Welcome to Let’s Talk Shop! In this episode, host Elias Khnaser is joined by cloud industry expert Sanjeev Mohan to break down the biggest takeaways from AWS re:Invent.

The landscape of cloud and enterprise tech is shifting rapidly, and keeping up with the "onslaught" of new models and technologies can be deafening for IT professionals. We dive deep into why this year’s re:Invent felt different—from the "AI agent" saturated keynotes to the game-changing announcements that actually matter for your business.

We discuss:

► The MultiCloud Pivot: Why AWS finally "threw in the towel" and embraced multi-cloud with the new AWS Interconnect.

► AI Factories: A look at AWS’s new approach to on-prem AI infrastructure.

► Nova Forge vs. RAG: Sanjeev explains why Nova Forge is a differentiator, allowing companies to build and tune proprietary frontier models for just $100k/year.

► The Future of Interconnectivity: How the industry is moving toward pointing compute at data, regardless of which cloud provider holds it.

2026 Predictions: What’s next for the market as AI continues to "take the oxygen out of the room".

Sign Up Now for my online course "The Cloud Strategy Master Class":
► On my web site: https://lnkd.in/gcxcrX and use promo code LINKEDIN20 to receive a 20% discount.
► On Udemy: https://www.udemy.com/course/cloud-strategy-master-class/

PODCASTS: Listen wherever you get your podcasts:
► Let's Talk Shop: http://letstalkshop.buzzsprout.com
► Reality Distortion Fields RDFs Podcast: https://youtu.be/88z1UiVaV00

Follow me:
► TikTok: @ekhnaser
► Instagram: @ekhnaser
► Twitter: @ekhnaser
► LinkedIn: https://www.linkedin.com/in/eliaskhnaser/
► Website: www.eliaskhnaser.com

How close are we to building Jarvis from Iron Man? Host Elias Khnaser sits down with Ali Maaz, AWS's leader for Go-to-Market Developer Services, to discuss how Amazon Q (Kiro) is transforming from a simple coding assistant to an Autonomous Agent and a peer on your team.

Recorded live at AWS re:Invent 2025, this conversation dives deep into the future of enterprise software development and Cloud Operations.

Key Takeaways:

► The Evolution of AI Agents: Why the biggest problem isn't coding, but the planning cycle—and how Kiro is solving it by arbitrating between product and engineering teams.
► Autonomous Agents: Our first look at Kiro Autonomous Agents, designed to address issues like bug fixes right out of Slack or Teams without a human opening a laptop.
► The Trust Factor: How AWS builds validation and trust with Property Based Testing, making Kiro a reliable, productive teammate.
► Cloud Ops Revolution: A major announcement focusing on a new agent specifically for Cloud Operations and DevOps to reduce Mean Time to Resolution (MTTR) and detect state/policy drift.
► AWS Differentiation: How AWS remains focused on customer-driven innovation, viewing internal teams (like Amazon.com) as just one of their largest and most important customers.
► The era of "bolt-on AI" is ending. The next step is "AI-driven development and operations." Tune in to see how you can "get out of the way" and let AI manage your next big project.

00:00:00 Intro & Guest Welcome: Ali Maz, AWS Developer Services
00:01:11 The "Jarvis" Question: How Close is AWS Q to Iron Man's AI?
00:01:46 Beyond Coding: Kiro's Role in the Planning Cycle (PR-FAQ)
00:03:43 Announcement 1: Kiro Autonomous Agent (From Assistant to Peer)
00:05:21 Building Trust: Validation, Oversight, and the Human in the Loop
00:06:46 Automated Reasoning & Property Based Testing (AI Validating AI)
00:07:34 Announcement 2: Kiro Powers & Personalized Context for ISVs
00:10:40 Agent Core: Policy Management & Evaluation for Production-Grade Agents
00:12:43 AWS Differentiation: Why We are Customer-Obsessed, Not Competitor-Obsessed
00:14:12 New Agent Announced: Focused on Cloud Operations & DevOps
00:16:33 The AI Evolution: Moving to "AI Managed" and "Get Out of the Way"
00:17:47 Conclusion & Wrap-up

Sign Up Now for my online course "The Cloud Strategy Master Class":
► On my web site: https://lnkd.in/gcxcrX and use promo code LINKEDIN20 to receive a 20% discount.
► On Udemy: https://www.udemy.com/course/cloud-strategy-master-class/

PODCASTS: Listen wherever you get your podcasts:
► Let's Talk Shop: http://letstalkshop.buzzsprout.com
► Reality Distortion Fields RDFs Podcast: https://youtu.be/88z1UiVaV00

Follow me:
► TikTok: @ekhnaser
► Instagram: @ekhnaser
► Twitter: @ekhnaser
► LinkedIn: https://www.linkedin.com/in/eliaskhnaser/
► Website: www.eliaskhnaser.com

Is storage is the new bottleneck in the age of AI? Elias Khnaser and Asad Khan, Senior Director of Google Cloud Storage, discuss this topic in depth. While all the spotlight is on fast, expensive GPUs and TPUs, Elias and Asad are back to basics.

In the past, CPU was never the bottleneck; slow storage was. Today, AI training and inferencing workloads require feeding high-cost GPUs/TPUs with data at an unprecedented speed to prevent them from sitting idle and wasting millions of dollars.

Key Takeaways:

► The shift: Why high-performance storage is now mission-critical for maximizing your ROI on massive GPU clusters.
► How Google Cloud is solving the data performance problem by moving beyond HDDs to intelligent SSD tiering.
► Deep dive into Google Cloud Storage solutions for AI, including Anywhere Cache and Rapid Store, designed to automatically handle caching, prefetching, and high-performance throughput across all zones without the customer having to worry about colocation.
► The importance of data APIs for researchers: object storage (GCS) vs. full POSIX compliance (Lustre).
► The truth: The best AI performance isn't just about the fastest chip—it's the correct configuration of GPUs, storage, and networking.

00:00:00 Intro & Guest Welcome: Asad Khan, Google Cloud Storage
00:01:19 GCS, Lustre, & the Full Google Cloud Storage Portfolio
00:02:00 Is Storage Dead? The GPU vs. Storage Conversation
00:03:12 The New AI Bottleneck: Why GPUs Sit Idle (Wasting Money)
00:06:39 From Cheap Scale to High-Performance Cloud Storage
00:08:22 The Two Dimensions of AI Storage: SSDs & APIs
00:10:37 Anywhere Cache: Automatic High-Performance Caching
00:13:15 How Storage Differs for AI Training vs. Inferencing
00:15:35 Rapid Store and Full POSIX Compliance with Lustre
00:18:26 The True Formula for AI Performance (It's Not Just the GPU)
00:20:39 Sony Honda Mobility Case Study: Lustre in Action
00:23:41 Traditional vs. AI Customers: Different Storage Priorities
00:27:07 The Future: Unlocking Insights from Unstructured Enterprise Data
00:33:40 Final Thoughts & Key Takeaways

Sign Up Now for my online course "The Cloud Strategy Master Class":
► On my web site: https://lnkd.in/gcxcrX and use promo code LINKEDIN20 to receive a 20% discount.
► On Udemy: https://www.udemy.com/course/cloud-strategy-master-class/

PODCASTS: Listen wherever you get your podcasts:
► Let's Talk Shop: http://letstalkshop.buzzsprout.com
► Reality Distortion Fields RDFs Podcast: https://youtu.be/88z1UiVaV00

Follow me:
► TikTok: @ekhnaser
► Instagram: @ekhnaser
► Twitter: @ekhnaser
► LinkedIn: https://www.linkedin.com/in/eliaskhnaser/
► Website: www.eliaskhnaser.com