Welcome to AI Uncharted – a quiet space for navigating what still feels like uncharted territory in artificial intelligence. This blog is where I document the hard parts, the practical tools, and the process of learning in public as I try to make sense of an ever-shifting landscape.
This project wasn’t born from a grand vision. It came from the urge to better understand artificial intelligence – not from the outside looking in, but from hands-on use, honest mistakes, and slow clarity.
I’ve never called myself a developer. My work has mostly been about systems – making them work, connect, and adapt. That’s why AI caught my attention. Not because it’s shiny, but because it changes how things connect, and how decisions get made.
Why this space exists
To learn and grow
This is where I untangle the things I’m working with – AI agents, workflows, orchestration layers, infrastructure, and tools I’m still figuring out myself.
To document and reflect
Writing helps me think. Explaining something – even just to myself – forces me to confront what I understand and what I don’t. It also helps others who may be somewhere along the same path.
To show what’s possible
I share what I build not to impress, but to lower the barrier for others. If I can get these tools working, anyone can – given time, intent, and a willingness to get a little lost.
On AI
AI is not just about generating images or responding to prompts. It’s a deeper shift in how we build, automate, and think. But to use it well, you need more than curiosity. You need structure, context, and real use cases.
That’s what I’m working on here.
What to expect
This site is part lab, part logbook – and part contribution to a shared understanding of how AI tools can be explored and applied in real workflows. Some things will work, some won’t. But everything will be documented with the same goal: making complex systems a little more understandable – for myself, and maybe for you too.
Where I’m at now
While I’ve used tools like ChatGPT in my daily work since late 2023 – to solve practical problems, automate small tasks, or think through ideas – it wasn’t until early 2025 that I began exploring AI seriously and systematically.
A friend and colleague once reminded me of a useful framework by Noel Burch, describing the four stages of competence: unconscious incompetence, conscious incompetence, conscious competence, and finally unconscious competence.
When I started, I was firmly in the first stage – unaware of how much I didn’t know, mostly driven by curiosity, hype fatigue, and a growing sense that these tools were starting to matter. I couldn’t yet articulate what was possible or how the pieces fit together.
Today, I sit somewhere around conscious incompetence – aware of how much more there is to learn, but with enough structure to start asking better questions. That’s why I document so much of what I’m doing here: not to teach, but to think out loud while I’m learning.