Curiosity, micro-sales, and AI as a supplement with Shaundai Person

Kent introduces Shaundai Person, a senior software engineer at Netflix specializing in privacy and consent on Netflix.com. They discuss her career transition from a decade in sales to engineering, emphasizing her approach to cross-team collaboration as a series of 'micro-sales'—engaging others through curiosity and questions rather than prescriptions. Her background in sales profoundly influences her communication style in tech teams.

Shaundai details her role at Netflix, focusing on privacy and consent management. She emphasizes the importance of designing user experiences that are intuitive, ensuring compliance across different regions with diverse data laws, and safeguarding user data, including children's privacy. She explains her responsibilities are primarily about shaping the user interface and experience, not handling the data itself, which remains with specialized teams.

She explains her approach to collaborating across teams—viewing conversations as 'micro-sales,' where she presents problems, seeks feedback, and collaboratively explores solutions. She highlights the value of curiosity, asking questions, and involving others to find effective, user-centered solutions. She's conscious of legal implications and technical constraints and advocates for clear communication, ongoing feedback, and thoughtful planning to implement changes.

Shaundai discusses how AI accelerates both good and bad practices in software development. She envisions the future where engineers shift from ticket-based task execution to high-level architectural and product thinking—akin to orchestration. She warns that unchecked AI use can lead to disorganized codebases filled with patches ('band-aids') and stresses the importance of human oversight, documentation, and maintaining architecture standards.

She warns about the risks of diminishing code cohesion when relying heavily on AI-generated code, leading to inconsistent patterns and an increase in 'band-aids' across repositories. She advocates for continuous refactoring, documentation, and adherence to best practices to keep the architecture sustainable, emphasizing that AI should supplement human judgment, not replace it.

Shaundai believes that AI will elevate engineers toward architecture, product thinking, and system design—adding new criteria for what makes an exceptional engineer. She stresses the importance of understanding both high-level architecture and detailed technical work, warning that neglecting either can harm long-term productivity. The focus is on deliberate skill development to navigate an AI-augmented environment.

She emphasizes that AI remains a tool to be wielded by humans, with software still fundamentally for human use. She underscores the necessity of human oversight, curiosity, and continuous improvement to use AI effectively. She also advocates for intentional, thoughtful use of AI rather than rushing to adopt new technologies for speed's sake.

Shaundai recommends a specific hands-on activity: trying Josh Comeau's Whimsical Animations or a CSS-based starter project without using AI. The goal is to strengthen problem-solving skills, understand the process better, and identify where tools can genuinely add value. This exercise encourages developers to refocus on foundational skills and deliberate craftsmanship.