Sumedh Thakar, CEO of Qualys, discusses the company's evolution from vulnerability management to comprehensive risk operations. He explains why organizations need a Risk Operations Center (ROC) separate from their SOC, focusing on proactive risk management rather than reactive breach detection.

Thakar talks about how Qualys is standardizing risk scores across vulnerabilities, misconfigurations, and identities to give organizations a single view of their security posture. He also addresses the balance between prevention and detection, the role of AI in accelerating security operations, and why profitability matters as much as growth in cybersecurity.

Key Takeaways:
• ROC focuses on proactive risk management while SOC handles reactive breach detection
• Standardized risk scoring helps organizations prioritize what actually matters to their business
• AI and agentic automation can help defenders match attacker speed
• Consolidation is possible without abandoning best-of-breed tools
• Risk management ultimately comes down to money: potential loss vs. mitigation cost

Chapters:
0:05 - ROCon Conference Introduction
0:27 - What is ROC (Risk Operations Center)
1:52 - Why ROC is different from SOC
3:43 - Rethinking prevention and detection
4:59 - Standardizing risk scores
8:54 - True Risk Score and prioritization
14:15 - Qualys Business strategy
16:05 - AI and agentic automation in security

Interview recorded at Qualys ROCon 2024

This episode of the Techzine TV Podcast comes to you from Atlassian Team Europe, Atlassian's annual event in Barcelona. Sander and Atlassian CTO Rajeev Rajan discuss the company's pragmatic approach to AI. A key part of that is that Atlassian maintains strict data privacy principles. That is, it doesn't train its AI on customer data. Still, it aims to deliver powerful AI capabilities through Rovo.

Rajan explains how the Teamwork Graph technology connects work data across 80+ applications, enabling permission-aware search and intelligent agents. He addresses the reality that only 4% of companies see company-wide AI benefits today, emphasizing the need for both C-level commitment and grassroots experimentation. The conversation covers AI model selection, data sovereignty, automation strategies, and why Atlassian focuses on end-user scenarios rather than building LLMs.

Key takeaways:
• Atlassian doesn't train AI on customer data - they're custodians, not owners
• The Teamwork Graph connects data across 80+ apps with permission-aware access
• Rovo offers three capabilities: search, chat, and autonomous agents
• AI adoption requires both top-down goals and bottom-up experimentation
• Only 4% of companies currently see broad AI benefits
• Atlassian uses multiple models (OpenAI, Claude, open source) for different use cases
• Data residency available in 11 regions for sovereignty requirements

Chapters:
0:09 - Introduction to Atlassian's AI Strategy
1:06 - Rovo AI Platform Overview
2:16 - Data Privacy and Responsible AI
3:09 - The Teamwork Graph Technology
9:04 - AI Adoption Challenges in Enterprises
11:16 - Top-Down vs Bottom-Up AI Strategy
15:17 - The Future Impact of AI
17:00 - Background and Building World-Class Teams

In this conversation, Rob Rae from Pax8 and Sander from Techzine TV discuss the evolving landscape of managed service providers (MSPs) in relation to cybersecurity and artificial intelligence (AI).

The conversation highlights the critical role of cybersecurity in the MSP market and the increasing importance of AI as a tool for efficiency and productivity.

The discussion also touches on the challenges of data privacy in Europe and the transition from traditional MSPs to Managed Intelligence Providers (MIPs). Rae emphasizes the need for MSPs to adapt to these changes and leverage new technologies to stay competitive.

AI is changing the MSP game, are you ready for it? Watch this episode of Techzine TV.

Chapters:

00:00 Introduction to Pax8 and Market Trends
03:06 The Impact of Cybersecurity on MSPs
06:07 AI's Role in Managed Services
09:00 Pax8's Marketplace and AI Integration
11:47 Navigating Data Privacy in Europe
14:48 The Evolution from MSP to MIP

Peter Bailis, the new CTO of Workday, discusses the company's ambitious AI agent strategy and recent major acquisitions including Sana, Paradox, and Flowise. He explains Workday's vision to become the "agent system of record" - extending their people and money management platform to govern AI agents across enterprises.

Bailis reveals how Workday plans to compete with tech giants like Salesforce, ServiceNow, and SAP by leveraging their unique position as the system of record for 75 million users. The conversation covers their open data lake strategy, enterprise search ambitions, and how recent acquisitions will accelerate their AI platform vision.

Key insights include Workday's approach to AI agent governance, the technical challenges of enterprise search, and why the company believes they can win the "experience layer" battle in enterprise AI. Bailis also discusses the evolution of agent protocols and Workday's strategy to enable customers to build AI applications on their platform.

Key Takeaways:
- Workday introduces "agent system of record" concept for AI governance
- Three major acquisitions: Sana ($1B), Paradox, and Flowise explained
- Strategy to compete with Salesforce, ServiceNow, and SAP in AI platform space
- Open data lake with zero-copy architecture and Apache Iceberg format
- Vision for enterprise search as the future front door for knowledge workers
- Discussion of agent protocols (MCP, A2A, OAuth) and delegation permissions

Chapters:
0:00 Introduction and agent system of record concept
2:47 Managing AI agents across multiple platforms
4:32 Standards and protocols for agent management
6:45 Three major acquisitions strategy explained
10:23 Competition with enterprise giants discussion
14:38 David vs Goliath analysis and efficiency focus
17:32 Open data platform and integration strategy
21:47 Future of enterprise search and user interfaces

#Workday #AIAgents #EnterpriseAI #TechStrategy #SaaS #DigitalTransformation #AIGovernance #EnterpriseSearch #WorkdayRising #TechzineTV

A lot has changed since Broadcom acquired VMware. With the launch of VCF 9, it's safe to say that VMware's strategy entirely revolves around VMware Cloud Foundation. We sit down with Prashanth Shenoy, CMO and VP Marketing for VMware Cloud Foundation at Broadcom, to explore how VCF has become the cornerstone of VMware's product strategy under Broadcom ownership. Shenoy offers candid insights into the company's business model transformation and future direction, particularly regarding AI integration and its hybrid cloud strategy. We also ask the hard questions about the choices Broadcom made and the effect it has on mid-market and smaller customers.

We dive deep into how VMware's flagship platform (VCF) has evolved to meet the changing demands of modern enterprises.

Shenoy pulls back the curtain on Broadcom's strategic realignment of VMware's sprawling portfolio, which once included a staggering 9,000 SKUs, so complex that partners needed six months of training to create customer proposals. The simplification strategy centers on three key pillars: transitioning to a subscription model, consolidating the product portfolio around VCF as the central platform, and standardizing go-to-market approaches to ensure consistency across all customer touchpoints.

For organizations struggling to determine where to place their workloads, VCF now offers unprecedented flexibility with a "buy once, deploy anywhere" model that spans on-premises environments, colocation facilities, cloud service providers, and hyperscaler infrastructure. Shenoy states that 70% of enterprises are now considering or actively repatriating workloads from public cloud environments due to concerns over cost transparency, security considerations, and data sovereignty requirements. Particularly as AI initiatives move from pilot to production.

The integration of private AI capabilities directly into VCF represents a significant strategic advantage, allowing organizations to maintain control over their proprietary data while leveraging the full power of generative AI. This development, coupled with VCF's unified platform for both traditional VM and containerized Kubernetes workloads, positions it as the foundation for the next generation of enterprise applications.

Discover how VMware Cloud Foundation can help you build a modern private cloud with the security, control, and cost predictability your organization demands while enabling cutting-edge AI and Kubernetes workloads at scale. Listen to Techzine Talks!

Harry Reid International Airport is a special airport, with some very specific needs. The network infrastructure is very important. That makes it possible to offer travelers a good experience, from curb to gate. During HPE Discover, we sat down with Rishma M. Khimji, the airport's Chief Information and Technology Officer, to talk about how special it is exactly.

Harry Reid International Airport is the largest largest 100% common-use airport in the United States. That means that Khimji and her team have a lot of control over its infrastructure and what runs on it. That's a good thing, because that means they can go for a unified approach, from gate assignments to passenger flow, without being constrained by airline-specific systems that plague other major hubs.

At the core of the airport is an extensive HPE infrastructure featuring over 3,000 HPE Aruba access points delivering connectivity throughout the terminals. This network does more than just provide free Wi-Fi; it also generates valuable analytics about passenger movement patterns. That's very valuable data for things like retail placement, bottleneck reduction, and service enhancements. The airport's segmented network architecture ensures casino gaming operations remain completely separate from other systems.

As Khimji explains, "The airport is the first and last look of the city." It should reflect that in terms of what travelers can do and experience. Listen to this new episode how Harry Reid International Airport does this and how it intends to do that in the future.

Browsers have become an endpoint, and have also become an attack vector and target for attackers. The problem is that your EDR isn't keeping up. In this conversation with Vivek Ramachandran, founder and CEO of SquareX, we dive deep into the emerging world of Browser Detection and Response (BDR) and why it matters for modern security teams.

Drawing from his 24 years in cybersecurity, Ramachandran explains why traditional security approaches are failing to protect the browser. The browser has effectively become an application platform rather than just a simple web viewer, so it is important to protect it. "EDRs currently have zero visibility into the browser," Ramachandran notes. "They primarily look at file and process, but by looking at a browser's memory, it's almost impossible to reconstruct what is happening at the application layer."

This blind spot creates vulnerabilities as organizations move to cloud-native operations, Ramachandran says. While SASE and SSE solutions claim to secure browser traffic, they introduce latency and are easily circumvented by modern attack techniques like "last mile reassembly," where attackers create malicious files entirely client-side, invisible to cloud inspection.

According to Ramachandran, Squarex takes a different approach from "enterprise browsers" that create user friction. Instead, BDR works with existing browsers through extensions, using WebAssembly to run detection algorithms at near-native speeds within the browser context. This provides complete visibility into attack chains and protects corporate identities, one of the primary targets nowadays.

Whether browser security emerges as a standalone category or becomes integrated into existing security tools, remains to be seen. Ramachandran is adamant that browsers represent an under-protected attack surface that needs immediate attention. Listen now to learn more about how "shifting up, not left" is necessary according to him and SquareX.

Work feels broken. We're drowning in too many systems, endless context switching, and information scattered across countless platforms. But what if the solution isn't adding another tool, but transforming one you already use into the glue that binds everything together?

In this conversation with Peter Dooling, Chief Customer Officer at Slack, we explore how Slack is evolving from a messaging platform into what they call a "work operating system." Dooling reveals how customer feedback has shaped Slack's transformation, particularly the groundbreaking "Salesforce Channels" that connect Salesforce's structured data records with the rich contextual conversations happening in Slack.

For organizations concerned that Slack may become too Salesforce-centric, Dooling stresses its commitments to open integration. Their approach to enterprise search stands apart from competitors, he further states. Rather than pulling you away from your workflow, Slack aims to federate searches across your systems while maintaining strict security protocols, bringing information to you instead of making you hunt for it.

And then there's Slack's understanding of communication patterns. Their Huddles feature serves a fundamentally different purpose than traditional video conferencing, Dooling states. It is designed for those quick, contextual conversations that drive business forward.

Looking ahead, Slack's three-pronged AI strategy wants to transform work: Slack AI enhances the core platform's intelligence, Salesforce Agent integration brings specialized AI assistants into channels, and an open ecosystem supports third-party AI applications. Throughout it all, Slack's core philosophy remains focused on capturing and maintaining attention. That's the scarcest resource in our distracted work lives.