Spec-Driven Development: Agentic Coding at FAANG Scale and Quality — Al Harris, Amazon Kiro

Structured alternative to vibe coding

Unlike informal prompting, Spec-Driven Development compresses the SDLC into requirements, design, and execution phases with formal artifacts representing system state at any point in time.

EARS requirement syntax standardization

Converts natural language prompts into structured requirements using Easy Approach to Requirements Syntax, creating precise acceptance criteria that serve as the single source of truth.

Holistic lifecycle integration

Synthesizes discovery, requirements, and design into a tight inner loop that respects decades of software engineering practices while accelerating delivery through rapid feedback.

Property-based testing integration

Translates EARS requirements directly into system invariants that automatically falsify incorrect implementations, providing high-confidence verification that code meets specifications.

Automated requirements validation

Scans requirements for ambiguities and logical conflicts using automated reasoning techniques before any code generation begins.

Mandatory test case embedding

Allows developers to define explicit unit test cases within task specifications, preventing agents from marking tasks complete without passing validation.

MCP servers across all workflow phases

Integrates Model Context Protocol during requirements, design, and implementation to pull external data like Asana tasks or GitHub issues directly into the specification.

Customizable natural language artifacts

Enables modification of any spec component—such as adding ASCII wireframes or additional test protocols—since artifacts remain natural language processed by the agent.

Left-shifted design concerns

Uses external data sources and stakeholder input to resolve design questions during specification rather than during implementation, reducing downstream rework.