The Marco Show

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

Martin Odersky, creator of Scala and co-designer of Java generics, joins Marco to trace the full arc from Pizza (the 1996 functional Java experiment) to Scala 3, and on to his vision for capabilities as a safety mechanism for AI-generated code. They discuss how Scala unified object-oriented and functional programming, the Scala 2 to 3 evolution (implicits, Tasty, the new compiler), higher-kinded types, and why Martin believes programming languages need to grow up fast to keep AI agents from doing catastrophic things in production.
Topics in this episode:
The origins of Scala and the Pizza language

Java generics: design, type erasure, and the 20-year wait for pattern matching

Scala 2 vs Scala 3: what changed and why

Higher-kinded types explained accessibly

Capabilities and effect polymorphism

How capabilities can sandbox untrusted AI agents

Scala in the real world: finance, Spark, media, education

The future of programming languages in an AI-first world

Timestamps:
(00:00) Intro
(00:31) Meet Martin Odersky, creator of Scala
(03:11) Why Scala was created
(04:49) How Scala took off
(07:01) The story behind Scala’s name and logo
(08:03) Java generics and Scala’s design principles
(10:41) Haskell, functional programming, and Scala’s identity
(12:18) Pizza, Java, and features that came later
(14:28) Type erasure and higher-kinded types
(16:05) Scala 2 vs Scala 3
(18:49) TASTy and Scala 3 compiler changes
(19:21) What Martin would change about Scala
(20:25) Kotlin, Java, and JVM languages
(23:09) Capabilities, concurrency, and function coloring
(29:28) Where Scala is used today
(32:07) Scala’s ecosystem and community
(36:50) Scala, AI agents, and the future of programming
(43:17) Using AI and teaching programming in the AI era
(45:56) Scala’s future
(49:18) Why code review may be doomed
(50:24) Giveaway question
(51:26) Rapid fire questions
(54:41) Outro

New episodes every other Wednesday. Subscribe for more developer-focused conversations.
🎥 Watch the full episode on YouTube: https://youtu.be/Xn_YpUtXWT4

Mohamed Aboullaite, backend engineer at Spotify, Java Champion, Google Cloud Developer Expert, and Docker Captain, joins Marco to talk about building AI-powered integrations at scale, what software engineering looks like when you're running five AI agents in parallel, and why the foundations still matter in an AI-first world.
They discuss the engineering behind Spotify's ChatGPT integration (built on MCP), the non-determinism challenges of tool-calling, agentic coding workflows, review fatigue, and a frank conversation about the junior developer pipeline and what it takes to become senior today.
💡 In this episode:
How Spotify's ChatGPT integration works (MCP apps, the Spotify widget inside ChatGPT)

Siri/Alexa/Google Home backends and Spotify's ubiquity strategy

Non-determinism in MCP tool-calling and how Spotify works around it

Running 5 AI agents in parallel: the plan mode, review loops, cognitive fatigue

Java at Spotify: monorepo, microservices, Backstage

AI's impact on junior hiring and how to become senior anyway

Finding mentors and the power of the Java community

The token economy: measuring productivity by tokens burned

⏱️Timestamps:
(00:00) Teaser
(00:50) Meet Mohamed: Spotify backend engineer and Java Champion
(01:53) What Mohamed works on at Spotify
(03:12) Spotify inside ChatGPT and MCP apps
(06:23) Building for new AI platforms
(08:53) Spotify tools, playback, and device switching
(09:48) Tool calling challenges with AI models
(11:24) Using AI in day-to-day development
(13:29) Running multiple coding agents in parallel
(14:39) Why planning matters more than prompting
(16:56) Review fatigue and cognitive load
(19:43) Spotify’s backend, microservices, and Backstage
(21:34) Java’s evolution and the AI era
(24:14) Scala, Kotlin, Haskell, and JVM languages
(25:46) Advice for junior developers in the AI age
(29:27) How to become senior when AI solves everything
(34:09) Finding mentors and growing through community
(37:41) Giveaway question
(39:28) Rapid-fire questions: Morocco, Sweden, Spotify, AI

New episodes every other Wednesday. Subscribe for more developer-focused conversations.

🎥 Watch the full episode on YouTube: https://youtu.be/6WvoouJ9Mrk

James Ward (Developer Advocate at AWS, Agentic AI Foundation Technical Committee Member) joins Marco to map out the fast-moving landscape of AI agents on the JVM. From MCP and ACP to Spring AI, Embabel, and Ktor — James explains how the JVM ecosystem has not only caught up with Python for building agents, but may have surpassed it. He also introduces SkillsJars (putting agent skills on Maven Central), explains effect-oriented programming and why it supercharges AI coding, and shares how he's been shipping five projects in two months entirely from his phone.

💡 In This Episode
• Why the JVM is no longer second-class for AI agents
• MCP vs ACP vs A2A — when to use which
• Spring AI, Embabel (Rod Johnson), Ktor, LangChain4J compared
• GOAP planning and domain-integrated context engineering
• Agent skills vs MCP servers — and why skills are winning
• SkillsJars: versioned, composable skills on Maven Central
• Testing non-deterministic agents with evals
• Effect-oriented programming and why types matter more than ever

Timestamps: 
(00:00:00) Intro
(00:00:49) Guest intro: James Ward, AWS, and the Agentic AI Foundation
(00:01:37) Are developers now orchestrating AI agents?
(00:02:51) Agent setup, context switching, and review fatigue
(00:05:58) Why typed languages matter more in the AI era
(00:07:14) Scala vs Kotlin vs Java
(00:10:02) What agentic frameworks are and why they matter
(00:14:08) MCP explained
(00:19:42) ACP explained
(00:21:56) How to get started with agent protocols and frameworks
(00:23:43) JVM agent frameworks: Spring AI, Embabel, Koog, and LangChain4j
(00:27:50) AIforJVM.com and building projects with AI
(00:29:55) AI from your phone, dopamine, and productivity
(00:33:14) Testing, evals, orchestration, and reliability in agent systems
(00:41:03) What skills are and where they fit
(00:43:46) SkillsJars and packaging skills for the JVM
(00:49:34) Which AI standards will actually last?
(00:55:35) Effect-oriented programming explained
(01:06:37) Giveaway question
(01:08:24) Rapid-fire round
(01:10:58) Outro

New episodes every other Wednesday. Subscribe for more developer-focused conversations.
🎥 Watch the full episode on YouTube: https://youtu.be/ACP0Nx-sW10