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Zscaler CAIO on securing AI agents and blending rule-based with generative models

August 18, 2025•ABcontributor•Original Link•3 minutes
ArtificialIntelligence
Cybersecurity
GenerativeAI

Claudionor Coelho Jr, Chief AI Officer at Zscaler, discusses AI's rapid evolution, cybersecurity challenges, and combining rule-based reasoning with generative models for enterprise transformation.

By Soumoshree Mukherjee
Editor’s note: This article is based on insights from a podcast. The views expressed reflect the speaker’s perspective.

Key Insights from Claudionor Coelho Jr.

Claudionor Coelho Jr., Chief AI Officer at Zscaler, shared critical perspectives on AI’s rapid evolution and cybersecurity challenges during a recent episode of the CAIO Podcast. With a PhD from Stanford and decades of experience in mathematics, machine learning, and enterprise-scale AI, Coelho emphasized the need for secure AI integration in business workflows.

AI at Scale: Zscaler’s Infrastructure

Zscaler processes over half a trillion transactions daily through its cloud-based cybersecurity platform. Coelho stressed that "to process that amount of data, we need from ground up to build an infrastructure that has AI in mind."

Bridging Rule-Based and Probabilistic AI

  • Large Language Models (LLMs) excel at probabilistic reasoning but struggle with rule-based tasks like bug detection. Coelho noted, "LLMs can fix bugs but they can’t find them."
  • His Unit 10x project combines formal methods (to locate bugs) with LLMs (to generate fixes), showcasing the power of hybrid approaches.

The Rise of Agentic Ecosystems

Coelho warned of risks in the emerging "Bring Your Own Agent" (BYOA) paradigm, where autonomous AI agents exchange data without traceability. His advice: "One of the safest bets is to put everything under your virtual private cloud, so that at least you control where the data is going."

Neuro-Symbolic AI for Enterprise Transformation

Coelho champions blending neural networks with rule-based systems to counter LLM ambiguity. He predicts enterprises will increasingly use AI to help humans write rules, accelerating decision-making in critical scenarios.

Choosing AI Use Cases Wisely

Coelho advocates for problem-driven design, leveraging LLMs to draw business scenarios while combining them with structured and unstructured internal data. "As you guide them, it helps you understand what really the business and the opportunity want to do," he said.

The Unprecedented Pace of AI Adoption

From ChatGPT to AI agents, adoption has surged in under a year. Coelho compared this wave to past tech revolutions: "AI’s adoption is faster, riskier, and more transformative than anything before." He highlighted shifts in UI/UX, governance, and workflows, stating, "[AI] will definitely change the way we do things."

Talent and Innovation

Coelho seeks professionals who "think outside the box" and understand both AI tools and business processes. His mantra: Pair innovation with security, or risk losing both.

READ: ‘Everybody is responsible’: Prudential Financial’s Gaia Bellone on AI integration in finance
READ: How CIOs are shaping the future of business: Insights from Ganesh Ramakrishnan

BYOA Security Paradigm

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About the Author

Dr. Sarah Chen

Dr. Sarah Chen

AI Research Expert

A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.

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Machine Learning
Natural Language Processing
Deep Learning
AI Ethics
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