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Recent episodes
Why Most Enterprises Are Still Stuck at Agent Sprawl - And What Actually Fixes It
Jun 25, 2026
Unknown duration
Boomi x AWS: What the Partnership Actually Means for Enterprise Customers Scaling AI
Jun 24, 2026
Unknown duration
From Data Pipelines to Orchestrating AI Agents: WWT's Architecture Story with Boomi
Jun 24, 2026
Unknown duration
Governing AI Agents in a Regulated Industry — Lexitas's Approach with Boomi
Jun 23, 2026
Unknown duration
The Next Big Shifts in Enterprise AI: AgentExchange, Headless Systems, and Agent-First Workflows
Jun 22, 2026
Unknown duration
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 6/25/26 | ![]() Why Most Enterprises Are Still Stuck at Agent Sprawl - And What Actually Fixes It | I learn the most from people who can explain hard things simply, and my conversation on The Ravit Show with Patricia Moore, AI Field CTO at Boomi, was one of those at Boomi World 2026.Patricia was direct about why so many AI agent pilots stall. Most teams rush to deployment before doing the work on context, data readiness, and governance. That is the gap between the enterprises getting real value and the ones still running experiments.We spent real time on context engineering. Everyone uses the phrase, but very few can explain it. Patricia made it obvious why context is not just another feature. It is what decides whether an agent can be trusted inside a real business. The same thinking applies to hallucinations. The fix is not bigger models. It is better grounding, cleaner data, and tighter checks around the agent.The part I enjoyed most was her view on the shift happening inside enterprises moving from experiments to real outcomes. The leaders getting it right are not chasing AI for the sake of AI. They are tying every initiative to outcomes that actually matter.My takeaway. The companies winning with agents are treating context, governance, and outcomes as the real product. The model is just one part of the story.#data #ai #BoomiWorld #theravitshow #BoomiAmbassador | — | ||||||
| 6/24/26 | ![]() Boomi x AWS: What the Partnership Actually Means for Enterprise Customers Scaling AI | At Boomi World 2026, I spoke with the amazing Nicole Bradley from Amazon Web Services (AWS) for a conversation on The Ravit Show, and it kept coming back to one idea. Most enterprises are not failing at agentic AI because of the models. They are failing because they are trying to stand up data management and agents without the right partnership underneath!!!!Nicole walked me through the patterns AWS is seeing across customers right now, why Boomi became the partner that made sense, and the use cases where this combination is genuinely hard to beat. We also talked about the roadmap for the next 12 months, and there is a lot coming that customers should be paying attention to.The line that stuck with me. Customers do not need more tools. They need fewer broken seams between them.#data #ai #BoomiWorld #theravitshow #BoomiAmbassador | — | ||||||
| 6/24/26 | ![]() From Data Pipelines to Orchestrating AI Agents: WWT's Architecture Story with Boomi | One of the sharpest architecture conversations I had at Boomi World 2026 on The Ravit Show was with Kenneth Maglio, Principal Architect at World Wide Technology. His view on agentic AI was refreshingly honest. Can't wait to do this again!!!!A lot of teams are still debating whether to prioritize data management or agentic AI. Ken's answer was simple. That debate is the problem. If you separate them, you end up with agents that look impressive in a demo and fall apart in production.We talked about what his team was spending too much time on before Boomi, and how much of that work was not moving the business anywhere. The bigger shift was around data freshness. Ken made the case that this is the single biggest factor in whether an agent can actually be trusted. Stale data is not a small issue. It is the difference between a system that scales and one that quietly erodes confidence across the business.We also got into the measurable outcomes WWT has seen since adopting the Boomi architecture, and what would break if that layer was removed. His answer made it clear how foundational this has become.The takeaway for me. Agentic AI in the enterprise will not be won by whoever has the best model. It will be won by whoever has the cleanest, freshest, most governed data feeding those agents in real time.#data #ai #BoomiWorld #theravitshow #BoomiAmbassador | — | ||||||
| 6/23/26 | ![]() Governing AI Agents in a Regulated Industry — Lexitas's Approach with Boomi | Quick conversation on The Ravit Show from Boomi World 2026 with John Baker, CIO and CISO at Lexitas. One of the most grounded customer perspectives I have heard this year. Thanks for the amazing insights, John :)John was clear about why Lexitas refused to treat data management and agentic AI as separate projects, what his team stopped wasting time on after Boomi, and why agent governance is the part most enterprises underestimate. Agents are only predictable when the layer beneath them is.My takeaway. The architecture decision is the AI decision.#data #ai #BoomiWorld #theravitshow #BoomiAmbassador | — | ||||||
| 6/22/26 | ![]() The Next Big Shifts in Enterprise AI: AgentExchange, Headless Systems, and Agent-First Workflows | Enterprise software is changing. I sat down with Brian Landsman, CEO of AgentExchange at Salesforce, to talk about what an agent-first future actually looks like. #salesforcepartnerThis wasn’t a surface-level conversation. We went deep into what’s coming next.Here’s what stood out:* AgentExchange evolved from a marketplace directory into a commerce and discovery layer, is rethinking how enterprises deploy software* Headless architectures could fundamentally reshape how people interact with enterprise systems since traditional UIs matter less* Agents are moving from assistants to becoming the primary interface* Workflows need to be redesigned from the ground up for an agent-first world* Success will be defined by agents executing end-to-end tasks, not just supporting humans* The gap between AI pilots and production is finally starting to closeWe also discussed how individuals can go to market faster with $50M AgentExchange Builders Initiative.Watch the full conversation and let me know what you think.#data #ai #tdx26 #salesforce #workflows #api #headless360 #agentexchange #apps #theravitshow | — | ||||||
| 6/19/26 | ![]() Atlassian’s AI Vision: How Teams Will Work in the Next 5 Years | Some conversations stay with you for days. This one did. Last week at Team '26 in Anaheim, I spoke to my favourite Tamar Yehoshua, Chief Product and AI Officer at Atlassian. A week later, I'm still thinking about three things she said.Here's the thing about Tamar. I always learn something new every time we talk. She's one of those rare leaders who can zoom from a product detail to a 5-year vision in the same breath without missing a beat.What makes her perspective so useful: Tamar has shipped product at Google Search, led product at Slack through their tenfold growth and IPO, and ran product and technology at Glean. Three different eras of how knowledge workers find what they need at work. And now she's leading Atlassian's AI strategy at the moment the entire category is being redefined.Team '26 was her first Team event as CPO and AI Officer. You could feel the weight of that moment in the room.Here's what we got into:- Day one through her eyes. What it actually felt like to walk on stage as the new CPO and announce the biggest set of AI launches in Atlassian's history.- The connective thread. Atlassian covered massive ground in the keynote. AI for developers, service teams, product teams, agents in Jira. I asked Tamar how she wants people to think about Atlassian's AI strategy as one story instead of five. Her answer reframed the whole keynote for me.- How customers are actually using Rovo. Not the marketing version. The real version. What's working, what's surprising, where the patterns are forming.- The shifts that matter. Tamar has lived through search becoming the default interface, then SaaS becoming the default workplace, then chat-based collaboration becoming the default for distributed teams. I asked what excites her most about this moment. Her answer wasn't what I expected.- The next 5 years. How teams will actually work differently. Not predictions. Patterns she's already seeing inside Atlassian's own teams.The throughline across everything she shared: context is the moat. Models will keep getting better and cheaper. What separates the winners is what your AI knows about how your company actually works.Big thank you to Tamar for the time and the candor, and for being so generous with her thinking every time we connect. And to the Atlassian team for hosting me at Team '26.#data #ai #atlassian #team26 #theravitshow | — | ||||||
| 6/17/26 | ![]() AI that is already delivering results | 300 to 600 hours reclaimed every single week. Ticket creation cut by 75%.These are not projections. This is what DocuSign is actually seeing from Atlassian's Rovo rollout right now.New episode of The Ravit Show is live with Shivi Singh Verma, MBA, PMP®, CSM®, PMI-ACP®, ITIL®, Senior Manager of Engineering at Docusign, recorded at Team '26 in Anaheim.If you have been waiting for an enterprise AI deployment story that goes past pilots and demos, this is the one to watch.Shivi leads GenAI and AI Agentic strategy at DocuSign. They have actually done the hard work most companies are still talking about. Phased rollout, real guardrails, measured ROI, and a clear plan for what comes next. Their philosophy on this is sharp: adopting AI at scale requires foundational trust, robust governance, and clear guardrails. Not optional, not later, on day one.What we got into:- The tipping point. What finally convinced DocuSign to move forward with Rovo. There is a specific moment Shivi described that I think every engineering leader weighing this decision needs to hear.- The phased rollout. What the pilot looked like, what surprised Shivi as they expanded beyond it, and the guardrails they put in place that they would recommend to other enterprises starting today. This is the playbook section.- How they actually measured ROI. Most companies struggle to prove AI value to leadership. DocuSign did not. I asked Shivi how they measured the 300 to 600 hours weekly and the 75% ticket reduction, and what convinced their leadership these gains were real and sustainable. The answer is more disciplined than I expected.- What comes next. DocuSign is planning to let non-technical teams build their own governed agents through Rovo Studio, and shift from reactive AI to proactive AI. We spent time on what that future looks like, and what they are doing now to prepare for it.- The line from Shivi that stayed with me: AI at enterprise scale is not a model problem. It is a trust problem. Get the governance right first and the productivity gains follow. Skip that step and the project will not survive its first incident.If you are an engineering leader, a CIO, or anyone trying to build the business case for enterprise AI inside your own company, watch this one. Shivi gives you the playbook.Big thank you to Shivi for the openness about what worked and what was harder than expected. And to the Atlassian team for the front-row access at Team '26.#data #ai #atlassian #team26 #theravitshow | — | ||||||
| 6/17/26 | ![]() Atlassian’s AI Strategy: From Teamwork Graph to Agent Orchestration | I had a blast chatting with Sherif Mansour, Head of AI at Atlassian, at Team '26 in Anaheim. If you want to understand what Atlassian actually shipped this year and why it matters, this is the conversation to watch.Sherif is the person inside Atlassian who has been thinking about AI longest and hardest. He runs Atlassian Intelligence, the generative AI platform that powers Rovo, the Teamwork Graph, and the agent experiences across Jira, Confluence, and Loom. When the entire company stage talks about AI for two hours, Sherif is one of the people who actually built what they are talking about.That made this conversation different from most AI interviews you will hear this year.What we covered:The keynote in his own words. Atlassian announced AI for developers, service teams, product teams, agents in Jira, and a brand new Product Collection. I asked Sherif what excites him most across all of it. His answer surprised me.Teamwork Graph, opened up. The 150 billion connection graph is now accessible to any agent through MCP, CLI, and Forge connectors. I asked Sherif what "opening it up" actually means in practice, and what changes for builders outside Atlassian who want to plug in.Agent orchestration in Jira. What it looks like when an agent is not just answering questions but coordinating work across an entire project. Sherif walked through how Atlassian thinks about keeping humans in the loop where it matters, and where to get out of the way.AI mythbusting. Sherif came in with strong opinions on the myths he is tired of hearing. We spent real time here. If you work in or around enterprise AI, this section alone is worth the watch.The line that stayed with me: the hardest problem in enterprise AI is not making models smarter. It is making them aware of how your company actually works. Everything Atlassian shipped at Team '26 traces back to that one bet.Big thank you to Sherif for the depth, the candor, and the patience with my follow-up questions. And to the Atlassian team for the front-row access at Team '26.#data #ai #atlassian #team26 #theravitshow | — | ||||||
| 6/15/26 | ![]() CosmosDB Conf 2026 Key Takeaways: OpenAI Scale, Agent Memory & AI-Native Databases | What happens when the database becomes an active participant in AI applications instead of just a place to store data? In this session of The Ravit Show, I sat down with Jay Gordon and Patty Chow to unpack the biggest announcements and takeaways from CosmosDB Conf!!!!One theme stood out throughout the conference:AI is not just changing applications. It's changing the database itself.We discussed:- How OpenAI scales from zero to millions of queries per second- Why Walmart relies on globally distributed architectures to keep checkout systems running during failures- How vector search, full-text search, and hybrid search are becoming native database capabilities- The rise of agent memory architectures and AI-native applications- Why developers need real-time visibility into query costs- How to think about CosmosDB vs Azure DocumentDB based on workload requirements- What the Azure CosmosDB Agent Kit means for developers building AI-powered systemsOne of my biggest takeaways was that retrieval is increasingly moving into the database layer itself. Instead of stitching together multiple services, developers can now work with a more unified approach to search, AI, and data.If you're building AI applications, working with data infrastructure, or trying to understand where databases are headed next, this conversation is worth watching.The full interview is now live.What was your biggest takeaway from CosmosDB Conf this year?#data #ai #azure #cosmosDB #microsoft #api #microservices #theravitshow | — | ||||||
| 6/11/26 | ![]() Rubrik Forward 2026 Key Announcements✨ | enterprise securityAI technology+3 | Anneka Gupta | Rubrik AIRubrik Agent Cloud+5 | Las Vegas | RubrikAI+5 | — | 24m 59s | |
| 6/10/26 | ![]() How AI Is Reshaping Teamwork: Insights from Atlassian’s Teamwork Lab✨ | AI strategyteam collaboration+3 | Molly Sands | AtlassianTeamwork Lab | — | AIteamwork+5 | — | 12m 51s | |
| 6/9/26 | ![]() POSETTE 2026 by Microsoft✨ | PostgresAI applications+3 | Charles Feddersen | MicrosoftAMD+1 | — | PostgresAI+6 | — | 12m 43s | |
| 6/8/26 | ![]() Why Data Context Matters: Inside Atlassian’s Teamwork Graph and AI Agents✨ | AIdata context+4 | Jamil Valliani | AtlassianThe Ravit Show | — | data contextAI tools+6 | — | 10m 03s | |
| 6/7/26 | ![]() AI Is Powerful… But Can You Trust It?✨ | AI trustenterprise AI+4 | Reggie Townsend | SASSAS Innovate+1 | — | AItrust+5 | — | 10m 50s | |
| 6/6/26 | ![]() Inside SAS Innovate: The Shift to Production-Ready AI✨ | enterprise AIproduction-ready AI+4 | Marinela Profi | SASSAS Viya+1 | — | AIenterprise AI+5 | — | 14m 39s | |
| 6/4/26 | ![]() Data: The Foundation Behind AI Success✨ | AIdata governance+3 | Dan Soceanu | SAS | — | AIdata+4 | — | 8m 28s | |
| 6/4/26 | ![]() Quantum AI Explained: Making Quantum More Accessible✨ | Quantum AIenterprise AI+4 | Amy Stout | SASSAS Innovate+1 | — | Quantum AIenterprise AI+5 | — | 9m 13s | |
| 6/2/26 | ![]() SAS Brings AI to Financial Services, Healthcare, Government and Beyond✨ | AI deploymententerprise AI+4 | Alyssa Farrell | SASSAS Innovate+3 | — | AISAS+6 | — | 10m 27s | |
| 6/2/26 | ![]() Equinix’s Internal Use of AI-Tools✨ | AI implementationemployee workflows+3 | Harmeen Mehta | EquinixGoogle Cloud | — | AIEquinix+5 | — | 14m 48s | |
| 5/31/26 | ![]() How Commvault, Google Cloud, and Clumio are redefining data resilience for the cloud era✨ | data resiliencecloud computing+4 | Woon Ho Jung | CommvaultGoogle Cloud+3 | — | data protectioncloud-native data+6 | — | 7m 36s | |
| 5/30/26 | ![]() Commvault’s AI vision: Data Activate, AI Protect, and what it means for enterprises✨ | AI deploymentdata management+3 | Michael Fasulo | CommvaultGoogle Cloud | — | AIdata+5 | — | 8m 38s | |
| 5/28/26 | ![]() Agentic Governance + Security✨ | AI governancesecurity+3 | A. Ravi M. | BoxGoogle Cloud+4 | — | AIgovernance+5 | — | 12m 47s | |
| 5/28/26 | ![]() Context for Agentic Success✨ | AI agentsdata context+4 | Ben Kus | BoxGoogle Cloud+3 | — | AIagents+8 | — | 8m 38s | |
| 5/26/26 | ![]() How Kore.ai Built the First AI-Programmable Platform for Enterprise AI✨ | enterprise AIAI platforms+4 | Prasanna Arikala | Kore.aiAmazon Web Services+1 | San Francisco | Kore.aiArtemis+5 | — | 26m 24s | |
| 5/25/26 | ![]() 48% to 90% GPU utilization: What DDN and Google Cloud unlocked for AI✨ | AI infrastructureGPU utilization+5 | Santosh Erram | DDNGoogle Cloud+5 | — | AIGPU+7 | — | 9m 26s | |
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