Recording Date: February 27, 2026
Hosts: Miriah Peterson, Matt Sharp, Chris Brousseau

Running AI locally is easier than ever.
Running it securely is another story.

In this episode of Domesticating AI, we break down the moment every homelab builder hits:

The second you move from one machine to two machines…
access becomes your first real engineering problem.

We explore the real architecture questions behind self-hosting AI:

Why a dedicated machine isn’t a sandbox
Why Docker alone isn’t isolation
How homelabs evolve from Plex servers to AI infrastructure
The blast radius problem with local agents
Why networking and access control matter more than model size

We also discuss the surge in local AI hardware demand and the risks of running powerful agents on machines with unrestricted access.

Whether you're running OpenClaw, Ollama, a NAS, Postgres, or a home automation stack, the same rule applies:

Infrastructure without containment is just risk waiting to happen.

High-memory Mac Minis are seeing long shipping delays as developers rush to build local AI systems.

https://www.tomshardware.com/tech-industry/artificial-intelligence/openclaw-fueled-ordering-frenzy-creates-apple-mac-shortage-delivery-for-high-unified-memory-units-now-ranges-from-6-days-to-6-weeks

Marketplace plugins and execution boundaries are becoming a growing security concern in agent systems.

https://www.linkedin.com/posts/matthewsharp_i-use-to-do-nothing-but-post-about-clean-activity-7432832983339999232-iR04

Overview of risks around agent plugin ecosystems and execution boundaries.

https://conscia.com/blog/the-openclaw-security-crisis/

Private mesh networking used to securely access homelabs.

https://tailscale.com

Local AI coding agent framework.

https://openclaw.ai

Local LLM runtime used for running models on personal machines.

https://ollama.com

Why people actually build homelabs
Plex, NAS, and home automation as infrastructure entry points
AI workloads vs dev workloads
Why long-running services shouldn’t live on your laptop
Networking architecture for homelabs
RBAC-style access control between machines
Secrets management mistakes developers make
Containment and blast-radius thinking for AI agents
Tailscale and private mesh networking

Each host answers:

If I had $0

What I would run
What I would avoid

If I had $1K

What machine I’d buy
How I’d isolate workloads

If I had $5K

How I’d segment infrastructure
What monitoring I’d deploy
What I would never expose to the internet

Staff Data Engineer, content creator, and founder of SoyPete Tech.
Miriah focuses on practical AI systems, Go infrastructure, and self-hosted AI engineering.

She is also a Google Developer Expert in Go and organizer of Go West Conf.

https://soypete.tech

AI engineer and co-author of LLMs in Production.
Matt focuses on applied AI systems, local model infrastructure, and developer-focused AI tooling.

Software engineer and AI practitioner focused on practical applications of machine learning and developer infrastructure.

Domesticating AI is supported by the SoyPete Tech community.

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