GENERATIVE AI
Local LLM Lab
Experiments with running language models locally, serving models, and connecting AI tools to practical workflows.
I'm an IT Engineer exploring the intersection of generative AI, cloud infrastructure, data engineering, and automation. I enjoy turning complex technical challenges into useful, dependable systems.
class Engineer:
focus = [
"Generative AI",
"LLM applications",
"Cloud infrastructure",
"Automation"
]
def build(problem):
# Learn, experiment, deliver
return useful_solution
01 / ABOUT
My background spans IT operations, Linux environments, deployment workflows, databases, and infrastructure. I'm expanding that foundation into generative AI and LLM engineering.
Here, I document what I build and learn: experiments with local models, AI application patterns, infrastructure projects, and practical lessons from troubleshooting real systems.
02 / SELECTED WORK
A selection of areas I'm building in. Project details and repository links can be added as each project is ready to publish.
GENERATIVE AI
Experiments with running language models locally, serving models, and connecting AI tools to practical workflows.
DATA ENGINEERING
A vessel-tracking workflow for collecting AIS positions, storing trajectories in PostgreSQL, and exploring ship movements.
CLOUD / DEVOPS
Linux services, virtual machines, containerized applications, deployment workflows, and reliable self-hosted systems.
03 / NOTES FROM THE FIELD
Practical write-ups, experiments, and lessons learned. These are starter article ideas; publish each post when its content is ready.
GENERATIVE AI
Notes on model serving, hardware constraints, and connecting local models to applications.
DATA ENGINEERING
A look at collecting vessel positions and turning them into useful geospatial history.
CLOUD & LINUX
A reproducible deployment workflow for a portfolio and technical blog.