The journey to shippable AI systems: Patterns that work

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This post details five patterns for building shippable AI systems: guarded tool calls (timeouts, retries, circuit breakers, fallbacks, input/output persistence, cost metadata), idempotent side-effects (write-once semantics, compensating actions), human checkpoints (approval steps, handling reviewer timeouts), deterministic plans with versioned prompts (orchestration stabilization, prompt/model version recording), and cost/policy budgets (token/spend tracking, graceful degradation). It argues that Durable Execution is the backbone for these patterns, providing state, retries, visibility, and long-running task management for AI workflows.