Tech Lead Journal

What if the MCP server you installed last week is silently leaking your emails to a stranger? The AI tools boosting your productivity could already be your biggest security liability. MCP (Model Context Protocol) has quickly become the standard for connecting AI agents to external tools and data sources. But as adoption accelerates, so do the risks – from malicious servers harvesting your credentials in the background, to local processes exposed to your entire network with no authentication. Most developers install MCP servers without fully understanding what code is running or who wrote it, creating serious supply chain and shadow IT problems inside organizations. In this episode, Ariel Shiftan, CTO of MCPTotal, explains how MCP actually works, why there is a wide gap between its original design and how it is used in practice, and what that gap means for security. He also walks through real zero-days his team has discovered and shares practical advice for developers and enterprise leaders trying to adopt MCP without compromising their security posture. Key topics discussed: Timestamps: _____ Ariel Shiftan’s Bio Ariel is a software engineer and security expert with more than 20 years of hands-on and executive leadership experience across cybersecurity, distributed systems, and AI infrastructure. He holds a PhD in Computer Science, specializing in advanced algorithms and systems. Earlier in his career, Ariel founded NorthBit, a deep-tech cybersecurity firm that was acquired by Magic Leap in 2016, where he led product security globally, overseeing the security lifecycle across more than 700 engineers. He has also led applied AI breakthroughs, including heading an XPRIZE-winning team that used deep learning to fight malaria in Africa. Follow Ariel: linkedin.com/in/shiftanmcptotal.io Like this episode? Show notes & transcript: techleadjournal.dev/episodes/249. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Think you’re just “not a people person”? Most tech leaders quietly believe this about themselves, and it’s exactly what’s holding them back. In this episode, Martijn Versteeg, founder of peer leadership community Group Effort and former CPTO with a background in organizational psychology, makes the case that it’s not: human behavior follows predictable patterns you can understand and work with, just like any system. The conversation covers a six-variable model for understanding what drives behavior and disengagement on your team, why popular personality tools like MBTI and DiSC often do more harm than good, and a clear structure for delivering bad news without the usual stress buildup. We also get into what it really takes to let go of hands-on coding when you move into leadership, why developing a product mindset matters even if product isn’t in your title, and the psychological risks of heavy AI use that most teams still aren’t thinking about. Key topics discussed: Timestamps: _____ Martijn Versteeg’s Bio Martijn Versteeg is the founder of Group Effort, a Netherlands-based collective that empowers tech and product leaders across Europe through peer groups, offsites, and specialized training. As a key figure in the global product community, he is also an organizer of the Product Mastery Conference, where he helps curate insights for the next generation of product leaders. Before founding Group Effort, Martijn built and successfully sold an EdTech IT platform and spent over five years as an Agile coach and Scrum Master. His unique perspective on leadership is rooted in high-performance athletics; at just 22 years old, he served as the National Rowing Coach for Singapore. Today, Martijn is a vocal advocate for community-led learning. He frequently challenges leaders to move past the search for “golden nuggets” of wisdom and instead focus on the consistent, incremental iterations that solve the “hard people stuff” in scaling organizations. Follow Martijn: linkedin.com/in/versteeggroupeffort.nlgroupeffort.nl/newslettergroupeffort.nl/action Like this episode? Show notes & transcript: techleadjournal.dev/episodes/248. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Is your platform engineering initiative struggling to deliver results? The problem might not be your tools or technology at all. In this episode, Sam Barlien, Community Organizer at Platform Engineering (the world’s largest platform engineering community), shares insights from speaking with nearly 400 engineering leaders last year about why their platform initiatives succeed or fail. The biggest revelation: it’s almost never about the tools. Sam explains why treating your internal platform like a product, complete with user research, documentation, and a product manager mindset, is the key differentiator between real platform engineering and just a rebranded operations team. He breaks down how to start small with a minimum viable platform, measure what actually matters, and build golden paths that developers want to follow. The conversation also covers how AI is both accelerating the need for platform engineering and transforming how platforms are built and operated. Key Topics Discussed: Timestamps: _____ Sam Barlien’s Bio Sam Barlien is a community organiser for the Platform Engineering Community. He is a tech nerd, and has been involved in tech communities for more than 10 years. He helps manage Platform Weekly, co-hosts PlatformCon, and drives the community Ambassador program, blog and Youtube channel. Follow Sam: linkedin.com/in/sam-barlien-3b2579184platformengineering.org Like this episode? Show notes & transcript: techleadjournal.dev/episodes/247. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(05:13) Brought to you by Sweep AI Sweep is the fastest coding assistant for JetBrains. It lets you write code 10x faster. Finally, AI that works in JetBrains. Download for free at ⁠sweep.dev⁠. What if Southeast Asia had its own ChatGPT that cost 20x less? Bruce Yang built Agnes AI to solve what global companies ignore: accessible AI for emerging markets. In this episode, Bruce Yang, CEO and founder of Agnes AI, explains how he’s built Southeast Asia’s fastest-growing AI platform with 4 million registered users and 300K daily active users. After working at Microsoft and LinkedIn in Silicon Valley, Bruce returned to Singapore and started his PhD at NUS right before COVID, positioning him perfectly to ride the AI wave. Agnes AI uses smaller, specialized models trained on Southeast Asian languages and local user data to deliver productivity features like deep research, PowerPoint generation, and AI-powered group chats at 1/20th the cost of major competitors. We discuss the challenges of building AI for emerging markets, the importance of keeping humans in the loop for critical thinking, and why Bruce believes the future of AI belongs to applications, not just models. Key topics discussed: Timestamps: _____ Bruce Yang’s Bio Bruce Yang is the founder and CEO of Agnes AI, a consumer AI platform making intelligence more collaborative, creative, and accessible. A Raffles Institution graduate, he studied Math and Computer Science at UC Berkeley, earned a Master’s from HEC Paris, and is pursuing a PhD at NUS. He previously worked at Microsoft and LinkedIn in Silicon Valley. Agnes AI redefines how people interact with AI through group chats, AI-assisted games, real-time content creation, slides generation, and research tools. Bruce envisions AI as a shared experience that amplifies human creativity and collaboration, enhancing rather than replacing human thinking and imagination. Follow Bruce: linkedin.com/in/tongbruceyanghttps://agnes-ai.com/bruce@sapiens-ai.io Like this episode? Show notes & transcript: techleadjournal.dev/episodes/246. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(05:22) Brought to you by Cyberhaven AI is exfiltrating your data in fragments. Not one big breach — a prompt here, a screenshot there, a quiet export into a shadow AI tool. Every week, AI makes your team faster and your data harder to see. Files are moved to new SaaS apps, models are trained on sensitive inputs, and legacy DLP is blind to the context that matters most. On February 3rd at 11 am Pacific, Cyberhaven is unveiling a unified DSPM and DLP platform, built on the original data lineage, so security teams get X-ray vision into how data actually moves — and can stop risky usage in real time. Watch the launch live at cyberhaven.com/techleadjournal. Did you know Singapore is one of the world’s top countries launching cyberattacks? Not as a victim, but as the source. Your routers, smart TVs, robot vacuums, or network-attached storage could be part of a massive botnet right now. In this eye-opening episode, Joseph Yap, founder of Otonata and cybersecurity expert, reveals the hidden cyber threat lurking in our homes. He reveals how everyday devices from routers to smart TVs become attack weapons. He explains why Singapore’s excellent infrastructure ironically makes it attractive for hackers and shares practical steps to protect your network. From residential proxies renting out your internet connection to teenagers running ransomware gangs, this conversation exposes the gap between our connected lives and our digital security practices. Key topics discussed: Timestamps: _____ Joseph Yap’s Bio With 20+ years in Operations and Supply Chain, Joseph Yap founded Otonata (https://otonata.com) after realizing how vulnerable home networks are to security breaches. Otonata brings corporate-grade cybersecurity to homes using digital hygiene and lean management principles, protecting dozens of households from growing threats posed by AI, smart devices, and expanding attack surfaces. Follow Joseph: linkedin.com/in/-joseph-yaphttps://otonata.com/https://otonata.com/hack-check Like this episode? Show notes & transcript: techleadjournal.dev/episodes/245. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(06:23) Brought to you by Sweep AI Sweep is the fastest coding assistant for JetBrains. It lets you write code 10x faster. Finally, AI that works in JetBrains. Download for free at sweep.dev. 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: Timestamps: _____ 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.com/in/realgenekim@RealGeneKimitrevolution.comhttps://itrevolution.com/product/vibe-coding-book/ Like this episode? Show notes & transcript: techleadjournal.dev/episodes/244. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

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: Timestamps: Like this episode? Show notes & transcript: techleadjournal.dev/episodes/243. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(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: Timestamps: _____ 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.com/in/jurgenappelojurgenappelo.comsubstack.jurgenappelo.comhttps://jurgenappelo.com/pages/human-robot-agent Like this episode? Show notes & transcript: techleadjournal.dev/episodes/242. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(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: Timestamps: _____ 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.com/in/adam-tornhill-71759b48codescene.compragprog.com/titles/atcrime2/your-code-as-a-crime-scene-second-edition Like this episode? Show notes & transcript: techleadjournal.dev/episodes/241. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(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: Timestamps: _____ 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.com/in/gregshovepersonalmath.substack.comsectionai.comprof.ai Like this episode? Show notes & transcript: techleadjournal.dev/episodes/240. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

(06:06) 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. Why do organizations constantly complain about having too much technical debt? Because they’re solving the wrong problem. In this episode, Dr. Andrew Brown, author of “Taming Your Dragon: Addressing Your Technical Debt,” reveals a profound insight: technical debt isn’t fundamentally a technical problem. It’s a trade-off problem rooted in human bias, organizational systems, and economic incentives. Through his innovative “Technical Debt Onion Model,” Andrew shows how decisions about code quality happen across five interconnected layers, from individual cognitive biases to wicked problem dynamics. Andrew explains why the financial debt analogy is dangerously misleading and, more importantly, how others can rack up debt you’ll eventually pay for. Drawing from behavioral economics, systems thinking, and organizational theory, he reveals why our emotions, not logic, drive most technical decisions, and how to work with this reality rather than against it. Key topics discussed: Timestamps: _____ Andrew Brown’s Bio Andrew Richard Brown has worked in software since 1999, starting as an SAP programmer fixing Y2K bugs. He realized the biggest problems in software development were human, not technical, and has since helped teams improve performance by addressing these issues. Andrew coaches organizations on software development and quality engineering, focusing on technical debt, risk in complex systems, and project underestimation. He investigates how cognitive biases drive software problems and applies behavioral science techniques to solve them. His research has produced counterintuitive insights and fresh approaches. He regularly speaks at international conferences and runs a growing YouTube channel on these topics. Follow Andrew: linkedin.com/in/andrew-brown-4b38062@behaviouralsoftwareclub705brownsensei@hotmail.comhttps://www.amazon.com/Taming-Your-Dragon-Addressing-Technical/dp/B0CV4TTP32/ Like this episode? Show notes & transcript: techleadjournal.dev/episodes/239. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Why does an AI that brilliantly generates code suddenly fail at basic math? The answer explains why your LLM will fail when you least expect it. In this episode, Emmanuel Maggiori, author of “Smart Until It’s Dumb” and “The AI Pocket Book,” cuts through the AI hype to reveal what LLMs actually do and, more importantly, what they can’t. Drawing from his experience building AI systems and witnessing multiple AI booms and busts, Emmanuel explains why machine learning works brilliantly until it makes mistakes no human would ever make. He shares why businesses repeatedly fail at AI adoption, how hallucinations are baked into the technology, and what developers need to know about building reliable AI products. Whether you’re implementing AI at work or concerned about your career, this conversation offers a grounded perspective on navigating the current AI wave without getting swept away by unrealistic promises. Key topics discussed: Timestamps: _____ Emmanuel Maggiori’s Bio Emmanuel Maggiori, PhD, is a software engineer and 10-year AI industry insider. He has developed AI for a variety of applications, from processing satellite images to packaging deals for holiday travelers. He is the author of the books Smart Until It’s Dumb, Siliconned, and The AI Pocket Book. Follow Emmanuel: linkedin.com/in/emaggioriemaggiori.com Like this episode? Show notes & transcript: techleadjournal.dev/episodes/238. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Can decades-old management philosophy actually help us tackle AI’s biggest challenges? In this episode, John Willis, a foundational figure in the DevOps movement and co-author of the DevOps Handbook, takes us through Dr. W. Edwards Deming’s System of Profound Knowledge and its surprising relevance to today’s most pressing challenges. John reveals how Deming’s four-lens framework—theory of knowledge, understanding variation, psychology, and systems thinking—provides a practical approach to managing complexity. The conversation moves beyond theoretical management principles into real-world applications, including incident management mistakes that have killed people, the polymorphic nature of AI agents, and why most organizations are getting AI adoption dangerously wrong. Key topics discussed: Timestamps: _____ John Willis’ Bio John Willis is a prolific author and a foundational figure in the DevOps movement, co-authoring the seminal The DevOps Handbook. With over 45 years of experience in IT, his work has been central to shaping modern IT operations and strategy. He is also the author of Deming’s Journey to Profound Knowledge and Rebels of Reason, which explores the history leading to modern AI. John is a passionate mentor, a self-described “maniacal learner”, and a deep researcher into systems thinking, management theory, and the philosophical implications of new technologies like AI and quantum computing. He actively shares his insights through his “Dear CIO” newsletter (aicio.ai) and newsletters on LinkedIn covering Deming, AI, and Quantum. Follow John: linkedin.com/in/johnwillisatlantax.com/botchagalupeaicio.ailinkedin.com/newsletters/attention-is-all-you-need-7167889892029505536linkedin.com/newsletters/profound-7161118352210288640linkedin.com/newsletters/rebels-of-uncertainty-7359198621222719490 Like this episode? Show notes & transcript: techleadjournal.dev/episodes/237. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

In this episode, Honey Mittal, CEO and co-founder of Locofy.ai, explores one of the most exciting transformations in software development: the convergence of design and engineering through AI-powered automation. Honey shares the fascinating journey of building Locofy, a tool that converts Figma designs into production-ready front-end code. But this isn’t just another AI hype story. It’s a deep dive into why Large Language Models (LLMs) fundamentally can’t solve design-to-code problems, and why his team spent four years building specialized “Large Design Models” from scratch. Key topics discussed: Whether you’re a front-end engineer tired of translating design pixel-by-pixel, a designer curious about coding, or a technical leader evaluating AI development tools, this episode offers practical insights into the future of software development. Timestamps: _____ Honey Mittal’s Bio Honey Mittal is the CEO and co-founder of Locofy.ai, a platform that automates front-end development by converting designs into production-ready code. Originally an engineer who built some of the first mobile apps in Singapore, Honey transitioned into product leadership after realizing his natural strength lay in identifying high-impact problems. He set a goal to become a CPO by 30 and achieved it, leading product transformations at major Southeast Asian scale-ups like Wego, FinAccel, and Homage. Driven by a decade of experience and the “grunt work” he and his co-founder faced, he started Locofy to solve the costly friction between design and engineering. Honey is passionate about the future of AI in development, the rise of the “Design Engineer”, and proving that globally competitive, deep-tech companies can be built from Southeast Asia. Follow Honey: linkedin.com/in/honeymittalx.com/HoneyMittal07locofy.ai Like this episode? Show notes & transcript: techleadjournal.dev/episodes/236. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Can you navigate AI disruption without understanding your landscape? Discover how to gain true situational awareness. The rise of AI has exposed a fundamental problem in how organizations make decisions. Most leaders operate using stories and graphs, not actual maps of their landscape. This leaves them vulnerable to disruption and unable to make informed choices about where to apply new technologies. The result is chaos, waste, and strategic mistakes that could have been avoided. In this episode, Simon Wardley, creator of Wardley Mapping, explains how to build true situational awareness in your organization. He shares why most business “maps” aren’t really maps at all, how to understand the landscape before making decisions, and what leaders need to know about AI adoption beyond the current hype. Key topics discussed: Timestamps: _____ Simon Wardley’s Bio Simon Wardley is a researcher, former CEO, and the creator of Wardley Mapping, a powerful method for visualizing and developing business strategy. His journey began accidentally after a bookseller recommended Sun Tzu’s The Art of War, which sparked a fascination with understanding the competitive “landscape.” As the former CEO of an online photo service acquired by Canon, he felt like a “fake CEO,” leading with stories while lacking true situational awareness. This led him to discover that almost all business “maps” were merely graphs, prompting him to develop his own mapping technique. Today, his work is used by organizations like NASA and taught at multiple MBA programs, helping leaders to “look before they leap” and navigate complex technological and market shifts, including the current disruption caused by AI. Follow Simon: linkedin.com/in/simonwardleyx.com/swardleywww.swardleymaps.com Like this episode? Show notes & transcript: techleadjournal.dev/episodes/235. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

How much of your code exists only to prevent failures? Discover a new paradigm for building reliable applications. In this episode, Preeti Somal, SVP at Temporal, explores a paradigm shift that can dramatically boost productivity and give developers peace of mind. Drawing on her experience leading massive infrastructure at Yahoo and HashiCorp, she explains Temporal’s concept of durable execution that helps developers focus on business logic and remove reliability concerns. Preeti also discusses key findings from Temporal’s first State of Development Report. In this episode, you will learn about: Timestamps: _____ Preeti Somal’s Bio Preeti is Senior Vice President of Engineering at Temporal. Preeti is passionate about building great products, growing world class organizations and solving complex problems. Prior to Temporal, Preeti led the Platform, Security and IT engineering organizations at HashiCorp. Her extensive career includes engineering leadership roles at Yahoo!, VMware and Oracle. While at Yahoo! Preeti was VP of Cloud Services in the Platform organization delivering highly scalable services used by engineers across Yahoo to build and operate applications with improved agility, reliability and security. These services power Yahoo!’s consumer and advertising business. Follow Preeti: linkedin.com/in/preeti-somal-131890x.com/psomaltemporal.io/pages/state-of-development-2025 Like this episode? Show notes & transcript: techleadjournal.dev/episodes/234. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

“Engineering leaders are stuck between the expectations put out by sensational headlines and the reality of what they’re seeing in their organization. There’s a big disappointment gap.” Is your AI investment paying off? Many leaders struggle to see real ROI beyond the hype. In this episode, Laura Tacho, CTO of DX, shares DX’s new research on measuring AI adoption success across 38,000+ engineers. Our conversation reveals why acceptance rates are misleading metrics and introduces DX’s new AI Measurement Framework™ with its three critical dimensions: utilization, impact, and cost. Learn why treating AI as an organizational problem closes the “disappointment gap” between hype and reality. Note: This episode was recorded in July 2025. The AI adoption rate mentioned has since risen to nearly 80%. In this episode, you will learn about: Timestamps: _____ Laura Tacho’s Bio Laura Tacho is CTO at DX, a developer intelligence platform, co-author of the Core 4 developer productivity metrics framework, and an executive coach. She’s an experienced technology leader and engineering leadership coach with a strong background in developer tools and distributed systems. Her career includes leadership roles at organizations such as CloudBees, Aula Education, and Nova Credit, where she specialized in building high-performing engineering teams and delivering impactful products. Laura has worked with thousands of engineering leaders as they work to improve their engineering practices with data. Follow Laura: linkedin.com/in/lauratachox.com/rhein_weinlauratacho.comgetdx.com/whitepaper/ai-measurement-framework/?utm_source=techleadjournalgetdx.com/guide/ai-assisted-engineering/?utm_source=techleadjournalgetdx.com/ai-code-metrics Like this episode? Show notes & transcript: techleadjournal.dev/episodes/233. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

“Architecture is something that has to emerge naturally from the code. If it doesn’t make the code better, more elegant, and more flexible, then you should not be doing it.” Why do so many developers have a love-hate relationship with ORM? The creator of Hibernate reveals the real reasons behind the controversy and what’s being done to fix the fundamental issues. In this episode, Gavin King, the creator of Hibernate, shares the story behind its creation, from a debate with his boss to its rise as a popular open-source. He dives deep into why developers often dislike ORM, pinpointing the “magic” of the stateful persistence context as a major pain point. Gavin explains how modern specifications are fixing these historical issues with an emphasis on type safety and more explicit, stateless operations, giving developers greater control. Key topics discussed: Timestamps: _____ Gavin King’s Bio Gavin King is the creator of Hibernate, the revolutionary framework that redefined data persistence for millions of Java developers. A key figure in the evolution of enterprise Java, he has led the development of major industry standards like the Java Persistence API (JPA) and CDI. After a decade designing the Ceylon programming language, he has returned to his roots to advance the next generation of data persistence with Jakarta EE. Follow Gavin: linkedin.com/in/gavinkingx.com/1ovthafewhibernate.org Like this episode? Show notes & transcript: techleadjournal.dev/episodes/232. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Are long code review cycles killing your engineering team’s velocity? Learn how top engineering teams are shipping code faster without sacrificing quality. In this episode, Greg Foster, CTO and co-founder of Graphite, discusses the evolution of code review practices, from the fundamentals of pull requests to the future of AI in code review workflows. He shares the secrets behind how the Graphite team became one of the most productive engineering teams by leveraging techniques like small code changes and stacked PRs (pull requests). Key topics discussed: Timestamps: _____ Greg Foster’s Bio Greg Foster is the CTO and co-founder of Graphite, an a16z and Anthropic-backed company helping teams like Snowflake, Figma, and Perplexity ship faster and scale AI-generated code with confidence. Prior to Graphite, Greg was a dev tools engineer at Airbnb. There, he experienced the impact of robust internal tooling on developer velocity and co-founded Graphite to bring powerful, AI-powered code review to every team. Greg holds a BS in Computer Science from Harvard University. Follow Greg: linkedin.com/in/gregmfosterx.com/gregmfostergreg@graphite.devgraphite.devx.com/withgraphite Like this episode? Show notes & transcript: techleadjournal.dev/episodes/231. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

Struggling with technical debt and code quality? Learn how a technical coach can help your team level up. In this episode, Emily Bache, a Samman technical coach, shares her proven method for building better engineering teams through structured learning and collaborative coding. We explore ensemble programming, learning hours, and why AI makes fundamental engineering practices more important than ever. Key topics discussed: Timestamps: _____ Emily Bache’s Bio Emily Bache is an independent consultant, YouTuber and Technical Coach. She works with developers, training and coaching effective agile practices like Refactoring and Test-Driven Development. Emily has worked with software development for 25 years, written two books and teaches courses on platforms including Pluralsight and O’Reilly. A frequent conference speaker, Emily has been invited to keynote at prestigious developer events including EuroPython, Craft and ACCU. Emily founded the Samman Technical Coaching Society in order to promote technical excellence and support coaches everywhere. Follow Emily: linkedin.com/in/emilybachex.com/emilybachesw-development-is.social/web/@emilybachegithub.com/emilybacheemilybache.comsammancoaching.orgyoutube.com/@EmilyBache-tech-coachyoutube.com/@ModernSoftwareEngineeringYT Like this episode? Show notes & transcript: techleadjournal.dev/episodes/230. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.