Read more about Capgemini's Digital Cloud Platform → https://cloud.mongodb.com/ecosystem/c... [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa3ZZNG1yQXUwb08yVDFBMV9taHcwSV9oTmtyUXxBQ3Jtc0trQmhzc2ZNaDFSTlVDckt5RkdKTmFuT0ZkMkEyRGl4My0yYXJ5UzlzRVRKNndpLW9maTFFcUE3SENaY05UVzd4bjJJSFZhWTRRWVU4NzJlTERfdGl3ODVpNWhBcWZKazNLM3A0eWwwazRpdk1ZMkFzUQ&q=https%3A%2F%2Fcloud.mongodb.com%2Fecosystem%2Fcapgemini-digital-cloud-platform&v=fwdi_n6MbpY]In this episode of the MongoDB Podcast, Apoorva is joined by Vinay Makkaji from Capgemini and Farid Mohammad from MongoDB to discuss how enterprises are powering the next wave of Agentic AI applications. The conversation explores the shift from AI experimentation to real-world deployment, including AI agents, RAG architectures, and large-scale data modernization.They also unpack how the MongoDB–Capgemini partnership enables organizations to build scalable, production-ready AI solutions through unified data management and modern architectures. Tune in to hear practical use cases, industry examples, and where enterprise AI is headed next.Sign-up for a free cluster → https://www.mongodb.com/cloud/atlas/r... [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbjE3TEZjVzUyaDhVMnpxbUlEeVhpamVNTUNxZ3xBQ3Jtc0trYUg5NUtFaDd3Vk9odV9ubW9JSWlhWV9ZZXozUHV0YXlsQnJKMjZ3TTM1bEQzVlJGV1RycjZHdnhCTXo1YzU2QVNKbEQweWVuaWdIbjBENnJyQXhPNHVOU0QweWhkRnZjQVY3NnR1V0RjcGxsN1dVbw&q=https%3A%2F%2Fwww.mongodb.com%2Fcloud%2Fatlas%2Fregister&v=fwdi_n6MbpY]Subscribe to MongoDB YouTube→ https://mdb.link/subscribe [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbjlrQi1xR1pRMmFGQTdYMlJDTDhVTk1WVUJLd3xBQ3Jtc0ttVFJORHppc1RnZEtsRi1lUDdpc0xHamhrSE5YandnWjdZaV82Qk9SMHQxcEV5R0E5d0lhODdZTTItcTR0MDJGTlluMmFMQTRMalJZQlphcExTbHBLV1RPcnJvTHVRQ1hlNjRSQ2tkRmVvdmdwQWowRQ&q=https%3A%2F%2Fmdb.link%2Fsubscribe&v=fwdi_n6MbpY]

00:00:00 [https://www.youtube.com/watch?v=fwdi_n6MbpY] Introduction to the MongoDB Podcast 00:00:58 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=58s] Meet the Experts: Vinay Makaji & Fared Muhammad 00:03:09 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=189s] The Three Phases of genAI Evolution 00:04:47 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=287s] Shifting from Generative to Agentic AI 00:06:55 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=415s] Why AI is a System, Not Just a Model 00:10:48 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=648s] The Power of Technology Partnerships 00:17:11 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=1031s] Case Study: Predictive Maintenance in Oil & Gas 00:20:18 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=1218s] How Agentic Systems Prevent $250k/Hour Downtime 00:24:22 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=1462s] The Future: Mainframe Modernization & Industrial IoT 00:28:28 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=1708s] Key Takeaway: Partnerships Build Outcomes 00:30:22 [https://www.youtube.com/watch?v=fwdi_n6MbpY&t=1822s] Final Advice: Data Strategy is the Foundation

From Data to Decisions: Powering gen/Agentic AI with Capgemini & MongoDB

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.

Don't Build Your Own AI (Unless You Have To)

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.

How to Build Production-Ready AI Agents: MongoDB Atlas + Google Vertex AI

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.

EP. 271 The "Vibe Coding" Controversy: What Devs Are Getting Wrong About AI

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.

EP. 270 Cisco’s Approach to Developing and Governing AI Agents

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.

EP. 269 The Secret to Trustworthy AI: "Fuzzing" Your Models with Haize Labs' Co-founder

In this event, Shane McAllister will cover how Albert Podusenko got introduced to MongoDB and in 2016 decided to start a company using MongoDB as primary database behind their server, handling everything: From model states and real-time event generation to maintaining episodes and storing historical data.In this show we'll talk about:

 * How to make a product out of research.
 * Walk through it's journey that culminated with the creation of Lazy Dynamics.
 * Show how they utilize MongoDB with demos and examples.

EP. 268 How to turn chaos into opportunity

Is building the backend for your AI application slowing you down? In this episode of the MongoDB Podcast, host Jesse Hall sits down with Srikar and Jimmy, the creators of Daemo AI, a revolutionary tool designed to eliminate the tedious "plumbing" of backend development.



Discover how Daemo AI is building upon deprecated MongoDB features like Realm App Services, creating a more powerful and flexible solution for developers. We dive deep into their tech stack, including Next.js, Deno, and Express , and explore why they chose MongoDB for its speed and flexibility in AI applications.



Plus, you'll see a live demo of Daemo's new SDK and CLI , learn how it can generate data migrations and dummy data on the fly , and get a real answer to the big question: Is AI going to take your job?



In This Episode, You Will Learn: What Daemo AI is and how it accelerates development. * How to build AI agents and integrate them with frameworks like LangChain. Why MongoDB is the ideal database for rapid-growth startups and AI. The future of developer jobs in the age of AI.

EP. 267 Full Stack AI: Building with MongoDB, Deno, and Next.js

🔴 LIVE: How MongoDB Atlas Is Redefining Elasticity for Cost-Optimized PerformanceWelcome to this special episode where we explore the cutting-edge elasticity features in MongoDB Atlas—designed to help organizations optimize costs without sacrificing performance.Whether you're a software engineer, DevOps lead, or IT decision-maker, this conversation will show you how to scale smarter, faster, and more reliably.

How MongoDB Scales Atlas & Reduces Cost

Is waiting months for employee feedback a thing of the past? Dive into the future of work with Shane McAllister and L10 founders, Zyrian Chung and Keith Chan. Discover how their AI-powered platform collects daily insights to transform workplace culture, empower managers, and address issues like silent quitting before they escalate. Learn how real-time feedback and AI can create more engaged and productive teams, and get a peek into the tech (including MongoDB) that makes it possible. Stop guessing, start understanding your team today!



TAGs:

#EmployeeEngagement, #AIinHR, #WorkplaceCulture, #FutureofWork, #EmployeeFeedback, #RealTimeInsights, #TeamManagement, #Leadership, #HRTechnology, #MongoDB, #L10, #ZyrianChung, #KeithChan, #SilentQuitting, #EmployeeMorale, #TeamProductivity, #PerformanceManagement, #AITools, #EmployeeSurveys, #PeopleAnalytics

EP. 265 AI for Happier Teams: L10's Real-Time Feedback Revolution

The MongoDB Podcast features guest interviews including developers, startups, and founders with MongoDB Principal Developer Advocate Michael Lynn. Learn about new and emerging technology, how to use the various MongoDB products and best practices, how organizations are using MongoDB, and what lead them to choose MongoDB over other databases.

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