Aishwarya Naresh Reganti
AI Product Consultant & Educator at Maven / Former Alexa & Microsoft
Early AI researcher at Alexa and Microsoft with 35+ published research papers who has supported over 50 AI product deployments and teaches the top-rated AI product course on Maven.
Dimension Profile
Key Themes
Episode Summary
Aishwarya Reganti explains why building AI products is fundamentally different from traditional software, centering on non-determinism and the agency-control tradeoff. She advocates for incremental autonomy deployment — starting with high human control and low AI agency, then progressively increasing autonomy as trust is built — and emphasizes that AI transformation requires leaders who are hands-on, cultures of empowerment, and obsessive understanding of workflows.
Leadership Principles
- → Building AI products requires understanding that non-determinism fundamentally changes the product development lifecycle
- → Start with high control and low agency, then incrementally increase autonomy as trust is earned
- → Leaders must rebuild their intuitions for AI — the CEO being hands-on with AI is the top predictor of success
Notable Quotes
"Most people tend to ignore the non-determinism. You don't know how the user might behave with your product, and you also don't know how the LLM might respond to that."
— On the fundamental difference between building AI and traditional software products
"Every time you hand over decision-making capabilities to agentic systems, you're kind of relinquishing some amount of control on your end."
— Introducing the agency-control tradeoff concept
"It's not about being the first company to have an agent among your competitors. It's about have you built the right flywheels in place so that you can improve over time."
— On sustainable AI product strategy vs. rushing to ship agents
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