Aishwarya Naresh Reganti + Kiriti Badam
Aishwarya Naresh Reganti and Kiriti Badam have helped build and launch more than 50 enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they’ve developed a small set of best practices for building and scaling successful AI products.
Overlay: Building AI Products Skills
Safely deploying agentic systems requires a graduated approach that begins with human-in-the-loop suggestions and scales to full autonomy only after building confidence and reliability.
"You need to be deliberately starting in places where there is minimal impact and more human control so that you have a good grip of what are the current capabilities and what can I do with them and th..."
The competitive advantage in AI products is not speed to launch, but the ability to build infrastructure for continuous learning and iterative calibration in production.
"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."
Building AI-native products requires a fundamental shift from fixed decision engines to managing fluid natural language interfaces and the trade-off between system autonomy and user control.
"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. The second difference is the agen..."