vs RAG vs fine tuning building local AI assistants experimenting with coding models creating private/offline AI workflows understanding the practical side of deploying AI systems I’d love to hear from the community