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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 Warnings Over Errors, Graceful Degradation by Default One Config, Many Surfaces Contract-Driven Integration GitOps as the Boring Substrate

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

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Build Your Own Legs Before the Crutches FailMar 9, 2026 · 14 min
AI-assisted development is useful leverage, but only if you convert borrowed competence into real judgment before the support becomes a dependency.
Explicit Control Loops Playbook: AI-Assisted Dev Adoption Loop Playbook: Agent Rollout With Guardrails
Repo Design Patterns for AI-Assisted Dev: Control Loops, Hooks, and MemoryFeb 9, 2026 · 5 min
Treat your repo like a control system: instruction hierarchy, workflows, hooks, and shared memory that make AI-assisted dev fast, reproducible, and hard to derail.
Explicit Control Loops One Config, Many Surfaces Playbook: AI-Assisted Dev Adoption Loop Playbook: Agent Rollout With Guardrails
Loom: One Registry, Many AI Coding AssistantsFeb 9, 2026 · 6 min
How Loom keeps MCP servers and skills in sync across Codex, Claude, Gemini, VS Code, Antigravity, Kilocode, OpenCode, and Zed.
One Config, Many Surfaces Playbook: AI-Assisted Dev Adoption Loop Playbook: Agent Rollout With Guardrails
Building Practical AI AgentsNov 15, 2025 · 4 min
What makes an AI agent reliable in production: explicit loops, bounded tools, and visible operator state.
Explicit Control Loops Contract-Driven Integration Playbook: AI-Assisted Dev Adoption Loop Playbook: Agent Rollout With Guardrails