Tech Lead Journal

(06:23) Brought to you by Sweep AI
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Is the era of writing code by hand coming to an end? Gene Kim explains how vibe coding solved problems he abandoned for 13 years and why the best days of coding might be ahead of us.
In this episode, Gene Kim shares his transformation from someone who hadn’t written production code in decades to building ambitious projects in minutes. He explains how meeting Steve Yegge and discovering vibe coding reignited his passion for programming.
Gene breaks down the FAAFO framework (Fast, Ambitious, Autonomous, Fun, Optionality) of vibe coding benefits and addresses the real risks of vibe coding, from deleted databases to corrupted repos. He emphasizes that developers need to shift from line cook to head chef, mastering delegation, architecture, and faster feedback loops. The conversation also explores whether AI will eliminate or expand developer roles, what skills matter most when hiring, and how organizations can build a vibe coding culture.
Key topics discussed:
Gene’s jaw-dropping a-ha moment solving his 13-year problem
The FAAFO framework for measuring vibe coding benefits
From line cook to head chef: the new developer skillset
Real risks and downsides of vibe coding
Will we need fewer developers or 10x more software?
Why feedback loops must be 100x faster than before
Building vibe coding culture across enterprise teams
Timestamps:
(00:00) Trailer & Intro
(03:13) What shaped Gene Kim’s career in DevOps and technology?
(07:26) How did Gene Kim’s books like Phoenix Project come about?
(09:55) What’s the story behind the Phoenix Project graphic novel?
(12:21) What was Gene Kim’s a-ha moment with vibe coding?
(14:41) How did Steve Yegge and Gene Kim collaborate on the book?
(21:06) What is vibe coding and how is it different from regular coding?
(25:57) What is the FAAFO framework for vibe coding benefits?
(32:08) Will AI replace software developers?
(36:10) What are the risks and downsides of vibe coding?
(41:51) What skills do developers need in the age of vibe coding?
(46:56) Why are feedback loops critical when using AI for coding?
(51:59) How can organizations adopt vibe coding as a culture?
(57:37) What should you look for when hiring developers in the AI era?
(59:45) 2 Tech Lead Wisdom
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Gene Kim’s Bio
Gene Kim is a WSJ bestselling author and researcher who has studied high-performing technology organizations since 1999. The founder and former CTO of Tripwire, he has authored several industry-defining books, including The Phoenix Project and The DevOps Handbook, with over 1 million copies sold. He also organizes the Enterprise Technology Leadership Summit.
Follow Gene:
LinkedIn – linkedin.com/in/realgenekim
Twitter – @RealGeneKim
IT Revolution – itrevolution.com
 Vibe Coding - https://itrevolution.com/product/vibe-coding-book/

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Show notes & transcript: techleadjournal.dev/episodes/244.
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Why are tech companies really laying off developers? The uncomfortable truth has nothing to do with AI efficiency and everything to do with running out of ideas.
In this episode, Stephan Schmidt, CTO coach and author of “The Amazing CTO’s Missing Manual,” shares a perspective on AI adoption that most tech leaders aren’t talking about. Developer layoffs aren’t about AI replacing jobs; they reveal a deeper problem. Product management has become a bottleneck, creating shallow features just to keep developers busy rather than driving meaningful innovation. When AI accelerates development, this bottleneck becomes impossible to ignore.
Stephan explains why architecture must be AI-ready before teams can benefit from AI tools, how CTOs can manage unrealistic business expectations, and why junior developers actually have a massive opportunity right now. He also challenges the common belief that vibe coding will democratize software development, explaining why you need to be a strong developer to prompt effectively.
Key topics discussed:
Why AI layoffs reveal companies ran out of good ideas
Architecture must be AI-ready for real productivity gains
Vibe coding only works if you’re already a strong developer
Product engineering roles will replace traditional developers
MCP connections unlock AI value beyond code generation
Juniors have huge advantage as AI-native engineers
Iterate on plans, not prompts, when using AI tools
CTOs can finally “rise and shine” using AI strategically
Timestamps:
(00:00) Trailer & Intro
(03:19) How do companies become truly AI-first?
(04:13) How should CTOs manage unrealistic AI velocity expectations?
(08:35) AI Use Cases Beyond Code Generation
(12:04) What is MCP and how does it unlock AI value?
(15:04) Why Developers Resist AI Adoption
(18:35) Are AI layoffs caused by a lack of product innovation?
(21:22) What is the future for junior developers in the age of AI?
(24:36) Critical Thinking and Moving Up the Abstraction Layer
(27:24) Vibe Coding: Benefits and Pitfalls
(31:59) What is the difference between a Developer and a Product Engineer?
(35:59) Building an Effective AI Adoption Strategy
(38:06) AI Adoption Strategy for Development Teams
(40:44) Avoiding the AI Tech Zoo
(44:48) How do tech leaders handle AI data privacy and security?
(50:31) How is the CTO role changing in 2026?
(57:23) 3 Tech Lead Wisdom

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(04:11) Brought to you by Jellyfish
AI tools alone won’t transform your engineering org. Jellyfish provides insights into AI tool adoption, cost, and delivery impact – so you can make better investment decisions and build teams that use AI effectively. See for yourself at jellyfish.co/platform/ai-impact.

Are you managing your team the same way you did five years ago? With AI agents now part of the workforce, the old playbook no longer applies.
In this episode, Jurgen Appelo, author of “Human Robot Agent” and creator of Management 3.0 and unFIX, challenges conventional thinking about management, organizational design, and the future of work in the AI era. He explains why rigid frameworks like Scrum are becoming bottlenecks to AI speed and why he believes we need to completely rethink how organizations operate.
The conversation dives into the concept of creating “fast tracks” for AI agents while maintaining “slow tracks” for human collaboration. Jurgen also breaks down why team sizes are shrinking and why professionals must move beyond T-shaped skills to become M-shaped, multidisciplinary workers to remain relevant. He also shares his controversial take on why Scrum is “done” and why he trusts AI more than the average human when solving complex problems.
Key topics discussed:
Managing systems vs people in hybrid human-AI teams
Why patterns beat frameworks for organization design
Why Scrum is done: adapting Agile for the AI era
M-shaped workers: the new multidisciplinary skill
Fast and slow tracks: redesigning work for AI
Why AI outperforms average humans at complex problems
Critical thinking as the essential leadership skill
The new optimal team size and dynamic reteaming
Timestamps:
(00:00:00) Trailer & Intro
(00:02:20) Career Turning Points: Seven-Year Career Pivots
(00:05:29) Origins of Management 3.0
(00:08:31) Managing Systems, Not People
(00:12:35) Everlasting Management Principles
(00:17:21) unFIX: Patterns Over Frameworks
(00:24:27) Core unFIX Patterns
(00:31:39) Pipedrive Case Study: unFIX in Action
(00:38:16) M3K: Merging Management 3.0 and unFIX
(00:41:33) Skeptical Enthusiast: Balanced AI Perspective
(00:47:18) Co-Creating with Humans and Machines
(00:51:51) From T-Shaped to M-Shaped Workers
(00:56:38) Why I Trust AI More Than Humans
(01:00:19) Scrum is Done (Not Dead)
(01:05:50) Redesigning Organizations for AI: Fast and Slow Tracks
(01:09:25) 3 Tech Lead Wisdom
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Jurgen Appelo’s Bio
Jurgen Appelo is an author, speaker, and entrepreneur who helps leaders rewire their organizations for AI-driven leadership and autonomous digital agents. Recognized by Inc.com as a Top 50 Leadership Expert and Top 100 Leadership Speaker, he bridges opposing worldviews: human ingenuity and AI, leadership versus governance, stability with innovation, and individual growth fueling collective success. As founder of The unFIX Company (and previously founder of Management 3.0 and co-founder of Agile Lean Europe), Jurgen pioneers the future of work through stories, games, tools, and practices that challenge conventional thinking.
Follow Jurgen:
LinkedIn – linkedin.com/in/jurgenappelo
Website – jurgenappelo.com
Substack – substack.jurgenappelo.com
 Human Robot Agent – https://jurgenappelo.com/pages/human-robot-agent

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Show notes & transcript: techleadjournal.dev/episodes/242.
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(04:00) Brought to you by Unleash
Unleash is a private, flexible, and scalable feature flag system that lets teams decouple deployments from releases. It reduces the risk of shipping new features and gives organizations real-time control over what reaches production. And as AI accelerates development, Unleash helps engineering teams move fast and stay stable with safe rollouts and instant kill switches. Start a free trial of Unleash at ⁠getunleash.io/pricing⁠.

Why do so many software projects still fail despite modern tools? The answer often lies in the psychology of the team, not the technology stack.
Software development is often viewed purely as a technical challenge, yet many projects fail due to human factors and cognitive bottlenecks. In this episode, Adam Tornhill, CTO and Founder of CodeScene, shares his unique journey combining software engineering with psychology to solve these persistent industry problems. He explains the concept of “Your Code as a Crime Scene,” a method for using behavioral analysis to identify high-risk areas in a codebase that static analysis tools often miss.
Adam covers the tangible business impact of code health, specifically how it drives predictability and development speed. He explains why 1-2% of our codebase accounts for up to 70% of our development work, and how focusing on these hotspots can make our team 2x faster and 10x more predictable. Adam also provides a critical reality check on the rise of AI in coding, exploring whether it will help reduce technical debt or accelerate it, and offers strategies for maintaining quality in an AI-assisted future.
Key topics discussed:
Combining psychology and software engineering
Why predictability matters more than speed
Treating your codebase as a crime scene
Behavioral analysis vs. static analysis
The hidden danger of the “Bus Factor”
Will AI help or hurt code quality?
Why healthy code helps both humans and AI
Essential guardrails for AI-generated code
Timestamps:
(00:00) Trailer & Intro
(02:36) Career Turning Point: From Developer to Psychologist
(07:43) Why Engineering Leaders Need Psychology Knowledge
(09:29) The Root Cause of Failing Software Projects
(11:37) Why Code Abstractness Makes Quality Hard to Measure
(12:58) Aligning Code Quality with Business Outcomes
(14:15) Code Health: 2x Speed, 10x Predictability
(17:06) Why Predictability is Undervalued in Software
(19:53) TDD and Practices That Drive Code Quality
(21:57) Benchmarking Code Health Across the Industry
(24:06) Introducing “Your Code as a Crime Scene”
(26:30) Behavioral Code Analysis: Hotspot Analysis vs Static Code Analysis
(29:40) Behavioral Code Analysis: Understanding Change Coupling
(31:33) Dealing with God Classes
(33:14) Behavioral Code Analysis: The Social Side of Code
(36:48) Why Developers Aren’t Interchangeable
(39:14) Introduction to CodeScene
(42:06) Will AI Help or Hurt Code Quality?
(43:06) Essential Guardrails for AI-Generated Code
(45:54) Using CodeScene to Maintain Quality in the AI Era
(48:32) How AI Accelerates Technical Debt at Scale
(50:42) Why AI-Friendly Code is Human-Friendly Code
(54:31) The Reality Check: Future of Software Development with AI
(58:27) 3 Tech Lead Wisdom
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Adam Tornhill’s Bio
Adam Tornhill is the founder and CTO of CodeScene and the best-selling author of Your Code as a Crime Scene. Combining degrees in engineering and psychology, Adam helps companies optimize software quality using AI-driven methodologies. He is an international keynote speaker and researcher who enjoys retro computing and martial arts in his spare time.
Follow Adam:
LinkedIn – linkedin.com/in/adam-tornhill-71759b48
CodeScene – codescene.com
 Your Code as a Crime Scene – pragprog.com/titles/atcrime2/your-code-as-a-crime-scene-second-edition

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Show notes & transcript: techleadjournal.dev/episodes/241.
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(06:03) Brought to you by Unleash
Unleash is a private, flexible, and scalable feature flag system that lets teams decouple deployments from releases. It reduces the risk of shipping new features and gives organizations real-time control over what reaches production. And as AI accelerates development, Unleash helps engineering teams move fast and stay stable with safe rollouts and instant kill switches. Start a free trial of Unleash at getunleash.io/pricing.

Are you making critical decisions without consulting AI? Greg argues it’s now irresponsible for any leader to make high-stakes decisions without talking to AI first.
In this episode, Greg Shove, CEO of Section and a multi-time founder with 30 years of entrepreneurial experience, shares how AI is fundamentally different from any previous technology wave. Unlike traditional software that makes us more productive within our existing boundaries, AI allows us to jump capability boundaries – enabling individuals and organizations to do things they simply couldn’t do before.
Greg explains why most enterprise AI rollouts are failing (hint: they’re treating AI like software when it’s actually co-intelligence), how to cultivate resilience through multiple startup failures, and the practical strategies for getting teams to adopt AI (from simple hacks like putting a post-it note on your monitor to creating an entire AI-dedicated screen).
This conversation goes beyond the hype to explore both the superpowers and limitations of AI, the real organizational outcomes you can expect (spoiler: it’s not just about layoffs), and why moving from efficiency to creation is the key to unlocking AI’s true potential in your organization.
Key topics discussed:
Why AI breaks capability boundaries unlike any other tech
Treating AI as a thought partner, not just a productivity tool
Why most large organizations fail at AI deployment
Managing workforce anxiety during AI transformation
The four possible team outcomes when rolling out AI
Moving from efficiency (cut) to growth (create) with AI
The Post-it note hack that changed how teams use AI daily
Walking the walk: leading authentically in AI adoption
Timestamps:
(00:00:00) Trailer & Intro
(00:02:44) Career Turning Points
(00:06:03) Cultivating Entrepreneurial Resilience
(00:07:49) Understanding the AI Wave: Scale and Transformation
(00:12:29) Pivoting to AI: Section’s Transformation Journey
(00:17:57) AI as a Thought Partner
(00:22:57) Practical Tips for Leaders Using AI Daily
(00:30:49) Rolling Out AI Organization-Wide: Managing Change and Anxiety
(00:41:30) AI ROI: Beyond Efficiency to Creation
(00:51:01) AI-Powered Education: The ProfAI Approach
(00:57:53) 1 Tech Lead Wisdom
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Greg Shove’s Bio
Greg Shove is a seven-time CEO, all in on AI. After first using ChatGPT in February 2023, he pivoted his company Section to be AI-powered. Now he helps enterprise organizations move from AI-anxious to AI-proficient with a proven playbook, delivered through keynote speaking and executive workshops.
Greg is also the founder of Machine & Partners, an AI lab building custom enterprise AI applications, and co-author of Personal Math, a weekly newsletter sharing business insights for early-career leaders and founders.
Follow Greg:
LinkedIn – linkedin.com/in/gregshove
Newsletter – personalmath.substack.com
Section AI – sectionai.com
Prof AI – prof.ai

Like this episode?
Show notes & transcript: techleadjournal.dev/episodes/240.
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