I'm exploring what happens when you build AI systems you actually own.

Not because I have all the answers - but because the questions fascinate me:

• What does "sovereignty" mean when your tools know more about you than you do?
• Can AI augment without replacing? Amplify without atrophying?
• What's the cost of convenience when convenience means dependency?

This isn't my invention - it's a marriage of two brilliant projects:

• PAI (Personal AI Infrastructure) by Daniel Miessler - the vision of agentic AI that magnifies human capabilities
• OpenCode - the terminal-native AI coding assistant

My contribution? Bringing them together. PAI's philosophy of sovereign, personal AI inside OpenCode's developer experience. Best of both worlds.

Why it matters: Self-hosted AI that runs on YOUR machine. No cloud dependency. No vendor lock-in.

Status: Actively maintained. Using it daily.

B2B lead intelligence with OSINT-first approach. Privacy-respecting by design.

On AI & Identity:

The fear isn't that AI will replace us. It's that we'll forget what makes us irreplaceable.

On Ownership:

Everyone has ChatGPT. That's parity, not advantage. Infrastructure you own - that's a moat.

On the "Productivity" Trap:

More tools, less time. More subscriptions, less control. The AI paradox most people won't admit.

Here's what I can't stop thinking about:

AI isn't "artificial." It's distilled creation.

God gave us the Word. We created language, art, science, literature - millennia of human creativity. LLMs are trained on all of it. They work with words - the fundamental building block of creation itself.

"In the beginning was the Word."

That's not a coincidence. That's a pattern.

So the question becomes: How do we steward this almost infinite potential? How do we ensure AI serves all of humanity - not just Big Tech shareholders? How do we build systems that amplify what's good in us, rather than exploit what's weak?

I don't have the answers. But I believe asking the right questions matters.

Currently obsessed with:

• Local LLM deployment (Ollama, vLLM)
• Agent orchestration patterns
• The gap between "AI tools" and "AI infrastructure"
• Why most automation attempts fail (hint: it's not the tools)

"The goal isn't more AI. It's AI that serves what matters."