GreenSky's Ken Bowles on Auditing Controls before They Silently Fail
Over his 15-year journey through healthcare and financial services security, Ken Bowles, now Director of Security Operations at GreenSky, has collected a plethora of practical strategies for prioritizing crown jewels, managing cloud over-permissions, and building SOCs that scale effectively. He reflects on transforming security operations through AI and intelligent automation and discusses how AI is reducing analyst investigation time dramatically.
Ken also asserts the importance of auditing security controls before they silently fail. The conversation touches on the evolving role of the MITRE framework, the concept of signaling versus alerting, and why embracing AI might be the best career move for security professionals navigating rapid technological change in cloud environments.
Topics discussed:
Building security operations programs around crown jewels and scaling outward to manage the most critical assets first.
Managing over-permissions in cloud environments that have snowballed across multiple administrators without proper governance.
Using AI to reduce analyst investigation time from 30 minutes to seconds through intelligent data enrichment and context.
Creating true single-pane-of-glass visibility by connecting security tools and data sources for more effective threat detection.
Training new security analysts with AI assistance to bridge knowledge gaps in SQL, SOAR platforms, and log analysis.
Documenting institutional knowledge while encouraging analysts to trust their intuition when something doesn't look right.
Understanding the limitations of impossible travel alerts and using AI to establish user behavior baselines for accurate detection.
Applying the MITRE framework as a guideline rather than gospel, adapting detection strategies to specific organizational needs.
Implementing signaling approaches that label security-relevant events without creating alert fatigue for security operations teams.
Auditing security controls regularly to catch configuration drift and ensure protective measures remain effective over time.
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FanDuel's Tyler Martin on the Bronze-Silver-Gold Path to Autonomous Security Triage
Tyler Martin, Senior Director of Enterprise Security Engineering & Operations at FanDuel, reflects on revolutionizing security operations by replacing traditional analyst tiers with security engineers supported by custom AI agents. Tyler shares the architecture behind SAGE, FanDuel's phishing automation system, and explains how his team progressed from human-in-the-loop validation to fully autonomous triage through bronze-silver-gold maturity stages.
The conversation explores practical challenges like context enrichment, implementing user personas connected to IDP and HRIS systems, and choosing between RAG versus CAG models for knowledge augmentation. Tyler also discusses shifts in detection strategy, arguing for leaner detection catalogs with just-in-time, query-based rules over maintaining point-in-time codified detections that no longer address active risks.
Topics discussed:
Restructuring security operations teams to include only security engineers while AI agents handle traditional level 1-3 triage work.
Building Security Analysis and Guided Escalation, an AI-powered phishing automation system that reduced manual ticket volume.
Implementing bronze-silver-gold maturity stages for AI triage: manual validation, automated closures with oversight, and full autonomous operations.
Enriching AI agents with organizational context through connections to IDP systems, HRIS platforms, and user behavior analytics.
Creating user personas that encode access patterns, permissions, security groups, and typical behaviors to improve AI decision-making accuracy.
Designing incident response automation that spins up Slack channels, Zoom bridges, recordings, and comprehensive documentation through simple commands.
Eliminating 90% of missing PIR action items through automated documentation capture and stakeholder tagging in Confluence.
Shifting detection strategy from maintaining large MITRE-mapped catalogs to just-in-time query-based rules written by AI agents.
Balancing signal volume and enrichment data against inference costs while avoiding context rot that degrades LLM performance.
Evaluating RAG versus CAG models for knowledge augmentation and exploring multi-agent architectures with supervisory oversight layers.
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Live Oak Bank's George Werbacher on AI As SecOps' Single Pane of Glass
George Werbacher, Head of Security Operations at Live Oak Bank, reviews the practical realities of implementing AI agents in security operations, sharing his journey from exploring tools like Cursor and Claude Code to building custom agents in-house. He also reflects on the challenges of moving from local development to production-ready systems with proper durability and retry logic.
The conversation explores how AI is changing the security analyst role from alert analysis to deeper investigation work, why SOAR platforms face significant disruption, and how MCP servers enable natural language interactions across security tools. George offers pragmatic advice on cutting through AI hype, emphasizing that agents augment rather than replace human expertise while dramatically lowering barriers to automation and query language mastery.
Through technical insights and leadership perspective, George illuminates how security teams can embrace AI to improve operational efficiency and mean time to detect without inflating budgets, while maintaining the critical human judgment that effective security demands.
Topics discussed:
Understanding AI's role in augmenting security analysts rather than replacing them, shifting roles toward investigation and threat hunting.
Building custom AI agents using Python and exploring frameworks like LangChain to solve specific SecOps use cases.
Managing moving agents from local development to production, including retry logic, failbacks, and durability requirements.
Implementing MCP servers to enable natural language interactions with security tools, eliminating the need to learn multiple query languages.
Navigating AI hype by focusing on solving specific problems and understanding what agents can realistically accomplish.
Predicting SOAR platform disruption as agents take over enrichment, orchestration, and response with simpler automation approaches.
Removing platform barriers by enabling analysts to use natural language rather than mastering specific tools or query languages.
Exploring context management, prompt engineering, and conversation history techniques essential for building effective agentic systems.
Adopting tools like Cursor and Claude Code to empower technical security professionals without deep coding backgrounds.
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Ochsner Health's Andrew Casazza on When AI Becomes the Hammer Looking for Nails
Andrew Casazza, AVP of Cyber Security Operations at Ochsner Health, explores how healthcare organizations navigate FDA-approved medical devices running on legacy operating systems, implement AI-powered security tools while maintaining HIPAA compliance, and respond to threats that now move from initial compromise to malicious action in seconds rather than hours.
Andrew gives Jack his insights on building effective security programs in heavily regulated industries, emphasizing the importance of visibility, automation with guardrails, and keeping humans in the loop for critical decisions while leveraging AI to handle the speed and scale of modern threats.
Topics discussed:
Unique security challenges in healthcare environments where medical devices run on legacy operating systems that cannot be easily updated.
Strategies for monitoring and securing systems that cannot have traditional security agents installed due to FDA regulations and medical certification requirements.
Leveraging AI and automation in security operations while navigating HIPAA regulations and protecting patient data from external training models.
Implementing human-in-the-loop approaches where AI performs initial analysis and triage while escalating critical decisions to human analysts.
Understanding the privacy and compliance implications of AI tools that may use customer data for model training and improvement.
The dramatic reduction in threat-actor dwell time from hours or days to minutes or seconds.
Building effective SOAR automation playbooks to handle repetitive cases and reduce noise while focusing attention on bigger threats.
Establishing appropriate guardrails for AI-powered security tools to prevent unintended consequences while enabling automated response capabilities.
The importance of being curious and maintaining broad knowledge across multiple domains to become more effective.
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Cisco Meraki's Stephen Gubenia on How to Crawl-Walk-Run to AI-Powered SecOps
Stephen Gubenia, Head of Detection Engineering for Threat Response for Cisco Meraki, shares his evolution from managing overwhelming alert volumes as a one-person security team to architecting sophisticated automated systems that handle everything from enrichment to containment.
Stephen discusses the organizational changes needed for successful AI adoption, including top-down buy-in and proper training programs that help team members understand AI as a productivity multiplier rather than a job threat.
The conversation also explores Stephen’s practical "crawl, walk, run" methodology for responsibly implementing AI agents, the critical importance of maintaining human oversight through auditable workflows, and how security teams can transition from reactive alert management to strategic agent supervision.
Topics discussed:
Evolution from manual security operations to AI-powered agentic workflows that eliminate repetitive tasks and enable strategic focus.
Implementation of the "crawl, walk, run" methodology for gradually introducing AI agents with proper human oversight and validation.
Building enrichment agents that automatically gather threat intelligence and OSINT data instead of manual investigations.
Development of reasoning models that can dynamically triage alerts, run additional queries, and recommend investigation steps.
Automated containment workflows that can perform endpoint isolation and other response actions while maintaining appropriate guardrails.
Essential foundations including proper logging pipelines, alerting systems, and detection logic required before implementing AI automation.
Human-in-the-loop strategies that transition from per-alert review to periodic auditing and agent management oversight.
Organizational change management including top-down buy-in, training programs, and addressing fears about AI replacing jobs.
Future of detection engineering with AI-assisted rule development, gap analysis, and customized detection libraries.
Learning recommendations for cybersecurity professionals to develop AI literacy through reputable sources and consistent daily practice.
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The Detection at Scale Podcast is dedicated to helping security practitioners and their teams succeed at managing and responding to threats at a modern, cloud scale.
Every episode is focused on actionable takeaways to help you get ahead of the curve and prepare for the trends and technologies shaping the future.
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