Java at Spotify: Microservices, MCP & AI Overload – Mohamed Aboullaite | The Marco Show

Java at Spotify: Microservices, MCP & AI Overload – Mohamed Aboullaite | The Marco Show

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 [https://youtu.be/6WvoouJ9Mrk]

The Future of Java in the Age of AI Agents - James Ward | The Marco Show

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

The Ugly Truth About Open Source - Andres Almiray | The Marco Show

Andres Almiray, Java Champion and creator of JReleaser, joins Marco to talk about the realities of open source, release automation, and the evolving Java ecosystem. They dive into what it really takes to maintain and grow open source projects, why code isn’t the most important part, and how communication, community, and sustainability determine whether projects thrive or die. The conversation also explores release engineering challenges, why most automation setups fail, and how tools like JReleaser simplify software delivery. 💡In this episode: * Open source realities: burnout, maintenance, and sustainability * Why code is NOT the most important part of OSS * JReleaser and release automation in modern workflows * Common CI/CD and release mistakes developers make * Maven vs Gradle: trade-offs and real-world experience * The future of the Java ecosystem and tooling * AI in open source: PR spam, licensing, and quality concerns * Advice for newcomers contributing to open source Timestamps:  (00:00:00) Intro (00:00:41) Guest intro + Java journey (00:01:45) JReleaser: origin, use cases, and adoption (00:07:49) Software releases and automation best practices (00:11:31) JReleaser roadmap and release cadence (00:14:39) Commonhaus, open source sustainability, and succession (00:20:22) What makes open source projects successful (00:25:17) Burnout, community management, and prioritization (00:31:24) Hackergarten and open source collaboration (00:34:40) Motivation, Java’s evolution, and favorite features (00:40:44) Maven vs Gradle (00:44:29) CI/CD, supply chain security, and the future of Java tooling (00:53:16) AI, licensing, and open source contributions (01:01:39) Giveaway question (01:03:25) Rapid-fire round (01:06:04) Advice for getting started in open source (01:08:34) Outro New episodes every other Wednesday. Subscribe for more developer-focused conversations. 🎥 Watch the full episode on YouTube: https://www.youtube.com/watch?v=Jts62hWkRO8

How Spring Boot Really Works (From a Core Engineer) - Moritz Halbritter | The Marco Show

Moritz Halbritter, Spring Boot engineer at Broadcom and team lead for start.spring.io (Spring Initializr), joins Marco to talk about the inner workings of the Spring ecosystem and the future of Java performance. 💡 In this episode: * GraalVM Native Image vs Project Leyden and Java startup performance * Observability in Spring Boot (logs, metrics, tracing) * Developer experience improvements: Testcontainers, Docker Compose, SSL hot reload * AI coding tools, JSpecify nullability, and the future of Spring ⏱️Timecodes: (00:00) Teaser (00:53) Meet Moritz Halbretter from the Spring Boot team (02:23) From school programming to consulting to Spring (08:14) How Moritz joined the Spring team (14:20) Spring Native, GraalVM, and Project Leyden (25:35) Observability, Micrometer, and customer-driven features (32:08) Developer experience: Docker Compose, Testcontainers, SSL hot reload (40:35) JSpecify and annotating Spring Boot for nullability (45:12) start.spring.io and generating Spring projects (50:45) Using AI in coding, reviews, and open source PRs (57:30) Where Spring is headed in the next few years (1:00:08) Favorite languages, Kotlin, and Linux (1:01:13) Personal projects: solar monitoring, Modbus, and heat pump predictions (1:08:46) Giveaway and rapid-fire questions (1:11:32) Outro New episodes every other Wednesday. Subscribe for more developer-focused conversations. 🎥 Watch the full episode on YouTube: https://youtu.be/FUFsul26rgA

JobRunr: Java Job Scheduling, OSS Monetization, $17K Deals – Ronald Dehuysser

Ronald Dehuysser, creator of JobRunr, joins Marco to talk about distributed job scheduling in Java, building a high-throughput background processing framework, and turning an open-source side project into a profitable business. They dive into what really happens when microservices lack distributed tracing, why dead letter queues can silently lose invoices, how JobRunr scales to thousands of jobs per second, and what it takes to monetize open source in the Java ecosystem.  💡In this episode: * Distributed job scheduling and background processing in Java * JobRunr architecture and high-throughput performance * Quartz vs modern scheduling approaches * Retries, exponential backoff, and reliability patterns * Dead letter queues and observability challenges * Microservices vs monoliths in enterprise systems * Monetizing open source and pro licensing models * Enterprise sales and scaling a developer product * Burnout, sustainability, and building a team * AI, LLMs, and the future of junior developers ⏱️Timestamps (00:00) Teaser(00:48) Who's Ronald Dehuysser and what's JobRunr(01:37) From enterprise dev to freelancing (and switching to .NET)(11:19) Job scheduling pain and birth of JobRunr(16:21) Quitting, COVID, and building the first version(28:48) First customers and monetizing open source(40:13) Big enterprise deal and going full-time(47:16) Burnout, Vipassana, hiring, and building a team(53:20) Sustainability features and the future of JobRunr(56:08) AI, junior developers, the future of coding(01:07:28) Giveaway and Rapid-fire questions New episodes every other Wednesday. Subscribe for more developer-focused conversations. 🎥 Watch the full episode on YouTube: https://youtu.be/9Zgw_0kVFk8 [https://youtu.be/9Zgw_0kVFk8]