The Marco Show

Michael Simons, a longtime Java developer and Neo4j engineer, joins Marco to talk about the engineering principles that have stayed relevant across decades of changing technologies. The conversation covers database-first thinking, Spring and the Java ecosystem, graph databases, developer tooling, and why pragmatic decisions often matter more than chasing the “best” framework. They also discuss how AI is changing software development, where AI tools genuinely help, and why human judgment and responsibility still matter.
💡 In this episode:
Why Michael still starts with the data model when building applications

Why too many tooling choices can lead to “death by tooling”

How Spring Boot changed the Java ecosystem

How Neo4j and graph databases help solve highly connected data problems

Where AI tools help developers and where traditional approaches still work better

Timestamps:
(00:00) Teaser
(00:31) Introduction
(02:42) Michael’s database-first background
(04:18) Why data outlives applications
(07:38) Are developers underusing their databases?
(09:53) Vendor lock-in: Is it really such a bad thing?
(10:57) JPA, jOOQ, Spring Data, and choosing database tools
(15:02) From Oracle to Java and Spring
(18:21) How Spring Boot changed the industry
(20:00) Tool wars and “death by tooling”
(23:20) Blogging, community building, and public speaking
(29:58) From blog posts to international conferences
(32:14) Writing technical books
(38:09) Can LLMs replace human editors?
(40:26) “I’m a product person, not a project person”
(41:28) How Michael joined Neo4j
(47:45) Graph databases, fraud detection, and LLMs
(48:55) What Michael is building at Neo4j
(57:43) The future of Java and AI-generated contributions
(59:19) AI-generated pull requests and maintainers
(01:01:34) How Michael actually uses AI tools
(01:03:46) Static code analysis vs. LLMs
(01:05:22) Why Michael doesn’t want AI doing the planning
(01:06:27) Giveaway
(01:07:34) Rapid-fire questions
(01:09:42) Outro
New episodes every other Wednesday. Subscribe for more developer-focused conversations.
🎥 Watch the full episode on YouTube: https://youtu.be/Leo8A1FjY1o

Venkat Subramaniam joins Marco to talk about what AI is really changing for developers. They discuss why AI often impresses novices more than experts, why “AI first” is the wrong mindset, and why critical thinking, fundamentals, and judgment matter more than ever.
💡 In this episode:
Why AI is better at finding problems than writing code

Why AI needs more skilled developers, not fewer

Why “AI is second”

The danger of bad AI metrics and token maxing

Why critical thinking still matters

What excites Venkat about the future of Java and virtual threads

Timestamps:
(00:00) Teaser
(00:40) Introduction
(01:12) What is different about AI?
(03:26) Why AI is better at finding problems than writing code
(04:50) Should AI implement an entire feature?
(09:15) How junior developers can become experts in the AI era
(12:46) Speed vs. sustainable software development
(14:11) Timeboxing and learning to verify solutions
(18:18) Why AI should come second
(21:19) Why developers and AI are better together
(24:22) Token maxing and failed AI adoption strategies
(26:43) Why powerful tools require more skill
(29:28) Programmer productivity vs. business agility
(31:03) What CTOs should do about AI
(33:35) Threat-driven development and forced AI adoption
(36:06) How Venkat learns new technologies
(41:44) How Venkat prepares talks and keynotes
(44:50) Why Venkat does not rehearse his talks
(47:00) Stage fright after thousands of presentations
(49:16) When Venkat’s laptop died before a live coding keynote
(53:53) What keeps Venkat learning and creating?
(54:21) From a failing student to earning a PhD
(56:00) “I hate studying, but I love learning”
(01:00:19) Why grades can destroy the joy of learning
(01:04:54) How Java has changed over the last decade
(01:05:29) Why Java 8 was the game changer
(01:09:13) Java’s release cycle and true agility
(01:11:29) Virtual threads and asynchronous programming
(01:15:47) What makes Java’s innovation different
(01:16:56) What is next for Java?
(01:19:25) Generics with value types
(01:20:30) Giveaway question
(01:21:53) Rapid-fire questions
(01:23:33) Outro
New episodes every other Wednesday. Subscribe for more developer-focused conversations.
🎥 Watch the full episode on YouTube: https://youtu.be/_590TxMwvWM

Sébastien Deleuze, a longtime Spring Framework committer and member of the Spring AI team, joins Marco to talk about how 13 years on the Spring team shaped his pragmatic approach to software development. The conversation covers how Spring AI fits into the Spring ecosystem, why enterprise AI still needs deterministic workflows and human accountability, and why long-term software quality matters even as GenAI changes how code gets written.
💡 In this episode:
How Sébastien joined the Spring team through open source contributions

Why he only introduces features he once wished Spring had as a developer

How Spring AI brings AI services into the familiar Spring programming model

Why AI helps with speed, but not with the most important decisions

Why accountability and sustainable engineering still matter in the age of GenAI

Timestamps:
(00:00) Teaser
(00:32) Introduction
(00:54) Sébastien Deleuze’s 13 years on the Spring team
(01:22) How an open-source contribution led to joining Spring
(03:08) Working on a fully remote team
(03:54) Building the Spring features he wished he had as a developer
(05:22) Why Kotlin was the right fit for Spring
(06:35) How the Spring team discovers what developers need
(08:23) Learning from competing frameworks without copying them
(11:06) What is Spring AI?
(13:27) Bringing AI into enterprise applications 
(14:53) AI-generated pull requests and the accountability problem
(16:36) How open-source maintainers deal with low-quality AI contributions
(18:27) Keeping up with the speed of change in AI
(20:43) Using AI tools for most coding tasks
(21:21) Writing better prompts by providing the right context
(24:05) Running multiple AI agents and managing context switching
(24:53) Can an AI agent fix a complex Spring issue?
(25:38) Why detailed issues and commit messages matter more in the AI era
(27:22) What’s next for Spring AI 2.0 and 2.1
(29:44) Spring AI’s relationship with Embabel and the wider ecosystem
(30:56) Why Spring AI is reducing its scope
(32:05) The most important engineering skill AI cannot replace
(33:29) Using AI outside of work
(38:10) Giveaway
(39:04) Rapid-fire questions
(40:13) Outro
New episodes every other Wednesday. Subscribe for more developer-focused conversations.
🎥 Watch the full episode on YouTube: https://www.youtube.com/watch?v=mCOGZGV48hU

Josh Long, Spring Developer Advocate at Broadcom, joins Marco to cover 25 years of Spring history and what the JVM's real shot at the AI era actually looks like. Josh has published a weekly blog since 2011 and a weekly podcast since 2018 without missing an episode. This conversation gets into why vibe coding concerns him as an engineer, what accountability for AI-generated code actually means, and why Python's dominance in AI is more a marketing gap than a technical one.
💡 In this episode:
Spring's origin story: why the documentation came before the code

How Spring Boot changed what a developer talk could look like

The hidden cost of vibe coding: context, accountability, and integration

Why 95% of generative AI projects fail — and what the 5% have in common

Project Valhalla, Project Panama, and the Vector API

Why Java could have built Kubernetes, and what that means for AI

Timestamps:
(00:00) Teaser
(00:37) Introduction
(01:02) Josh's journey before joining the Spring team
(03:06) Becoming Spring's first Developer Advocate
(05:47) What a Spring Developer Advocate actually did
(08:41) How Spring Boot changed Java forever
(12:32) Building a career around talks, blogs, and community
(15:32) Writing a weekly blog for 15+ years without missing one
(19:14) Stage fright and speaking at hundreds of conferences
(20:07) Live coding, talk preparation, and presentation failures
(26:33) How DevRel changed after COVID
(29:08) Why live coding beats slides
(31:46) Advice for aspiring Developer Advocates
(33:12) AI coding agents, vibe coding, and why more code isn't better
(39:27) How AI changed search and everyday work
(40:17) The future of Java, Spring, and AI
(46:48) Giveaway
(47:32) Rapid-fire questions
(49:36) Outro

New episodes every other Wednesday. Subscribe for more developer-focused conversations.
🎥 Watch the full episode on YouTube: https://youtu.be/_ftzJ33mCTI

Martin Lippert, longtime maintainer of Spring Tools and one of the people who has witnessed developer tooling evolve from Eclipse to VS Code, joins Marco to discuss how AI is transforming Java development, and what that means for the future of software engineering.
⏱️ Timestamps:
(00:00) Teaser(00:38) Meet Martin Lippert, Spring Tools & the evolution of Java IDEs(03:28) What happened to Eclipse? Lessons from the rise and fall of a Java giant(12:20) Why Spring Tools moved to VS Code and embraced the Language Server Protocol(20:03) How AI is changing Java development and everyday coding workflows(21:59) Martin's AI workflow: Cursor, IDEs, code review & testing(26:16) Building developer tools for AI agents instead of humans(31:10) Why AI is changing release cycles and developer tooling(36:03) AI review fatigue, cognitive depth & trusting generated code(39:06) Will AI replace senior developers? What happens to junior engineers?(42:16) The future of Java, Spring & software architecture in an AI-first world(48:42) AI's hidden energy problem and the sustainability challenge(54:39) Practical tips for greener software engineering and AI usage(1:00:06) Giveaway & rapid-fire questions

💡 In this episode:
How AI is changing Java development and developer workflows

Why IDEs still matter alongside coding agents like Cursor

Building developer tools for AI instead of humans

AI review fatigue and the importance of writing code yourself

Will AI replace senior developers?

Why software architecture still matters in an AI-first world

The evolution of Java tooling: Eclipse, VS Code, Language Server Protocol, and beyond

The future of Java and Spring in the age of AI

AI's hidden environmental cost and the rise of Green Software Engineering

New episodes every other Wednesday. Subscribe for more conversations with the people shaping the future of software development.
🎥 Watch the full episode on YouTube: https://youtu.be/gUm6DOf1NHI