The Reasoning Show
The Reasoning Show AI moves fast. Thinking clearly matters more.
The Reasoning Show cuts through the hype to explore how the smartest people in enterprise AI actually make decisions — the strategy, the tradeoffs, and the hard lessons no press release mentions.
Every week, hosts Aaron Delp and Brian Gracely sit down with the founders building the tools, investors funding the shift, and operators running AI in the real world. Not hype. Not panic. Just clear-headed conversations with people who have to make actual decisions.
Because the AI revolution isn't just happening. It's being reasoned through.
New shows every Wednesday and Sunday.
Topics: Enterprise AI strategy · LLMs in production · AI leadership · Agentic AI · Digital Sovereignty · Machine Learning · AI startups · Cloud Computing
The Reasoning Show
The Intersection of Cybersecurity and AI
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Monzy Merza (@monzymerza, CEO/Founder @Crogl) talks about build a next-generation Enterprise SOC by leveraging AI to stay ahead of Cybersecurity threats.
SHOW: 969
SHOW TRANSCRIPT: The Cloudcast #969 Transcript
SHOW VIDEO: https://youtube.com/@TheCloudcastNET
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SHOW NOTES:
Topic 1 - Welcome to the show, Monzy. Give everyone a brief introduction and tell us about your unique journey from government research to Splunk to Databricks to founding Crogl.
Topic 2 - Let's start with the current state of cybersecurity and AI. We're seeing headlines about AI being the top cybersecurity concern for 2025, even overtaking ransomware. From your perspective, what's driving this shift and why should organizations be paying attention to the intersection of cybersecurity and AI?
Topic 3 - You've described Crogl as an "Iron Man suit" for security analysts. That's a compelling metaphor. Can you break down what you mean by that and how your approach differs from the traditional "reduce alerts" mentality that most vendors have been pushing?
Topic 4 - Let's talk about your "knowledge engine" and what you call an “AI for the Enterprise SOC”. You're using compound AI systems with LLMs, smaller models, and knowledge graphs. This sounds quite different from vendors who are just "bolting on" LLMs to existing tools. Walk us through this architectural decision and why it matters.
Topic 5 - The cybersecurity industry is experiencing massive alert fatigue - 4,500 alerts per day, with analysts only able to investigate 8-25 of them. Your philosophy is "every alert should be analyzed" rather than filtering them out. That seems counterintuitive to what the market has been doing. How does your autonomous investigation approach actually work in practice?
Topic 6 - Where do you see t
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