The MongoDB Podcast

Are you trying to figure out if your team should build an AI model from scratch or integrate an off-the-shelf solution? You aren’t alone.
In this episode of the MongoDB Podcast, Shane McAlister sits down with Akshaya Murthy, Director of AI Transformation at Zendesk, to decode the maze of building enterprise AI products. They dive into why integrating is often the winning move for speed-to-market, the hidden costs of custom models, and why bad data will break even the most perfect transformer model.

What you’ll learn in this episode:
The Build vs. Buy Calculus: Why lower Total Cost of Ownership (TCO) and rapid deployment favor integration for most enterprises.

Spotting "AI Washing": How to avoid vendor buzzword salads and focus on actual problem-solving and ROI.

Architectural Must-Haves: Why your AI stack needs modular API layers, model hot-swapping, and CI/CD pipelines just like your standard code.

The "Garbage In, Hype Out" Rule: Why a solid data strategy and a centralized single source of truth are non-negotiable.

Ready to stop experimenting and start delivering real AI value? Tune in now.

In this episode, Michael Lynn (MongoDB) and Yang Li (Google Cloud) break down the architectural blueprint for building intelligent, production-grade applications. Move beyond simple RAG (Retrieval-Augmented Generation) and explore the world of AI Agents.
What you’ll learn:
The Google Cloud AI stack: Vertex AI, Agent Space, and Model Garden.

Deep-dive integration: Connecting MongoDB Atlas with BigQuery and Dataflow.

Real-world Demo: Building a grocery store AI assistant using Gemini and Vector Search.

Startup Perks: How to access up to $350k in Google Cloud credits and $10k in MongoDB credits.

Everyone's talking about AI taking over coding jobs, but what's the real story? Shane McAllister and DataCamp's Richie Cotton dive into the "vibe coding" phenomenon and expose the biggest misconceptions developers have about AI. Learn how to shift your mindset from a pure coder to a "vibe curator" and future-proof your career. Don't miss the full video discussion, available to watch now in the Spotify app.

In this live episode we’ll explore how Cisco harnesses the power of MongoDB Atlas Vector Search to enable cutting-edge AI capabilities across various projects. We’ll dive into its pivotal role in solutions like Retrieval-Augmented Generation (RAG) and the Agentic Framework, demonstrating how it serves as the backbone for efficient and scalable data retrieval. Learn how MongoDB Atlas Vector Search empowers Cisco to bridge the gap between unstructured data and intelligent AI-driven insights, fueling innovation across various use cases.

How do you test a GenAI application that's constantly changing? In this episode, Shane talks to Leonard Tang, co-founder of Haize Labs, about why traditional testing fails for LLMs and how to adopt a new evaluation strategy. Leonard introduces "fuzzing"—a powerful technique for discovering edge cases, improving reliability, and building AI you can actually trust. He also gives a live demo of the Haize Labs platform, so be sure to watch the video version on YouTube or Spotify to see it in action.