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Every blog post and case study on the site with the principles and playbooks each piece argues for. Filter by any principle or playbook to see just the evidence behind it.

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PrincipleAll Explicit Control Loops Evidence First, Measure Before You Optimize Classify Failures, Then Choose Recovery One Config, Many Surfaces Contract-Driven Integration GitOps for Reviewable Operations

PlaybookAI-Assisted Dev Adoption Loop AI Infrastructure Readiness Audit Healthcare Integration Onboarding Agent Rollout With Guardrails

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Operating a Kubernetes LLM Platform on Consumer GPUsCase studyJan 15, 2026
How I evolved a small AMD GPU cluster into a CRD-driven inference platform with an OpenAI-compatible boundary, evidence-based model promotion, and safe rollouts.
Evidence First, Measure Before You Optimize GitOps for Reviewable Operations Playbook: AI Infrastructure Readiness Audit
Standing Up a GPU-Ready Private AI Platform (Harvester + K3s + Flux + GitLab)Dec 29, 2025 · 5 min
Field notes from building and operating a small private GPU platform with Harvester, K3s, and a GitLab -> Flux delivery loop.
One Config, Many Surfaces GitOps for Reviewable Operations Playbook: AI Infrastructure Readiness Audit
Building an Operator-Focused Kubernetes DashboardCase studyNov 1, 2025
How FlexDeck combines Kubernetes, Flux, CI, observability, and model state without hiding freshness, access boundaries, or the limits of a homelab control surface.
Explicit Control Loops One Config, Many Surfaces GitOps for Reviewable Operations