Tech Lead Journal

• #235 - From AI Chaos to Clarity: Building Situational Awareness with Wardley Mapping - Simon Wardley

  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:Why leading with stories instead of maps creates fake CEOsThe critical difference between graphs and maps in business strategyWhat Wardley mapping is and the three pattern types leaders must understandHow to identify where human decision-making adds value in your AI adoptionWhy vibe coding is powerful but dangerous without proper code reviewsWhy software development is still a craft, not engineeringHow Jevons Paradox means AI won’t eliminate jobs but expand codebasesThe hidden dangers of AI hallucinations and the need for critical thinkingTimestamps:(00:00:00) Trailer & Intro(00:02:59) Career Turning Points(00:06:45) Importance of Understanding Landscape for Leaders(00:10:42) The Problem of Leading with Stories(00:12:49) Wardley Maps vs Other Types of Business Maps/Analysis(00:17:32) Wardley Map Overview(00:23:54) Why Mapping is Not a Common Industry Practice(00:26:23) Climatic Patterns, Doctrines, and Gameplay(00:30:51) Understanding Disruption by Using a Map(00:33:17) Navigating the Recent AI Disruption(00:39:37) A Leader’s Guide to Adopting AI(00:42:49) Turning Coding From a Craft Into Engineering(00:48:05) Simon’s AI & Vibe Coding Experiments(00:55:28) The Importance of Critical Thinking for Software Engineers(01:03:49) Navigating Career Anxiety Due to AI Fear(01:08:56) Tech Lead Wisdom_____Simon Wardley’s BioSimon 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 – linkedin.com/in/simonwardleyTwitter – x.com/swardleyWebsite – www.swardleymaps.comLike this episode?Show notes & transcript: techleadjournal.dev/episodes/235.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

  --------  

  1:10:52

  --------

  1:10:52
• #234 - Building for Reliability: Durable Execution & Insights from Temporal's Report - Preeti Somal

  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:Lessons from operating large-scale systems at Yahoo and HashiCorpWhy reliability ranks higher than cost for most engineering teamsHow durable execution removes reliability complexity from developer concernsWhy unlearning old patterns proves harder than learning Temporal’s modelCreating a strong incident response culture through blameless post-mortemNurturing psychological safety in infrastructure teams and on-call engineersBuilding security and compliance from day one versus retrofitting laterTimestamps:(00:00) Trailer & Intro(02:20) Career Turning Points(04:43) Key Learnings from Operating Large Scale Infrastructure(07:56) Key Learnings on Platform Engineering(09:59) Key Learnings on Maintaining High Reliability(12:02) Key Highlights Working at HashiCorp(13:52) Running Infra as Code using Temporal(15:28) Key Principles for Managing a Strong Incident Response(18:37) The Importance of Nurturing Psychological Safety within Infra Team(21:13) The Temporal’s State of Development Report(22:39) The State of AI Usage & Adoption(23:54) Using Temporal for Building AI Applications(26:06) The Complexities Involved in Building AI Applications(28:51) Key Learnings from Temporal’s State of Development Report(31:03) The Choice of Developer Tooling Misalignment(33:12) Integrating Security, Compliance, and Cost into Your Engineering Mindset(33:39) Building with Security and Compliance-First Mindset(36:57) Temporal Paradigm Shift(39:14) How Temporal Hides Away The Complexities of Building Reliable Applications(42:47) Unlearning Required for Using Temporal Programming Model(46:33) Getting Started Building with Temporal(48:34) Temporal’s Durable Execution Guarantee(51:23) The Concern About Temporal Lock-In(54:09) Temporal’s Strong Developer Focus(56:16) The Compliance and Security Aspect of Temporal Cloud(58:41) 3 Tech Lead Wisdom_____Preeti Somal’s BioPreeti 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 – linkedin.com/in/preeti-somal-131890Twitter – x.com/psomal📖 Temporal’s State of Development Report 2025 – temporal.io/pages/state-of-development-2025Like this episode?Show notes & transcript: techleadjournal.dev/episodes/234.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

  --------  

  1:02:11

  --------

  1:02:11
• #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-metricsLike this episode?Show notes & transcript: techleadjournal.dev/episodes/233.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

  --------  

  1:07:01

  --------

  1:07:01
• #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 BioGavin 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.orgLike this episode?Show notes & transcript: techleadjournal.dev/episodes/232.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

  --------  

  1:35:21

  --------

  1:35:21
• #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 – [email protected] – graphite.devGraphite X – x.com/withgraphiteLike this episode?Show notes & transcript: techleadjournal.dev/episodes/231.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

  --------  

  1:00:57

  --------

  1:00:57

More Technology podcasts

Trending Technology podcasts

About Tech Lead Journal