Tech Lead Journal

Henry Suryawirawan

Great technical leadership requires more than just great coding skills. It requires a variety of other skills that are not well-defined, and they are not something that we can fully learn in any school or book. Hear from experienced technical leaders sharing their journey and philosophy for building great technical teams and achieving technical excellence. Find out what makes them great and how to apply those lessons to your work and team.

  1. #233 - Data Beats Hype: Measuring Your AI Adoption Impact - Laura Tacho

    HACE 9 H

    #233 - Data Beats Hype: Measuring Your AI Adoption Impact - Laura Tacho

    “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: The “Disappointment Gap” between AI hype and realityWhy the popular “acceptance rate” metric is misleadingThe DX AI Measurement Framework™ and its three dimensionsThe top time-saving AI use case (it’s not code generation!)How AI impacts long-term software quality and maintainabilityWhy organizational readiness matters for successful AI adoptionThe bigger bottlenecks beyond coding that AI has not yet solvedTreating AI agents as team extensions, not digital employeesTimestamps: (00:00:00) Trailer & Intro(00:02:32) Latest DX Research on AI Adoption(00:03:54) AI Role on Developer Experience(00:05:43) The Current AI Adoption Rate in the Industry(00:09:27) The Leader’s Challenges Against Al Hype(00:13:22) Measuring AI Adoption ROI Using Acceptance Rate(00:17:39) The DX AI Measurement Framework™(00:23:05) AI Measurement Framework: Utility Dimension(00:27:51) DX AI Code Metrics(00:30:31) AI Measurement Framework: Impact Dimension(00:32:57) The Importance of Measuring Productivity Holistically(00:35:54) AI Measurement Framework: Cost Dimension(00:38:34) AI Second Order Impact on Software Quality and Maintainability(00:42:38) The Danger of Vibe Coding(00:46:31) Treating AI as Extensions of Teams(00:52:31) The Bigger Bottlenecks to Solve Outside of AI Adoption(00:55:47) DX Guide to AI-Assisted Engineering(01:00:38) Being Deliberate for a Successful AI Rollout(01:02:32) 3 Tech Lead Wisdom_____ Laura Tacho’s BioLaura 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 – linkedin.com/in/lauratachoTwitter – x.com/rhein_weinWebsite – lauratacho.com AI Measurement Framework – getdx.com/whitepaper/ai-measurement-framework/?utm_source=techleadjournal Guide to AI-Assisted Engineering – getdx.com/guide/ai-assisted-engineering/?utm_source=techleadjournalAI code metrics – getdx.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.

    1 h y 7 min
  2. #232 - Hibernate Creator on Why Developers Hate ORM (And How We're Fixing It) - Gavin King

    22 SEP

    #232 - Hibernate Creator on Why Developers Hate ORM (And How We're Fixing It) - Gavin King

    “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: The origin story of Hibernate and the early frustrations with Java EEThe single biggest mistake that led some developers to hate ORMWhy type safety matters and how the new Jakarta specifications enable type-safe queriesWhy architecture should emerge from code, not from whiteboard diagramsA critique on industry dogmas and architecture best practices, including DDD aggregatesWhy disagreement is essential for healthy engineering teamsTimestamps: (00:00:00) Trailer & Intro(00:02:24) Career Turning Points(00:16:11) The Problems That Led to Hibernate Creation(00:24:22) Key Things That Make Hibernate Successful(00:31:57) Behind the Scene of Java EE Specifications(00:37:42) The Renaming of Java EE to Jakarta EE(00:40:15) Jakarta Persistence, Jakarta Data, Jakarta Query Language(00:47:20) The Importance of Type Safety(00:54:08) Why Some People Dislike ORM(01:00:47) The Fundamental of Data Fetching and Association(01:08:52) The Upcoming Jakarta Data and QL Updates(01:16:06) Gavin’s View on Software Architecture(01:26:08) The DDD from Gavin’s Perspective(01:30:55) Tech Lead Wisdom_____ 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 – linkedin.com/in/gavinkingTwitter – x.com/1ovthafewWebsite – hibernate.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.

    1 h y 35 min
  3. #231 - Faster Code Reviews, Faster Code Shipping with Stacked PRs - Greg Foster

    1 SEP

    #231 - Faster Code Reviews, Faster Code Shipping with Stacked PRs - Greg Foster

    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: The evolution of code review from bug-hunting to knowledge sharingBest practices for PRs and why small PRs get better feedbackHow stacked PRs eliminate waiting time in development workflowsThe rise of AI in the code review processWhy AI code review works best as an automated CI checkHow Graphite achieves P99 engineering productivityHiring engineers in the age of AI-assisted codingTimestamps: (00:00) Trailer & Intro(02:21) Career Turning Points(05:11) Now is The Golden Time to Be in Software Engineering(09:08) The Evolution of Code Review in Software Development(14:59) The Popularity of Pull Request Workflow(21:01) Pull Request Best Practices(26:17) The Stacked PR and Its Benefits(34:07) How Graphite Ships Code Remarkably Fast(40:03) The Cool Things About AI Code Review(45:23) Graphite’s Unique Recipes for Engineering Productivity(50:55) Hiring Engineers in the Age of AI(55:31) 2 Tech Lead Wisdom_____ Greg Foster’s BioGreg 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 – linkedin.com/in/gregmfosterX – x.com/gregmfosterEmail – greg@graphite.devGraphite – graphite.devGraphite X – x.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.

    1 h y 1 min
  4. #230 - Technical Coaching in the Age of AI with Samman (Ensemble) - Emily Bache

    25 AGO

    #230 - Technical Coaching in the Age of AI with Samman (Ensemble) - Emily Bache

    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: The role of a Technical Coach and the Samman Method explainedHow AI amplifies good engineering practices instead of replacing themHow to use ensemble programming to achieve single-piece flowRunning effective ensemble sessions and avoiding common failure modesWhy learning is part of the work, not only a side activityWhy pull requests should not be the primary tool for mentoring junior developersThe dangerous trend of “vibe coding” with AI toolsTimestamps: (00:00) Trailer & Intro(02:22) Career Turning Points(03:23) Being Part of Modern Engineering YouTube Channel(04:27) The Role of a Technical Coach(05:42) The Impact of AI on Technical Coaching(08:20) Sofware Engineering is a Learning Process(09:55) Optimizing Learning With Samman Method(11:40) The Samman Method: Ensemble (Mob Programming)(14:59) The Main Benefit of Ensemble: Single Piece Flow(17:26) How to Do Ensemble and Avoid Common Failure Modes(20:27) The Types of Coding to Ensemble On(22:12) The Importance of Trust, Communication, and Kindness(23:52) Common Things Development Teams Are Struggling With(25:37) Prompt Engineering(27:16) The Samman Method: Learning Hours(29:08) Learning is Part of the Work(31:32) The Practice of Learning as a Team(34:39) The Constraint When Learning from Pull Requests(36:30) Putting Aside Time for Learning Hours(39:14) Becoming a Technical Coach(41:23) How to Measure the Effectiveness of Technical Coaching(43:52) Danger of AI Assisted Coding(46:59) The (Still) Important Skills in the AI Era(49:56) Why We Should Not Refactor Through AI(52:41) The Samman Method & Technical Coaching Resources(53:29) 3 Tech Lead Wisdom(54:56) Finding Mentors for Career Progression_____ 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 – linkedin.com/in/emilybacheX – x.com/emilybacheMastodon – sw-development-is.social/web/@emilybacheGitHub – github.com/emilybacheWebsite – emilybache.comSamman Coaching – sammancoaching.orgYouTube – youtube.com/@EmilyBache-tech-coachModern Software Engineering – youtube.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.

    57 min
  5. #229 - The Management System for High-Performing Engineering Organizations - Michi Kono

    18 AGO

    #229 - The Management System for High-Performing Engineering Organizations - Michi Kono

    Why do engineering teams slow down as they scale? It’s not the technology—it’s the management systems. In this episode, Michi Kono, CTO at Garner Health and former engineering leader at Meta, Capital One, and Stripe, shares his battle-tested approach to building scalable engineering organizations. We explore why most teams slow down as they scale and how to build systems that accelerate growth. Our conversation covers everything from designing effective org charts to creating accountability without killing psychological safety. You’ll learn practical strategies for nurturing engineering culture while maintaining high-performance standards. Key topics discussed: The challenges of hypergrowth and the need to constantly reinvent yourselfHow to avoid slowdowns by holding teams accountable for outcomes, not just shipping codeThe art of designing org charts that maximize team autonomyBuilding a culture of accountability and learning from mistakes without blameWhen managers should stop writing code (and why this decision matters)The difference between being a people manager and an executiveWhy communication becomes the most critical skill at senior levelsTimestamps: (00:00) Trailer & Intro(02:10) Career Turning Points(03:55) Skills Advice for Engineers(06:46) The Challenges of a Hypergrowth Company(09:09) Learning and Growing in a Hypergrowth Company(12:07) The Slowdown in Engineering as You Scale(15:55) Designing Organization Structure Well(18:11) Effective Organization Chart Tips(21:05) Nurturing a Good Engineering Culture(25:37) Nurturing Psychological Safety(28:14) Learning from Mistakes & Performance Review(30:27) Being a Mission-Driven Company(32:11) Aligning Mission and Values in the Day-to-Day Work(34:45) The Importance of Management System in Organization(41:53) The Importance of Having Good Managers(45:30) For Strong ICs: Writing Code or Being a Manager?(50:55) The Difference Between a Manager Role and Executive Role(56:01) A Unique Thing Learned from Doing Payment Systems(58:43) 3 Tech Lead Wisdom_____ Michi Kono’s BioMichi Kono is the Chief Technology Officer (CTO) at Garner Health, a company on a mission to help people get better healthcare. With a unique and extensive career spanning multiple industries, Michi has navigated the entire spectrum of the tech world. He began his journey in startups, one of which was acquired, leading him to a role at Capital One. From there, he gained invaluable experience at tech giants like Meta and financial-tech leader Stripe before taking the helm at Garner Health. Michi is passionate about the art and science of scaling engineering teams, building resilient cultures, and designing effective management systems to drive success in high-growth environments. He believes deeply in empowering engineers, fostering accountability, and the critical importance of clear communication for any leader. Follow Michi: LinkedIn – linkedin.com/in/michikonoTwitter – x.com/michikonoGarner Health – getgarner.com Like this episode?Show notes & transcript: techleadjournal.dev/episodes/229.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

    1 h y 1 min
  6. #228 - Leading Transformational Engineering Teams with Craft in the AI Era - Mohan Krishnan

    11 AGO

    #228 - Leading Transformational Engineering Teams with Craft in the AI Era - Mohan Krishnan

    How do you build a high-performing engineering team in the AI era? And will AI make fundamental engineering skills obsolete? In this episode, Mohan Krishnan, Head of Engineering at Grab, shares lessons from leading multiple transformational engineering teams. Drawing from his experience at Grab, Bukalapak, BBM Emtek, and Pivotal Labs, Mohan explains why core engineering fundamentals still matter, even in the age of AI, and will become even more valuable than ever. He discusses building disciplined, high-performing engineering teams and the importance of hands-on leadership. We also explore the unique challenges and vast potential of the tech landscape in Southeast Asia. Key topics discussed: Why foundational skills like TDD and system design are becoming more critical in the age of generative AIHow to effectively use AI as a pair programmer for upskilling and idea generation, while avoiding the pitfalls of “vibe coding”Mohan’s “sports team” analogy for building successful engineering teams with discipline, a mix of seniority, and a culture of deep learningThe importance of hands-on technical leadership, and why even CTOs should “dive deep” to set the right engineering barThe state of engineering talent in Southeast Asia and what’s needed to bridge the gap in deep tech and AI developmentActionable career advice for junior and mid-career professionals navigating the AI-infused software industryTimestamps: (00:00:00) Trailer & Intro(00:02:08) Career Turning Points(00:06:03) Things We Should Learn in the AI Era(00:09:53) AI as a Pair Programmer(00:13:58) The Danger of Outsourcing Our Thinking to AI(00:17:29) The Dopamine Hit of Using AI(00:20:36) Building a Successful Transformational Engineering Team(00:25:33) The Discipline Rigor in An Engineering Team(00:29:14) Understanding & Delivering Outcomes for the Business(00:32:21) Having a Tough Approach as an Engineering Leader(00:39:07) Going Back as an IC at Google(00:45:40) The Importance of Being Hands-On with Recent Technologies for Leaders(00:52:40) Hands-on vs Micromanagement(00:55:11) Engineering Talents in Southeast Asia(00:58:06) Building Tech Talents in Southeast Asia(01:01:17) Bridging the AI Gap in Southeast Asia(01:04:03) Should We Still Pursue a Tech Career in the AI Era?(01:07:24) 2 Tech Lead Wisdom_____ Mohan Krishnan’s Bio Mohan Krishnan, based in Singapore, is currently a Head of Engineering at Grab. Mohan Krishnan brings experience from previous roles at Google, Bukalapak, BBM and Pt. Kreatif Media Karya. Mohan Krishnan holds a 1998 - 2002 Bachelor of Engineering in Multimedia, Electronics at Multimedia University. With a robust skill set that includes Ruby on Rails, Multithreading, Web Services, HTML, Services and more. Follow Mohan: LinkedIn – linkedin.com/in/mohangk Like this episode? Show notes & transcript: techleadjournal.dev/episodes/228. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

    1 h y 10 min
  7. #227 - Infrastructure as Code: Delivering Dynamic Systems for the Cloud Age - Kief Morris

    4 AGO

    #227 - Infrastructure as Code: Delivering Dynamic Systems for the Cloud Age - Kief Morris

    How has Infrastructure as Code changed in the last five years? Explore the key shifts and how to align your infrastructure to real business value. In this episode, Kief Morris, a Distinguished Infrastructure Engineer at Thoughtworks, returns to discuss the third edition of his book “Infrastructure as Code.” He shares fresh insights on designing and delivering dynamic systems for today’s cloud-driven world. Kief explores the evolution of IaC, practical methods for modern teams, the next generation of tools, and lessons learned from the recent years. Learn how to align infrastructure with business needs and manage today’s growing infrastructure complexities. Key topics discussed: How “Infrastructure as Code” book has evolved across three editionsWhy infrastructure decisions must align with business valueHow IaC and the toolchain have evolved over the last few yearsHandling the growing complexity of modern infrastructureThe rise of platform engineering and internal developer platformsTerraform vs. OpenTofu: which one should you use?Balancing governance, speed, and innovation in the cloud eraThe current limitations and role of AI in managing infrastructureTimestamps: (00:00) Trailer & Intro(02:39) Updates in the Last Five Years(04:13) Infrastructure as Code Definition(05:58) The Practice of Infrastructure as Code(06:32) The Differences Between the Book Editions(10:21) Aligning Infrastructure to the Business Value(15:03) Handling the Growing Infrastructure Complexities(19:10) The Tools and New Inventions in IAC(24:11) Terraform vs OpenTofu(27:38) Orchestrating Infrastructure Changes Using IAC(30:35) Platform Engineering(33:06) Internal Developer Platform Key Success Factor(37:15) Key Considerations of Building Teams with Infrastructure Skills(41:56) Infrastructure Compliance and Governance(45:53) Using AI for Infrastructure as Code(50:31) Using AI for Troubleshooting and Root Cause Analysis(51:50) 3 Tech Lead Wisdom_____ Kief Morris’s Bio Kief Morris is the author of the O’Reilly book Infrastructure as Code, and is a Distinguished Infrastructure Engineer at Thoughtworks, based in London. He works with clients and project teams around the world to explore, shape, and share better ways of working with cloud and infrastructure architecture. Kief started out as a developer and systems administrator in the dot-com boom days, then worked with a series of digital scaleups applying infrastructure automation before DevOps was a thing. He joined Thoughtworks in 2010 as the wider industry was discovering Infrastructure as Code, DevOps, and Cloud, which gave him the opportunity to bring what he had learned in the previous fifteen years to enterprise clients in many industries and many countries. He wrote the book Infrastructure as Code (now on the third edition) to share these ideas with a wider audience, which has given him a platform to meet and learn from an ever-growing variety of people and organizations. Follow Kief: LinkedIn – linkedin.com/in/kiefmorrisTwitter – x.com/kiefBlueSky – bsky.app/profile/kief.comPersonal Website – kief.comInfra as Code Website – infrastructure-as-code.com Infrastructure as Code – https://www.oreilly.com/library/view/infrastructure-as-code/9781098150341/ Like this episode? Show notes & transcript: techleadjournal.dev/episodes/227. Follow @techleadjournal on LinkedIn, Twitter, and Instagram. Buy me a coffee or become a patron.

    56 min
  8. #226 - Ex-Google Duplex Eng Lead on Disrupting $2B Clinical Trials with AI - Patrick Leung

    28 JUL

    #226 - Ex-Google Duplex Eng Lead on Disrupting $2B Clinical Trials with AI - Patrick Leung

    Ever wondered how AI is being applied in the world of clinical trials where human lives are at stake? In this episode, Patrick Leung, CTO of Faro Health and former Google Duplex Engineering Lead, reveals how AI is transforming the clinical trial process — a process that can cost up to $2 billion per drug and take over 10 years to complete. Patrick reveals how Faro Health’s AI systems generate complex clinical documentation in minutes instead of months in which hallucinations aren’t acceptable, while navigating the strict regulatory requirements of the healthcare industry. Patrick also reflects on the evolution of AI technologies, the realities of large language models, and offers practical advice on how to thrive in the rapidly changing AI-driven era. Key topics discussed: The evolution of AI from image recognition and Google Duplex to LLMsHow Faro Health uses AI to transform clinical trial processThe challenges of applying AI in highly regulated industriesAI’s potential to save time and millions in clinical trialsHow to tackle AI hallucinations and ensure high-quality outputsPatrick’s thoughts on AGI and the future of AI beyond current capabilitiesThe viability and limitations of vibe codingStrategies and advice for individuals to thrive in the AI eraTimestamps: (00:00) Trailer & Intro(02:09) Career Turning Points(02:46) The Advancements of AI in the Past 10 Years(04:13) Non-LLM Types of AI(05:42) The Google Duplex(07:28) The Use of AI in Faro Health(09:44) Tackling AI Hallucination for Clinical Documents(12:25) Building the Evaluation Process on AI Results(14:28) AI as a Research Assistant(16:40) The Need of Building Custom AI Model(18:50) The Huge Impact of AI in Clinical Trials(21:15) The Regulations on Applying AI Technology(23:28) AI Success Stories in the Life Science Industry(25:16) The Possibility of AGI(28:36) The Path to AGI Using LLM(30:43) Actions People Should Take in the AI Era(35:48) AI Engineers and AI-Enabled Engineers(38:37) The Viability of Vibe Coding(41:03) Hiring AI Engineers(42:26) Important Engineer Attributes in the AI Era(44:23) Important Leader Attributes in the AI Era(46:59) The Room for Juniors in the AI Era(49:04) Inspirational Story of a Successful Junior(51:33) 3 Tech Lead Wisdom_____ Patrick Leung’s BioPatrick Leung is a Chief Technology Officer at Faro Health, a company at the forefront of optimizing clinical trial development through the use of artificial intelligence. In his role, he is instrumental in applying large language models and other AI technologies to enhance protocol design and outcomes for clinical trials. A native of New Zealand, Mr. Leung holds degrees in Computer Science and Finance. His career includes being a foundational member of an early e-commerce software company, where he played a key role in guiding the company from its initial stages to a successful initial public offering. Follow Patrick: LinkedIn – linkedin.com/in/puiwahTwitter – x.com/puiwahWebsite – farohealth.com Like this episode?Show notes & transcript: techleadjournal.dev/episodes/226.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

    54 min
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Great technical leadership requires more than just great coding skills. It requires a variety of other skills that are not well-defined, and they are not something that we can fully learn in any school or book. Hear from experienced technical leaders sharing their journey and philosophy for building great technical teams and achieving technical excellence. Find out what makes them great and how to apply those lessons to your work and team.

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