# Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google, and Amazon Page: https://stenobird.com/podcast/lenny-s-podcast/why-most-ai-products-fail-lessons-from-50-ai-deployments-at-openai-google-and-amazon Text version: https://stenobird.com/podcast/lenny-s-podcast/why-most-ai-products-fail-lessons-from-50-ai-deployments-at-openai-google-and-amazon.md Podcast: [Lenny's Podcast: Product | Career | Growth](https://stenobird.com/podcast/lenny-s-podcast) Published: 2026-01-11T13:31:22+00:00 Episode link: https://www.lennysnewsletter.com/p/what-openai-and-google-engineers-learned Audio file: https://pscrb.fm/rss/p/api.substack.com/feed/podcast/183007822/2b837414840ab980e55aefc8ec5ab324.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/lenny-s-podcast/episodes/why-most-ai-products-fail-lessons-from-50-ai-deployments-at-openai-google-and-amazon Duration seconds: 5182 ## Resource 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 — Brought to you by: Merge —The fastest way to ship 220+ integrations: https://merge.dev/lenny Strella —The AI-powered customer research platform: https://strella.io/lenny Brex —The banking solution for startups: https://www.brex.com/product/business-account?ref_code=bmk_dp_brand1H25_ln_new_fs — Transcript: https://www.lennysnewsletter.com/p/what-openai-and-google-engineers-learned — My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/183007822/referenced — 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 — Where to find Aishwarya Naresh Reganti: • LinkedIn: https://www.linkedin.com/in/areganti • GitHub: https://github.com/aishwaryanr/awesome-g… ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/lenny-s-podcast/episodes/why-most-ai-products-fail-lessons-from-50-ai-deployments-at-openai-google-and-amazon/transcription-requests` — Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/lenny-s-podcast/why-most-ai-products-fail-lessons-from-50-ai-deployments-at-openai-google-and-amazon.md` — Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.