The CTO Playbook

AI adoption is getting easier for everyone. The harder question is whether you're using it to optimise the game you're already in, or to build a position that changes the game.

Ritavan, author of The System Gambit and Data Impact, returns to The CTO Playbook after his first appearance on episode 30.

A System Gambit is a deliberate sacrifice that builds a structural advantage that compounds. Rather than optimising within the system you're already in, it changes the system so competitors can't simply buy or copy their way to your position.

Ritavan explains the difference between a System Gambit and a System Anti-Gambit, using Nokia and Amazon as examples. He also explains why adding AI to the data your business already generates tends to keep you inside your existing paradigm.

Adam then puts his own move from fractional CTO work to coaching through Ritavan's three tests: self-improving loops, path dependence, and management logic antagonism.

In this episode, he explains:
■ 𝗪𝗵𝗮𝘁 𝗮 𝗦𝘆𝘀𝘁𝗲𝗺 𝗚𝗮𝗺𝗯𝗶𝘁 𝗜𝘀: Why a deliberate sacrifice now can unlock a structural advantage that compounds.
■ 𝗧𝗵𝗲 𝗦𝘆𝘀𝘁𝗲𝗺 𝗔𝗻𝘁𝗶-𝗚𝗮𝗺𝗯𝗶𝘁: Why optimising inside your current system is rational, and why it leaves you exposed when a rival changes the game.
■ 𝗔𝗴𝗶𝗹𝗶𝘁𝘆 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗮 𝗧𝗵𝗲𝘀𝗶𝘀: What Nokia shows about reaching peak agility and still losing badly in a market.
■ 𝗔𝗜 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗘𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗣𝗮𝗿𝗮𝗱𝗶𝗴𝗺: Why adding AI to your own business data may bring incremental gains without moving you into a new system.
■ 𝗧𝗵𝗲 𝗧𝗵𝗿𝗲𝗲 𝗧𝗲𝘀𝘁𝘀: Self-improving loops, path dependence and management logic antagonism, applied to Adam's own CTO coaching journey.
■ 𝗪𝗵𝗲𝗻 𝗡𝗼𝘁 𝘁𝗼 𝗠𝗮𝗸𝗲 𝗮 𝗚𝗮𝗺𝗯𝗶𝘁: Why a short runway, or a lack of real control over the system, makes it the wrong move.

Build your own CTO Playbook at www.theCTOplaybook.com, the leadership platform built for the full CTO journey. Coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.

You'll Learn:
[0:00] Introduction
[3:07] Why Strategic Advantage Requires a Sacrifice
[5:34] Why a System Gambit Isn't a Gamble
[8:37] The System Gambit vs the System Anti-Gambit
[9:38] What Nokia Shows About Incremental Optimisation
[13:41] What Actually Qualifies as a Paradigm Shift
[23:12] Why AI Alone May Reinforce the Existing Paradigm
[26:25] How Amazon Built Structural Advantage
[29:37] Testing Adam's Own System Gambit
[33:05] Applying the Tests Live
[38:18] How Cross-Coupled Loops Create Compounding Advantage
[40:29] Why Path Dependence Makes a Strategy Hard to Copy
[46:42] When the System Anti-Gambit Is the Right Move
[50:45] When You Actually Need a System Gambit
[53:03] The Three Tests: Self-Improving Loops, Path Dependence and Management Logic Antagonism
[55:39] Where to Find Ritavan

Follow Ritavan:
■ Book: https://www.amazon.com/dp/B0GY8J23SK
■ Substack: https://systemgambit.substack.com
■ Website: https://ritavan.com
■ LinkedIn: https://www.linkedin.com/in/rritavan/?isSelfProfile=false
■ YouTube: http://www.youtube.com/@UCKf6F9wfQH56mCphHdbnCYg

The CTO Playbook:
■ Build your own CTO Playbook at https://www.thectoplaybook.com, the leadership platform built for the full CTO journey, coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.
■ Follow Adam: https://www.linkedin.com/in/adamhorner/
■ YouTube: https://www.youtube.com/@TheCTOplaybook
■ Prefer listening? Catch the podcast: https://bit.ly/thectoplaybook

AI isn't just changing how engineers work. It's forcing technology leaders to rethink what makes management valuable.

Prof. Charles Wood is Senior Manager, Data Science & AI at Comcast, where he has spent nearly a decade leading enterprise AI strategy, and the author of Artificial Intelligence Management. Most of the AI and jobs conversation focuses on developers.

Charles looks at the layer above them. His argument is that the qualities that make a manager good, like consistency, fairness and a repeatable process, are exactly what a language model can reproduce. He explains why the more predictable management work becomes, the easier it is to automate. He also covers why implementing AI means nothing until you prove the impact, and why the managers who stay valuable will be the ones creating outcomes that can't be reduced to an average.

In this episode, he explains:
■ Why Middle Management Is Exposed: Why predictable, repeatable, standardized management work is easier to automate than engineering itself.
■ AI Is Arriving Top-Down: Why adoption is coming from the executive level, and why it has to start with business value.
■ Precision, Personalization and Scale: What AI makes possible, and where hallucinations, testing and human oversight still matter.
■ Stop Asking "Did We Implement AI?": Why every AI initiative needs measurable outcomes, and why the real question is "So what?"
■ Are You Average?: How managers can use AI to expand their scope, take on more complexity, and deliver results no model can replicate.
■ The New AI Playbook: Charles' principles for rebuilding your leadership playbook, starting with continuous learning and the willingness to nuke your old one.

Build your own CTO Playbook at www.theCTOplaybook.com, the leadership platform built for the full CTO journey. Coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.

You'll Learn:
[0:00] Introduction
[5:10] Why AI Could Disrupt Middle Management More Than Engineering
[9:42] Why Predictable Management Work Is Easier to Automate
[14:18] What LLMs Can and Cannot Replace in Technical Teams
[19:06] Why AI Adoption Has to Start With Business Value
[24:15] Hyper Precision, Personalization and Scale
[29:37] Hallucinations, Testing and Human Oversight
[34:21] Why Every AI Initiative Needs Measurable Outcomes
[39:04] Using AI to Expand Your Scope and Stay Relevant
[44:12] Continuous Learning as a Leadership Requirement
[49:06] The Five Principles of the New AI Playbook
[54:18] From "Did We Implement AI?" to "So What?"

Follow Prof. Charles Wood:
■ Book: Artificial Intelligence Management
■ Convergent Lens: https://convergentlens.com
■ LinkedIn: https://www.linkedin.com/in/profwood/

The CTO Playbook:
■ Build your own CTO Playbook at https://www.thectoplaybook.com, the leadership platform built for the full CTO journey, coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.
■ Follow Adam: https://www.linkedin.com/in/adamhorner/
■ YouTube: https://www.youtube.com/@TheCTOplaybook
■ Prefer listening? Catch the podcast: https://bit.ly/thectoplaybook

Quantum computing may not be breaking your security today, but the decisions you make now could determine how exposed your organization is when it does. Conor Deegan explains why CTOs need to start preparing before Q Day arrives.

Build your own CTO Playbook at www.theCTOplaybook.com, the leadership platform built for the full CTO journey. Coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.

My guest this week is Conor Deegan, a security engineer, cryptographer, and co-founder of Project 11, focused on helping organizations prepare for the transition from classical cryptography to post-quantum cryptography.

The quantum threat goes far beyond Bitcoin and digital assets. Conor explains how quantum computing could eventually affect the cryptography behind banking, communications, cloud infrastructure, authentication, health records, and everyday internet security.

He breaks down what "Q Day" means, why organizations cannot simply wait until a powerful quantum computer exists, and how "harvest now, decrypt later" could put sensitive information collected today at risk in the future.

The transition also comes with real engineering challenges. Post-quantum cryptography can require more computing resources, memory, storage, and bandwidth, while legacy systems and constrained devices such as IoT hardware can make migration even more difficult.

Conor then shares a practical framework for CTOs: understand the threat, put someone in charge, identify critical systems and data, take the easy wins, put pressure on vendors, and stop creating migration debt.

You'll Learn:
[0:25] The Quantum Threat and Why It Matters
[3:54] Understanding Q Day
[7:52] How Quantum Computing Impacts Security
[11:22] The Mission Behind Project 11
[18:58] Harvest Now, Decrypt Later
[21:30] The Challenges of Post-Quantum Cryptography
[27:29] From Engineer to CTO
[30:20] A Practical Quantum Security Plan for CTOs
[36:56] Identifying Critical Systems and Data
[41:03] Taking the Easy Wins
[43:12] Preparing Vendors for the Quantum Transition
[43:57] Avoiding Migration Debt
[45:59] Building Crypto Agility
[48:35] The Quantum Challenge for IoT
[54:50] Preparing for Q Day

Find more from Conor Deegan and learn more about Project 11 through his professional channels: projecteleven.com, X, and LinkedIn. Conor welcomes direct contact on post-quantum migration questions.

Find more from Adam on https://www.linkedin.com/in/adamhorner/ and https://www.youtube.com/@TheCTOplaybook, and explore coaching, cohorts, and how you can stay up to date at the https://www.thectoplaybook.com/, helping you build your own playbook for your path at your pace.

If you prefer listening, check out the podcast at https://bit.ly/thectoplaybook.

Twenty years at one company should have made my guest predictable, and that is exactly the trap he built a method to escape.

Build your own CTO Playbook at www.theCTOplaybook.com - the leadership platform built for the full CTO journey. Coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.

Krystian Kolondra runs the browser portfolio at Opera, a set of products used by more than 300 million people, and he has spent two decades watching what happens to technical judgment when the work that built it starts to disappear.

His argument is uncomfortable. Your judgment was earned through execution, and AI compresses execution. So what is training your judgment now?

His answer starts somewhere I did not expect: an audit of the questions you stop asking. He calls it the shape of your curiosity, and he thinks most leaders have never looked at theirs.

We get into why he refuses to check AI's output and flips the task back on the model instead. There is a sniper analogy that reframes what "learning from failure" actually requires. There is a story about Opera GX where the first questions his team asked turned out to be the wrong ones, and the right ones only appeared once they went somewhere uncomfortable.

If you lead engineers, and you have felt the ground shift under what "senior judgment" means, this conversation gives you something concrete to practice tomorrow morning, before your first coffee.

You'll Learn:

[0:00] Introduction
[5:46] Twenty years at Opera and the business behind free browsers
[7:18] Why leading five hundred people is a different job entirely
[9:39] The temptation to stick with what already worked
[12:39] Curiosity as a counterweight to accumulated experience
[17:44] How the gamer browser came from asking the wrong questions
[23:26] Learning from failure means planning the shot before firing
[29:06] How AI compresses execution but never the judgment
[36:14] Auditing the questions you never ask to find blind spots

Resources Mentioned:

A Beautiful Constraint by Adam Morgan and Mark Barden | Book
Theory of Constraints by Eliyahu M. Goldratt | Book
Really Achieving Your Childhood Dreams (aka The Last Lecture) with Randy Pausch | TED Talk
Eric Ries, Validated Learning | Wikipedia
Igor Grossmann | Website
A route to well-being: intelligence versus wise reasoning by Grossmann, I. et al. | Article

Unlock more ways to make your browser yours with deeper personalization and an expanded modding universe with the Opera GX Gaming Browser here.

Find more from Krystian Kolondra on LinkedIn.

Find more from Adam on LinkedIn and YouTube, and explore coaching, cohorts, and how you can stay up to date at theCTOplaybook.com, helping you build your own playbook for your path at your pace.

Most CTOs think adopting AI means picking the right tools, but Sumeet argues the real work is closing the accountability gap between agents and engineers.

Build your own CTO Playbook at www.theCTOplaybook.com - the leadership platform built for the full CTO journey. Coaching, podcast, and community to help you lead with clarity, confidence, and strategic impact.

My guest this week is Sumeet Vaidya, co-founder and CEO of Crafting, who spent years at Facebook, Uber, and Discord before building the infrastructure enterprise engineering teams now use to put agents to work safely.

His perspective matters because he sees what CTOs say publicly, and what their teams are actually doing internally, and the gap is bigger than most leaders want to admit.

Roughly 80% of enterprise engineering orgs, he estimates, are doing close to nothing meaningful with AI. The rest are either reacting to hype or trying to build something durable, and the difference is not the tools they pick.

One partner running 3,000 agents against 250 engineers changed how he thinks about capacity entirely. That number is where his six diagnostic questions come from and where the cracks appear first: brittle CI/CD, accountability gaps for agents, and a hiring pattern that's storing up debt for the next downturn.

If you're under pressure to show AI gains while cutting token spend, this one is aimed at you.

You'll Learn:

[0:00] Introduction
[2:25] The disconnect between what companies say and what teams do
[4:38] Why 80% of enterprises watch and wait on agents
[9:31] Chasing the latest model as a vanity metric
[14:14] Resilient cultures survive shocks that short-term thinking cannot
[15:46] The engineering cultures that shaped Sumeet's career
[28:51] Silicon Valley is not the whole world
[33:02] What breaks if you 10X the team today
[42:31] Hiring only senior engineers stores up hidden debt
[47:11] Turning engineers from code writers into builders

Find more from Sumeet Vaidya on LinkedIn, X, or explore the Crafting Website.

Find more from Adam on LinkedIn and YouTube, and explore coaching, cohorts, and how you can stay up to date at theCTOplaybook.com, helping you build your own playbook for your path at your pace.