Griffin Payne on relationships, AI-augmented pen testing, and trust in cyber hiring.

Thomas chats with Griffin Payne on the Cybersecurity Recruiter podcast about his career from help desk to senior security roles including IBM X-Force Red and Protiviti, and his current work as Principal Platform Engineer at Autonomous Cyber.

Griffin describes startup life while working from home with three kids and explains Autonomous Cyber’s approach to AI-enabled offensive security as an augmented, collaborative tool that boosts testers rather than a “set-and-forget” automated pen test.

They discuss how commoditized offensive AI tools create noise and risk, token/rate-limit and cost challenges, and how AI is impacting bug bounty quality, hiring (fake applicants, deepfakes), and workplace communication.

Griffin emphasizes relationships and communication as key to career opportunities, alongside rigorous interviewing and skills.

Book recommendations include Dan Brown’s “The Secret of Secrets”

00:30 Linkedin and social media habits

01:40 Griffin career highlights

03:02 Day in the life at home

05:11 Autonomous pentesting boom

08:53 How their tool works

11:28 Bug bounty AI slop

14:14 AI and hiring trust issues

17:32 Deepfakes and interview cheating

19:52 Honesty in interviews

20:44 Networking opens doors

23:47 Help desk to red team

26:08 Visualization and momentum

28:26 Trust beats cold applying

29:58 Building the platform

31:17 Token limits and costs

33:05 AI needs fundamentals

35:55 Speed of AI attacks

38:00 Books and final thoughts

Nexo - Executive, GTM & Cybersecurity Recruitment https://www.linkedin.com/in/thomaspropen/

Michael Greenlaw on AI, DevSecOps, and FedRAMP Automation: Speed, Risks, and the Need for Fundamentals

Tom and Michael discuss Microsoft’s strategy and licensing shifts pulling organizations toward Windows and Azure, and the frustration of incompatible cloud service naming across AWS/Azure/GCP. Michael describes using Claude to learn and build with LLMs rapidly, calling it “fast Google,” but warns about hallucinations, compounded errors in chained tasks, human limits in reviewing massive AI-generated code, poor handling of branching strategies, and the need for humans to own architecture and fundamentals.

They debate layoffs attributed to AI versus post-COVID overhiring and shareholder optics, and note AI’s growing impact on vulnerability discovery and exploitation.

Book recommendations: “How to Win Friends and Influence People” (Dale Carnegie), “The Trusted Advisor,” and “Thinking in Bets.”

00:00 Welcome and Intro

00:39 Career Path Update

01:25 Why Windows Again

05:41 Cloud Naming Frustrations

07:27 Keeping Up With Titles

09:12 AI Learning Acceleration

11:36 Curiosity in Hiring

15:39 Market Whiplash Era

19:11 FedRock and AI Experiments

22:19 Automating Workflows With RPA

24:31 AI Saving Lives Story

25:44 AI Pitfalls and Guardrails

31:09 Markets Overhyped AI

33:02 AI Errors And Whiplash

33:50 Why Juniors Still Matter

35:34 Overhiring Blamed On AI

38:11 Metrics Gaming And Talent

40:32 Shareholders And Productivity

42:28 AI Addiction And Frustration

47:08 Learning Boosts And Security Risks

51:58 Using AI With Responsibility

55:16 Scale Problems In Big Orgs

57:06 Books That Changed Everything

01:02:19 Closing Thanks And Wrap Up

Nexo - Executive, GTM & Cybersecurity Recruitment https://www.linkedin.com/in/thomaspropen/

00:00 Welcome and introductions

00:39 Lindsay career snapshot

01:41 Threat intel at Human

02:37 New book launch

03:33 Malware needs context

04:42 Spotting real people online

08:25 AI as attack amplifier

09:45 Phishing at scale

11:50 Democratized hacking risks

15:18 Path to VP leadership

20:00 AI proof risk communication

21:53 Time boxing MIT MBA grind

23:13 Writing a book discipline

23:49 Small wins and purpose

25:15 Book writing deepens mastery

26:39 Communication skills through practice

29:15 Behind the scenes struggles

32:02 Mentors versus sponsors

34:41 Security community collaboration

35:48 Whats next and book teaser

37:46 Boat go faster mantra

39:49 Final thanks and wrap up