Intro to Building a Quality-First AI Coding Workflow

In a recent workshop, Nnenna Ndukwe demonstrated a quality-first AI coding workflow using SignalPay, a FastAPI payments API, to add a refund endpoint without compromising code quality. The approach emphasizes defining task requirements and constraints before coding, ensuring that AI-assisted code changes are testable and maintainable. Key aspects of the workflow include using agentic engineering principles, such as planning, behavior-driven development, and implementing deterministic checks like linting and type checking before submitting pull requests. The process also involves local pre-PR reviews and independent code reviews to identify and fix deeper code issues, ensuring that changes meet all defined requirements and constraints. Ndukwe highlights the importance of visible documentation and clear task definitions for agents, advocating for a looped workflow that integrates rules, agent skills, and verification plans to maintain high-quality code generation and implementation.

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