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/