Agentic Ai Homelab

agentic-ai-homelab

How I work with agentic AI, end-to-end: cloud LLM APIs, local self-hosted models, project scaffolding, and the connective tissue between them.

Not a tutorial. Not best practices. **This is what I run.** Patterns here have been used in real projects; configs here are the actual templates I deploy (with secrets stripped). Take what's useful, leave the rest.

Status

**v0.2 — all four pillars are real.** Templates bootstrap; infra composes deploy; cloud workflow examples run; agent harness configs drop in. Plus a top-level `provider-bakeoff/` that compares 10 LLM providers across 4 countries on the same tasks with real cost numbers.

What's still open: ops items that need live access (image-tag pinning post-boot), Claude Code `settings.json` extraction, and existing project AGENTS.md dedup. See [`docs/wip/NEXT_STEPS.md`](docs/wip/NEXT_STEPS.md).

Continuity log: [`docs/history/`](docs/history/) — `0001-genesis.md` is the founding session, `0003-v0.2-arc.md` is the arc that brought the four pillars to real.

What's here

.
├── AGENTS.md                 — repo-scoped agent rules (harness-agnostic)
├── CLAUDE.md                 — Claude Code entry; imports AGENTS.md so every harness picks up the same rules
├── LICENSE                   — MIT
├── docs/                     — narrative + recipes + history (MkDocs site)
│   ├── philosophy.md         — the underlying "how I work" 1-pager
│   ├── project-setup.md      — pillar 1: scaffolding for new projects
│   ├── local-ai-infra.md     — pillar 2: self-hosted LLM stack (vLLM + Ollama + observability)
│   ├── cloud-ai-workflow.md  — pillar 3: working with Claude / OpenAI / Gemini APIs
│   ├── agent-harnesses.md    — pillar 4: opencode / Claude Code / MCP registry
│   ├── recipes/              — operator-facing recipes (DGX dashboard, GPU mode-swap, ...)
│   ├── adr/                  — architecture decision records for this repo
│   ├── rfc/                  — open proposals not yet decided
│