Episode Details

Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google, and Amazon

Published 5 months, 1 week ago

Description

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. The goal of this conversation is to save you and your team a lot of pain and suffering.

We discuss:

1. Two key ways AI products differ from traditional software, and why that fundamentally changes how they should be built

2. Common patterns and anti-patterns in companies that build strong AI products versus those that struggle

3. A framework they developed from real-world experience to iteratively build AI products that create a flywheel of improvement

4. Why obsessing about customer trust and reliability is an underrated driver of successful AI products

5. Why evals aren’t a cure-all, and the most common misconceptions people have about them

6. The skills that matter most for builders in the AI era

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Transcript: https://www.lennysnewsletter.com/p/what-openai-and-google-engineers-learned

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My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/183007822/referenced

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Get 15% off Aishwarya and Kiriti’s Maven course, Building Agentic AI Applications with a Problem-First Approach, using this link: https://bit.ly/3V5XJFp

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Where to find Aishwarya Naresh Reganti:

• LinkedIn: https://www.linkedin.com/in/areganti

• GitHub: https://github.com/aishwaryanr/awesome-generative-ai-guide

• X: https://x.com/aish_reganti

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Where to find Kiriti Badam:

• LinkedIn: https://www.linkedin.com/in/sai-kiriti-badam

• X: https://x.com/kiritibadam

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Where to find Lenny:

• Newsletter: https://www.lennysnewsletter.com