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Ship It

Shipping is where the AI work loop becomes operational: configuration, coding, evals, observability, trust architecture, and production standards. The leap from drawing the chart to running the voyage.

Who This Is For​

Use this section when a workflow has moved from discovery into build or operation. Business leaders can use it to know what proof to ask for; operators and developers can use it to build the proof.

Where To Start​

Design AI-native execution patterns — Agentic Workflows

Configure AI coding agents and shared rules — Agentic Coding

Define what good AI output means — AI Product Principles

Measure model and agent quality — AI Evaluation

See why systems fail in production — AI Observability

Establish authorization and trust boundaries — Trust Architecture

  • Work Mapping — the business workflow shipping should serve.
  • AI Toolkit — models, prompts, skills, MCP, chat, and CLI choices.
  • AI Agents — autonomous AI agent profiles and framework selection.

Questions​

What evidence would prove the AI system improved the workflow rather than only producing a convincing demo?