Dr. Yanbing Li, Chief Product Officer at Datadog, outlines how the company has integrated AI and automation into its incident response framework, helping customers manage both traditional security challenges and emerging AI-specific risks.

Topics Include:

• Introduced talk about incident response and CISO liability
• Datadog founded 14 years ago for cloud-based development
• Platform unifies observability and security for cloud applications
• Current environment has too many fragmented security products
• SEC requires material incident reporting within four days
• Datadog's incident response automates Slack room creation
• Response team includes Legal, Security, Engineering, and Product
• System tracks non-material incidents to identify concerning patterns
• Real-time telemetry data drives incident management automation
• On-call capabilities manage escalation workflows
• Datadog uses own products internally for incident response
• Company focuses on reducing time to incident detection
• AI brings new risks: hallucination, data leaks, design exploitation
• Bits.ai launched as LLM-based incident management co-pilot
• Tool synthesizes events and generates incident summaries
• Bits.ai suggests code remediation and creates synthetic tests
• Security built into AI products from initial design
• Prompt injection prevented through structured validation approach
• Sensitive data anonymized before LLM processing
• Engineering and security teams collaborate closely on AI
• LLM observability becoming critical for production deployments
• Customers need monitoring for hallucinations and token usage
• Datadog extends infrastructure monitoring into security naturally
• Company maintains strong partnership with AWS
• Q&A covered Bits.ai proactive capabilities and enterprise differentiation

Participants:

Yanbing Li – Chief Produce Officer - Datadog

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Sanjay Kalra of Zscaler and Randy DeFauw of Amazon Web Services explore the hidden dangers of generative AI security—from invisible text manipulation and deep fakes to data poisoning and dark AI models—while offering practical strategies for protecting your enterprise in this era of generative AI.

Topics Include:

• AI security threats grouped into data, malicious use, trust/safety
• Data security critical for SaaS-based AI services
• Model training data vulnerable to poisoning and manipulation
• GenAI lacks traditional data deletion capabilities
• Access controls difficult once data becomes model embeddings
• Prompt injection attacks becoming widespread, with libraries available online
• Deepfake scams increasing in sophistication and frequency
• AI enhancing phishing attacks with better written content
• Dark AI models emerging specifically for malicious purposes
• Model hallucinations being exploited for security attacks
• AI accelerating analysis of stolen data
• Shadow AI usage by employees poses security risks
• Existing vendor AI integration creating unexpected security challenges
• Fine-grained access controls essential for AI applications
• PII protection critical in both inputs and outputs
• Comprehensive prompt and response logging necessary
• Invisible text manipulation emerging in resumes and RFPs
• Model fine-tuning can compromise built-in security guardrails
• Multi-language inputs create new security considerations
• Competition-sensitive content requires careful AI management
• AI firewalls needed for input/output monitoring
• Regular security testing required for AI models
• AI compliance standards emerging globally
• Multi-modal AI creating new security challenges
• Browser isolation helping control AI application usage

Participants:

• Sanjay Kalra – Product Management at Zscaler
• Randy DeFauw – Senior Principal Solutions Architect, Amazon Web Services

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This illuminating conversation with CyberArk's SVP of Finance, Nili Serr-Reuven, reveals how the 25-year-old cybersecurity leader successfully transformed from a traditional software company to a SaaS business model in just five quarters - far faster than the industry standard of 2-2.5 years - while maintaining strong margins and customer trust throughout the transition.

Topics Include:

• Introduction to SaaS transformation challenges and opportunities.
• Tomaz Perc introduces Nili Serr Reuven from CyberArk.
• Overview of CyberArk's 25-year history and milestones.
• Transition from a perpetual model to SaaS.
• CyberArk's accelerated transformation in just five quarters.
• Challenges of shifting from product-centric to customer-centric.
• Importance of market research and peer consultations.
• Key role of cross-functional collaboration in success.
• Explanation of "swallowing the fish" in SaaS.
• Managing short-term revenue drops during SaaS transformation.
• CyberArk's 70% SaaS revenue share post-transformation.
• Impact of global economic challenges on business strategy.
• CyberArk's robust demand for identity security solutions.
• Strategic leadership's role in transformation execution.
• CyberArk's disciplined financial planning during uncertainty.
• Establishing KPIs like ARR and customer satisfaction.
• Managing rising cloud costs with FinOps practices.
• CyberArk's approach to pricing and packaging SaaS solutions.
• Leveraging acquisitions to speed up SaaS capabilities.
• Impact of transformation on CyberArk's finance department.
• Evolution of finance roles to support SaaS growth.
• Communication with investors during transformative periods.
• The importance of cultural shifts in transformation success.
• Continuous learning, transparency, and collaboration as cornerstones.
• Advice for future SaaS leaders: plan, communicate, adapt.

Participants:

• Nili Serr Reuven – SVP Corporate Finance, CyberArk
• Tomaz Perc – SaaS Business Lead, Amazon Web Services

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Soumya Banerjee, Associate Partner at McKinsey and Company, shares a comprehensive data-driven exploration of how generative AI is transforming the cybersecurity landscape, revealing emerging threats, organizational challenges, and strategic opportunities for security professionals.

Topics Include:

• AI's transformative potential in cybersecurity
• Survey of 500 cybersecurity professionals
• Generative AI's impact on security landscape
• Rising sophistication of phishing attacks
• Threat actors leveraging generative AI
• Deepfake technologies circumventing biometric controls
• Cybersecurity companies' valuation and growth
• Platform versus point solution debates
• Expanding cybersecurity attack surfaces
• Cloud security emerging as top priority
• AI use cases in threat detection
• Generative AI risks for organizations
• Securing AI investments and budgets
• Data protection and sensitive information challenges
• Regulatory scrutiny of AI technologies
• Talent gaps in cybersecurity sector
• Evolving cyber insurance risk models
• Identity and access management trends
• API and machine identity security
• LLM prompt and data protection
• Enterprise strategies for AI adoption
• Emerging technologies for cybersecurity defense
• Partnerships between cybersecurity vendors
• Disclosure risks in generative AI
• Future of cybersecurity technology landscape

Participants:

·        Soumya Banerjee – Associate Partner at McKinsey and Company

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Brendan Ittelson, Chief Ecosystem Officer of Zoom and Fedrico Torreti of AWS share how Zoom and AWS are leveraging generative AI to revolutionize application development, enhance cross-app personalization, and streamline user experiences with intelligent communication tools.

Topics Include:

• Introduction of speakers and session overview.
• Generative AI's disruptive impact across industries.
• Reimagining customer experiences with generative AI.
• Driving productivity through AI-powered applications.
• Challenges faced by application developers with AI integration.
• Importance of AI as a collaborator, not replacement.
• Cross-functional workplace complexity with multiple apps.
• Reducing task redundancy via generative AI automation.
• Case study: AI accelerating creative project briefings.
• Business outcomes achieved through thoughtful AI implementation.
• McKinsey and Gartner projections on generative AI's potential.
• Top use cases: R&D, customer operations, sales, marketing.
• Bridging data silos for richer user experiences.
• Security and compliance challenges in AI implementations.
• Zoom's federated model for adaptable AI architecture.
• Meeting summaries powered by Zoom AI Companion.
• Expanding generative AI into chat, whiteboards, voicemails.
• Vision for AI amplifying, simplifying, and delegating tasks.
• Integrating external data for personalized user experiences.
• Open platform approach for seamless data exchange.
• AI Companion empowering users with actionable insights.
• Role of AWS in enabling AI-first solutions.
• Addressing notification overload with smarter AI design.
• Enhancing end-to-end workflows with unified AI tools.
• Encouragement for developers to embrace thoughtful AI adoption.

Participants:

• Brendan Ittelson - Chief Ecosystem Officer, Zoom
• Fedrico Torreti - Head of Product, AppFabric, AWS

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Jonathan Shulman, Senior Partner at McKinsey & Company, highlights the transformative potential of AI in the software industry and the evolutions needed to capture emerging market opportunities.

Topics Include:

• AI's transformative potential in the software industry.
• Why AI is a massive business opportunity.
• Software industry evolution: Mainframe to Cloud SaaS eras.
• Potential entrance into a new AI-driven era.
• AI spend forecast: $15B to $200B by 2026.
• Most AI spend repurposed from existing IT budgets.
• Legacy software spend likely shifting towards AI.
• Importance of targeting specific, high-impact AI use cases.
• Key areas disrupted: sales, marketing, software engineering.
• AI's adoption rates vary by industry and function.
• Four waves of AI: predictive to agent-based.
• Most companies are still in early AI stages.
• Prioritize building agentic, end-to-end AI solutions.
• Winning companies invest disproportionately in AI innovation.
• Position offerings to tap into AI-specific budgets.
• Deliver complete workflows, not isolated point solutions.
• Generative AI accelerates development and iteration cycles.
• Scaling AI pilots remains a major industry challenge.
• Tool fragmentation undermines productivity and innovation.
• Change management critical for successful AI integration.
• Rethinking team roles and processes for AI deployment.
• Consumption-based pricing models gaining industry traction.
• Shift from perpetual to subscription to consumption models.
• Balancing value-driven and cost-efficient consumption pricing.
• AI market poised to redefine IT and business landscapes.

Participants:

• Jonathan Shulman – Senior Partner, McKinsey and Company

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AWS's Miguel Álava and BoardWave's Phill Robinson explore how European software companies can overcome market fragmentation, leverage cloud and generative AI, and adopt global strategies to scale competitively.

Topics Include:

• Introduction of Miguel Álava and Phill Robinson
• Overview of BoardWave's mission and community
• Challenges for European software companies in scaling globally
• Comparison of US and European software market dynamics
• Cloud adoption benefits for European software scalability
• Modern licensing models to centralize operations in Europe
• Impact of fragmented European markets on growth
• COVID-19's effect on sales strategies and efficiency
• Selling enterprise software across Europe via cloud tools
• Role of centralized marketing in global competitiveness
• Advantages of targeting the US before EMEA expansion
• BoardWave's "Voyager" model for scaling internationally
• Importance of solving universal versus local market problems
• Using cloud infrastructure to penetrate diverse markets
• Generative AI's role in product innovation and scaling
• Generative AI's transformational impact on global software industry
• European software companies' opportunity to lead in AI
• Building a collaborative European ecosystem for innovation
• Lessons from Silicon Valley's collaborative success model
• BoardWave's mentoring programs for European software CEOs
• AWS's support for cloud adoption and business scaling
• The evolving role of Chief Product Officers (CPOs)
• AI's potential to enhance cross-market product functionality
• Strategic next steps for scaling European software businesses
• Vision for Europe as a software superpower by 2034

Participants:

• Phill Robinson – Founder, Boardwave
• Miguel Alava – EMEA ISV General Manager, Amazon Web Services

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Richard Borstein of RingCentral and Richard Sonnenblick of Planview discuss how AI-driven innovations enhance customer and employee experiences, and unlock organizational growth through cutting-edge tools and strategies.

Topics Include:

• Importance of integrated communication tools for businesses.
• Challenges caused by disconnected communication platforms.
• Role of data in enhancing business operations.
• How RingCentral addresses communication and data integration issues.
• Benefits of real-time conversational intelligence in organizations.
• Leveraging AI to transform communication into actionable insights.
• Unlocking customer and employee voices through AI.
• How AI identifies patterns in customer interactions.
• Overview of RingSense for Sales AI tool.
• Real-world success story with RingSense for Sales.
• Streamlining customer interactions using AI-powered analysis.
• Enhancing employee productivity with AI-driven tools.
• AI solutions for faster, accurate information searches.
• Overview of RingCentral's Ring CX contact center solution.
• Improving customer satisfaction through AI-powered call analysis.
• Case study: Success with Ring CX at Worldwide Express.
• Features and benefits of RingCentral Events platform.
• Integrating event tech with existing customer workflows.
• Personalizing events with branding and engagement tools.
• PlanView’s use of AWS to drive innovation.
• Solving governance challenges with PlanView’s solutions.
• How generative AI accelerates productivity and decision-making.
• Making every user a power user with AI.
• Practical examples of generative AI in project management.
• Unlocking growth with next-gen AI-driven business tools.

Participants:

• Richard Bornstein - Chief Business Development Officer, RingCentral
• Richard Sonnenblick Ph.D – Chief Data Scientist, Planview

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Benjamin Flast, Director, Product Management at MongoDB discusses vector search capabilities, integration with AWS Bedrock, and its transformative role in enabling scalable, efficient, and AI-powered solutions.

Topics Include:

• Introduction to MongoDB's vector search and AWS Bedrock
• Core concepts of vectors and embeddings explained
• High-dimensional space and vector similarity overview
• Embedding model use in vector creation
• Importance of distance functions in vector relations
• Vector search uses k-nearest neighbor algorithm
• Euclidean, Cosine, and Dot Product similarity functions
• Applications for different similarity functions discussed
• Large language models and vector search explained
• Introduction to retrieval-augmented generation (RAG)
• Combining external data with LLMs in RAG
• MongoDB's document model for flexible data storage
• MongoDB Atlas platform capabilities overview
• Unified interface for MongoDB document model
• Approximate nearest neighbor search for efficiency
• Vector indexing in MongoDB for fast querying
• Search nodes for scalable vector search processing
• MongoDB AI integrations with third-party libraries
• Semantic caching for efficient response retrieval
• MongoDB's private link support on AWS Bedrock
• Future potential of vector search and RAG applications
• Example use case: Metaphor Data's data catalog
• Example use case: Okta's conversational interface
• Example use case: Delivery Hero product recommendations
• Final takeaways on MongoDB Atlas vector search

Participants:

• Benjamin Flast - Director, Product Management, MongoDB

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David Gildea of Druva shares their approach to building cost-effective, fast generative AI applications, focusing on cybersecurity, data protection, and the innovative use of LLMs for simplified, natural language threat detection.

Topics Include:

• Introduction by Dave Gildea, VP of Product at Druva.
• Focus on building generative AI applications.
• Emphasis on cost and speed optimization.
• Mention of Amazon's Matt Wood keynote.
• AI experience with kids using "Party Rock."
• Prediction: GenAI as future workplace standard.
• Overview of Druva's data security platform.
• Three key Druva components: protection, response, and compliance.
• Druva's autonomous, rapid, and guaranteed recovery.
• Benefits of Druva’s 100% SaaS platform.
• Handling 7 billion backups annually.
• Managing 450 petabytes across 20 global regions.
• Druva’s high NPS score of 89.
• Introduction to Dru Investigate AI platform.
• Generative AI for cybersecurity and threat analysis.
• Support for backup and security admins.
• Simplified cybersecurity threat detection.
• AI-based natural language query interpretation.
• Historical analogy with Charles Babbage’s steam engine.
• "Fail upwards" model for LLM optimization.
• Using small models first, escalating to larger ones.
• API security and customer data protection.
• Amazon Bedrock and security guardrails.
• Testing LLMs with Amazon’s new prompt evaluation tool.
• Speculation on $100 billion future model costs.
• Session wrap up

Participants:

·        David Gildea - VP Product Generative AI, GM of CloudRanger, Druva

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