AI Can Generate the UI. Can You Ship It?

About this session

AI coding tools can generate a working interface in minutes, but working code is not the same as production-ready code. Generated UIs can introduce accessibility failures, fragile interactions, inconsistent components, and testing gaps that surface only after development moves downstream. This session presents a practical engineering approach for adding verification to AI-assisted frontend development. We will look at how design-system constraints, automated accessibility checks, test scaffolding, CI quality gates, and human review can work together to catch problems early without losing the speed benefits of AI. Attendees will leave with a framework they can adapt to teams already using AI coding assistants.

Speaker

• Niharika Pramod Pujari, Lead Software Engineer, McGraw Hill

Key takeaways

• Identify the hidden quality gaps in AI-generated frontend code before they reach production.
• Build accessibility, testing, and design-system constraints directly into AI-assisted development workflows.
• Create practical verification gates that preserve AI development speed while improving reliability and maintainability.

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