
Episode 123: Deming, DevOps History, AI Risk, and Critical Thinking, with John Willis
Software Defined InterviewsShow Notes
W. Edwards Deming was a physicist, statistician, and quality theorist who taught post-war Japanese manufacturers what eventually became the Toyota Production System - and, decades later, DevOps. John Willis, one of the founders of the DevOps movement and the author of a book on Deming, walks Whitney and Coté through that lineage: Deming's system of profound knowledge (theory of knowledge, variation, psychology, and systems thinking), how it landed at Toyota, and how it threads through Lean software development into modern delivery practice. From there, the conversation turns to what the industry is getting wrong about AI: bragging about K-LOC and token counts instead of value, treating probabilistic systems with old deterministic notions of risk, and forgetting the social-technical lessons we already paid for. Along the way: VC moats and the buy-versus-build conversation inside large organizations, David Foster Wallace's "This is Water" and the ladder of inference, Jevons Paradox and whether AI gets us a three-day work week or a six-day one, and what CS students should be learning besides how to code. Also a brief detour into why John would want fifteen minutes with Bill Clinton.
You can watch the video version of this episode as well, if you prefer that kind of thing.
Mentions:
John on LinkedIn - the entry point to his author portal and writing.
John's book on Deming, Deming's Journey to Profound Knowledge.
John's book on AI, Rebels of Reason.
The DevOps Handbook, which John co-authored with Gene Kim, Jez Humble, and Patrick Debois.
Donella Meadows, Thinking in Systems.
Steven Spear, The High-Velocity Edge.
Mary and Tom Poppendieck, Lean Software Development.
David Foster Wallace, "This is Water" commencement speech.
The 1980 NBC documentary If Japan Can, Why Can't We?.
More from Software Defined Interviews
Rick Clark is Global Head of Cloud Advisory at UST, and co-founded OpenStack. His argument is that enterprise architecture is nearly extinct, killed off by fifteen years of shifting every decision left, and that this is how one insurance company he worked with ended up running over 50 secrets managers in production. Whitney and Coté push on whether platform engineering was meant to solve exactly that, and on what a modern enterprise architect would do instead - write the rules the platform enforces. The back half is agents: why nobody is ready to run them in production, and the difference between a rule an agent cannot break and one it must not break.
Viktor Farcic is a developer advocate at Upbound, runs the DevOps & AI Toolkit YouTube channel, and was last on the show back in episode 89. Whitney and Coté start with the animated bedtime stories he has started making - tech history told as fairy tales with a nightmare at the end - which he began after catching sight of himself in a mirror and deciding people should not have to watch that. From there it is what his working day looks like now, with 20 to 50 agents running at once, a coder and a tester and a reviewer who are not allowed to do each other's jobs and argue until they agree, and a private YouTube channel where the agents post recorded tests for him to review on his phone in the morning. The last stretch is money: why he thinks AI is cheap next to what a person costs, why he expects a bloodbath as industries fail to adapt, and a walk through Docker, Chef, Puppet, Ansible and HashiCorp on whether an open source company can ever turn a profit on its own.
Lin Sun is Head of Open Source at Solo.io, a recent KubeCon + CloudNativeCon program co-chair, and an emeritus member of the CNCF Technical Oversight Committee. Whitney and Coté start with the keynote she gave in Amsterdam, where she flew a drone over 13,000 people so an AI model on her laptop could score how engaged the audience was - it broke twice on stage, and Whitney, who was in the room, remembers nothing else from that day. Lin’s account of why it worked anyway is a checklist: a wow factor, something the audience does every day so they can relate to it, real engagement, and a planted surprise. From there they get into the part of co-chairing nobody sees, where three thousand submissions become about two hundred talks, how the AI-written ones get spotted, and why the CNCF cannot simply run a detector over the pile. The rest is open source as a job - twenty years of it, Istio at IBM through to Solo, and a straight answer to the question her own reports keep asking her, which is whether working on open source makes you less strategic to the company paying you.
Jason Yee is a Staff Technical Advocate at Datadog and one of three global co-chairs of DevOpsDays, and both jobs turn out to be mostly about getting other people to talk. Whitney and Coté ask him how the DevOpsDays machine actually works - local teams run the events, a global core team advises, and the co-chairs exist as a final escalation point - and what happens to conference sponsorship now that DevOps is mature rather than hot. His answer is that the sponsors who do well have stopped counting leads and started running workshops, on the grounds that a Lego giveaway gets you a list of people who wanted Lego.
Michael Rishi Forrester does AI workforce transformation at Accenture LearnVantage, after three years at KodeKloud and about thirty years in IT before that. Whitney and Coté talk with him about running tabletop role-playing games with AI. He built his 19-year-old son a homebrew campaign on top of Lancer, the sci-fi mech game, in about 20 hours instead of the 60 to 100 it would have taken him before - and got a website, a virtual tabletop and some Discord bots out of it. What breaks is the interesting part: there was a night when every shot did one damage, because the model had quietly stopped using the dice harness and started doing the math itself.