Kiro vs Cursor: Specs, Agents, and How Each Verifies Code

Kiro and Cursor are compared as AI-assisted development environments with different workflows: AWS-backed Kiro emphasizes repository-based, requirements-first specifications using EARS-formatted requirements, design documents, and task files, while Cursor emphasizes editor-centric planning through editable markdown plans and built-in browser automation. Both support shared AGENTS.md instructions, project-specific rules, MCP integrations, stop hooks that can re-prompt agents after failed checks, and headless CLI operation, but Kiro offers broader IDE, CLI, web, and mobile surfaces through a unified agent harness whereas Cursor provides faster in-editor iteration and native browser access. The walkthrough demonstrates converting acceptance criteria for a staff-table search feature into real-browser Kane CLI checks, revealing that an apparent implementation failure may instead expose an incorrect requirement, such as mismatched empty-state wording. It recommends using external, deterministic browser validation and evidence packs to independently verify agent work, connecting those checks to hooks and CI pipelines rather than relying solely on the coding agent’s own completion judgment. Kiro is positioned for teams seeking traceable specifications and structured task workflows, while Cursor is positioned for rapid editing and browser-based UI iteration; teams using both can share instructions and verification scripts while maintaining tool-specific configuration.

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