Ep4: Where’s The Graph Data Type In Programming Languages? Breaktime Tech Talks podcast

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Ep55: Demystifying MCP + Future of Vibe Coding and RAG 13:14

לפני 13 ימים13:14

13:14

Explore the latest challenge with Neo4j vector indexes, demystify Model Context Protocol (MCP), and hear insights on vibe coding and Retrieval-Augmented Generation (RAG). What's Inside: Confusion around Neo4j vector indexes - models and dimensions Why knowing the embedding model matters for vector similarity search The limitations of current Neo4j vector index metadata What is Model Context Protocol (MCP) and why it matters for generative AI Real-world analogies for understanding MCP (microservices, snack choices, Docker containers) The power of MCP servers for secure, modular data access Article highlight: “From Gimmick to Game Changer – Vibe Coding Myths Debunked” How AI coding tools and generative AI are lowering barriers for developers and business users Risk mitigation vs. risk avoidance in adopting new technologies YouTube livestream: “RAG Was Fine, Until It Wasn’t” – lessons from Neo4j Graph Academy’s evolution The importance of focusing on goals over syntax in development Links & Resources: Neo4j vector index documentation Neo4j MCP server information From Gimmick to Game Changer – Vibe Coding Myths Debunked (article by Michael Hunger) RAG Was Fine, Until It Wasn’t (YouTube livestream) Thanks for listening! If you enjoyed this episode, please subscribe, share, and leave a review. Happy coding!…

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Ep54: Spring AI Integrations + Real-World RAG Challenges 13:10

לפני 20 ימים13:10

13:10

Hear my latest hands-on experiences and lessons learned from the world of AI, graph databases, and developer tooling. What’s Inside: The difference between sparse and dense vectors, and how Neo4j handles them in real-world scenarios. First impressions and practical tips on integrating Spring AI MCP with Neo4j’s MCP servers—including what worked, what didn’t, and how to piece together documentation from multiple sources. Working with Pinecone and Neo4j for vector RAG (Retrieval-Augmented Generation) and graph RAG, plus the challenges of mapping results back to Java entities. Reflections on the limitations of keyword search versus the power of contextual, conversational AI queries—using a book recommendation system demo. Highlights from the article “Your RAG Pipeline is Lying with Confidence—Here’s How I Gave It a Brain with Neo4j”, including strategies for smarter chunking, avoiding semantic drift, and improving retrieval accuracy. Links & Resources: Neo4j MCP Cypher server repository Spring AI MCP client Your RAG Pipeline is Lying with Confidence Jennifer’s Goodreads demo app Thanks for listening! If you enjoyed this episode, please subscribe, share, and leave a review. Happy coding!…

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Ep53: Language Models for Data Tasks + MCP Journey Begins 12:43

לפני 7 weeks12:43

12:43

In this episode of Breaktime Tech Talks, I delve into my recent experiences with Model Context Protocol (MCP) and Large Language Models, specifically Claude. First, I share my experiment using an LLM to clean up flat files. Then, my journey with MCP began integrating a Neo4j MCP server with Claude , highlighting the practical benefits and challenges faced with an anecdote on one particular incident where the LLM blended facts. It's also crucial to have clean data sets, but this is rather challenging. To round us out, I summarize an article about the recently released Neo4j data modeling MCP server and its functionality. Join me as I navigates these intriguing tech explorations and sift out the practical takeaways. 00:00 Introduction to Breaktime Tech Talks 00:48 Exploring Large Language Models for Flat File Cleanup 03:01 Diving into MCP Exploration 05:02 Challenges with Large Language Models 08:33 Data Set Challenges and Solutions 10:05 Highlight: Neo4j Data Modeling MCP Server 12:11 Conclusion and Future Directions…

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Ep52: Enhancing AI with Spring Advisors + GraphRAG Python Adventures 13:26

לפני 8 weeks13:26

13:26

In this episode of Breaktime Tech Talks, I share insights from my recent work, including a successful GraphRAG workshop and breakthroughs in utilizing Spring AI advisors for vector search and generative AI - check out code in my Github repository for QuestionAnswerAdvisor branch and custom advisors branch . I discuss my methods for integrating default and custom advisors, including coding details and implementation challenges. I also cover my exploration of Neo4j's GraphRAG Python package , highlighting its components and the learning curve. I give updates on my upcoming projects, advocacy activities, and my experience with new developer tools like Claude code. Finally, I share a great resource on everything you need to know about GraphRAG . 00:00 Introduction to Breaktime Tech Talks 00:37 GraphRAG Workshop and Python Learning 01:27 Spring AI Advisors and Custom Implementations 06:32 GraphRAG Python Package Insights 08:42 Developer Advocacy Updates 10:15 Exploring AI Tools and Learning Approaches 11:39 GraphRAG.com Resource Overview 12:53 Conclusion and Upcoming Projects…

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Ep51: Exploring AI Agents + Agentic GraphRAG in Java 8:39

לפני 11 weeks8:39

8:39

In this episode, I delve into the world of agents, discussing my experience with Spring AI tool calling. I share my approach to vector search and graph retrieval tools, address JSON deserialization, and avoid manual boilerplate - the code of which is all available in a Github repository branch . Plus, 1.0 updates to the main branch of the repository using traditional/manual GraphRAG. I wrap up with a recent content piece by Christoffer Bergman from Neo4j, which explores agentic AI frameworks with Java and Neo4j and the differences between traditional and agentic GraphRAG approaches. P.S. Don't forget to leave your feedback/suggestions for BTT in this form ! 00:00 Introduction to Breaktime Tech Talks 00:54 Exploring Spring AI Tool Calling 01:20 Understanding Agentic Frameworks 02:13 Hands-On with Vector Search and Graph Retrieval 02:36 Challenges and Solutions in Tool Functionality 04:02 Updates and Future Plans 05:01 Agentic AI with Java and Neo4j 08:06 Conclusion and Recap…

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Ep50: GraphRAG with Advisors + Spring AI Concepts 9:50

לפני 12 weeks9:50

9:50

It's the 50th episode of Breaktime Tech Talks! And to celebrate, I launched a podcast feedback form for you, my listeners. In this 50th episode, follow my latest explorations into Spring AI and GraphRAG. I delve into my attempts to streamline the manual GraphRAG process using Spring AI advisors and tools, sharing the challenges I'm facing, specifically with context parsing from one advisor to the next. I also update the Spring AI starter kit to the 1.0 GA release and recap my Neo4j developer certification livestream . To wrap up, I highlight the Spring AI documentation's AI Concepts page that beautifully blends a blog-post style with key project information.…

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Ep49: Moving toward AI Tools/Agents + Local RAG app with Quarkus 9:41

לפני 13 weeks9:41

9:41

This week, I simplified my Langchain4j project with improved prompt variable injection. Then hear my perspective on the role of tools vs. agents in AI workflows—looking at how structured processes differ from autonomous systems, especially in the context of Java frameworks and GraphRAG. Get an inside scoop on how I use different AI coding tools: IntelliJ IDEA for in-flow coding, VS Code with agent mode for problem-solving, and ChatGPT for summarizing and refining content. Lastly, hear highlights from an article on building a local RAG app with Quarkus —clear diagrams and step-by-step breakdown of ingestion vs. retrieval workflows.…

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Ep48: Java GraphRAG and Langchain4j 1.0 + Thoughts on conversational interfaces 12:08

לפני 14 weeks12:08

12:08

This week, there were quite a few things I learned: Common steps for implementing GraphRAG in Java using Spring AI and Langchain4j, highlighting key differences in setup and customization. Study prep updates and help on the Neo4j Developer Certification for June! Celebrate Langchain4j’s 1.0 release . Two thought-provoking articles—one on enhancing RAG with graphs , and another analyzing the effectiveness of voice-based interfaces . For a high-level review of steps for GraphRAG in Java, upcoming step-by-step help for prepping to take the Neo4j certification, Langchain4j GA news, and keeping up on tech content, this episode has you covered!…

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Ep47: Langchain4j GraphRAG Friction + MCP Authorization Headaches 7:38

לפני 15 weeks7:38

7:38

In this episode, I share some hands-on insights from building apps with Langchain4j using Quarkus and Neo4j , and compare it with Spring AI—especially around how each framework handles vector search and GraphRAG workflows. Spoiler: customization in Langchain4j feels a bit clunky. I also dig into one article's critical take on the MCP authorization spec and why its current approach to security is misaligned with how enterprises actually structure identity and access. The article I discuss breaks down both the architectural intentions and the practical enterprise concerns—token handling, overhead, and developer friction. If you’re working at the intersection of GenAI infrastructure and enterprise systems, this one’s for you.…

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Ep46: Quarkus Neo4j Application + Development Lessons Learned 9:21

לפני 16 weeks9:21

9:21

In this episode, we dive into the Quarkus framework with a code repository and an article about development lessons learned. Topics covered include: 🔗 Building a starter application with Quarkus Neo4j and the Object Graph Mapper (OGM). 📝 Exploring similarities and differences between Quarkus and Spring frameworks. 📑 Resources for building with Quarkus and Neo4j - blog post and documentation . 📚 Key takeaways from an article on developer philosophy , touching on code rewrites, estimation challenges, and the importance of automation and edge cases. Whether just curious or writing code, we all learn and face similar development challenges!…

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Ep45: Exploring Java Frameworks + Launch of Spring AI 1.0 10:03

לפני 17 weeks10:03

10:03

In this episode, I have some exciting technical updates, along with insights from my recent work and learning. Topics covered include: 📝 Neo4j Java Driver & Object Mapping – My latest blog post and upcoming updates to the GraphAcademy Java courses. 🧪 Framework-less Java Apps – Experiments in building Java applications without a framework and comparing with tools like Spring and others. 🔧 Code Refactoring Strategy – Lessons learned on managing updates in stages for cleaner version control and project maintenance. 🤖 Spring AI 1.0 Release – Highlights from the official launch , including an AWS blog post on architecture insights, real-world examples, and key resources for getting started with AI in Java. Whether you're deep into Java development or just exploring the intersection of frameworks and AI, there's something here for you!…

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Ep44: Updates in Java tools + MCP and Security 10:58

לפני 18 weeks10:58

10:58

In this episode, we dive into three key updates from the world of Java development and emerging tech standards: First, walk through a new feature in the Neo4j Java driver (v5.28.5) that enables lightweight object mapping. I’ve set up a sample code repository showcasing how to return Cypher query results directly into your Java domain objects—no full-blown OGM needed. It’s a big improvement, but with a few gotchas you’ll want to understand. Next, we take a look at Jackson Jr , a lightweight version of the popular Jackson library . If you're working in resource-constrained environments or want faster startup times, this stripped-down data processor might be just what your project needs. Finally, we revisit Model Context Protocol (MCP) security, following up on concerns raised in Episode 42. I share two recent articles that highlight current security limitations in MCP and practical tips for developers looking to build safely with it today, even before full support matures. Whether you're optimizing your Java stack or exploring AI protocols, there’s something in this episode for you.…

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Ep43: MCP Java SDK + Naive RAG vs GraphRAG 11:18

לפני 19 weeks11:18

11:18

In this episode, we dive into the latest upgrades in Neo4j tooling, along with recent bug fixes and enhancements in the LLM Knowledge Graph Builder . We also explore a new preview feature for Java object mapping in the Neo4j Java driver and check out the MCP Java SDK . Next, we highlight the new " Using Neo4j with Java " course on GraphAcademy and unpack a compelling Weaviate article on RAG vs. GraphRAG , featuring Microsoft’s GraphRAG methodology. Whether you're a Java dev, graph enthusiast, or AI-curious, there's something in here for you!…

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Ep42: RAG and Java + AI-generated content and MCP 12:33

לפני 20 weeks12:33

12:33

Star Wars Day is nearly here, and this episode is stacked with tech goodness to celebrate! I’m diving into highlights from the Neo4j ecosystem, starting with an early look at the Using Neo4j with Java course —perfect for getting started with the Java driver in a framework-less setup. Also in this episode: ⚙️ Behind-the-scenes of APOC + Pinecone integration ✨ Part 2 of my Intro to Retrieval Augmented Generation series 🎥 My recent guest spot on Neo4j Live , discussing the Developer’s Guide to Building a Knowledge Graph 🤖 A fascinating series on an AI content experiment from Mark Heckler 📚 Michael Hunger’s must-read blog on the Model Context Protocol (MCP) May the Fourth be with you!…

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Ep41: Spring AI M7, NODES, RAG + Neo4j, Quarkus, and Intelligent Apps 11:46

לפני 21 weeks11:46

11:46

In this episode, we unpack a busy week of updates, learning, and cool tech! From Spring AI’s milestone 7 release with simplified Pinecone configuration to some tricky wifi, I walk through recent changes and adventures. Plus, NODES 2025 is officially announced , and there’s hints of our upcoming GraphAcademy Java course. I also talk about the first part of my new blog series on Retrieval Augmented Generation and highlight a fantastic article on Neo4j, Quarkus, and intelligent applications .…

Breaktime Tech Talks

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Ep40: Recent AI learnings + More than a vector database 10:24

לפני 23 weeks10:24

10:24

Fresh from the Arc of AI conference , I’m unpacking the biggest insights that stuck with me—ranging from the extremes of AI’s capabilities to the deeper implications for how we build and maintain our tech systems. I’ll also share a new blog post and code repo I published on loading data into Pinecone, some next-gen tools I’m eyeing, and thoughts on a great article from the Redis blog about why vector databases aren’t enough . Navigate the evolving landscape of LLMs, generative AI, and modern infrastructure with me in this episode.…

Breaktime Tech Talks

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Ep39: Why embedding models should match + Advice for starting a blog 13:36

לפני 24 weeks13:36

13:36

In this podcast episode, hear about my hands-on experience ( code repository on Github ) understanding the importance of using the same embedding models for both creating and searching vector embeddings in databases and how mismatched models can lead to poor search results. I also pull highlights from an article with advice for those interested in blogging , and how it particularly relates to my own approach to tech blogging.…

Breaktime Tech Talks

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Ep38: Spring AI Debugging + How to Contribute to Open Source 13:25

לפני 26 weeks13:25

13:25

In this episode, I continue my journey with vector databases, integrating Pinecone , Neo4j , and Spring AI . While making some progress, I also encountered hurdles, such as evolving APIs and the unique architecture of vector stores. Next, I share insights from an article on contributing to open-source projects , how it can accelerate your career and enhance both your technical and soft skills. From picking the right project to building credibility within the community, it's a series of steps that gets better with time and practice!…

Breaktime Tech Talks

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Ep37: Vector Database Frustration + Microsoft LazyGraphRAG 12:22

לפני 27 weeks12:22

12:22

In this episode, I discuss my challenges exploring vector databases for an upcoming demo. From what is a vector database to integration issues, hear how I tried a few different approaches with limited success and discover the surprising one with the most promise. I also explore Microsoft's "Lazy Graph RAG" approach, which seems to trade one challenge for another but could be valuable in certain cases.…

Breaktime Tech Talks

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Ep36: What is a Developer Advocate + Balancing Digital Consumption 11:27

לפני 29 weeks11:27

11:27

This week, I explored the Javalin Java framework and project decisions I'm trying to make. I also answer: What exactly does a Developer Advocate/Evangelist/Devrel do? Finally, I reflect on an article on balancing digital consumption with actual productivity.

Breaktime Tech Talks

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Ep35: Vector Databases + Building Effective Agents 8:53

לפני 30 weeks8:53

8:53

In this episode, there are two topics I'm looking forward to diving deeper into: vector databases and AI agents. I'm particularly interested in understanding how vector databases work, how they work with data, and their role in AI applications. Then I share my thoughts on Anthropic’s article about Building AI Agents , which discusses their varying definitions—from simple workflows to fully autonomous systems—and provides practical examples. The article highlights the importance of starting simple, adding complexity only as needed.…

Breaktime Tech Talks

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Ep34: Outlines and Iterating + Lessons from Grace Hopper 13:21

לפני 31 weeks13:21

13:21

In this podcast episode, hear my process of preparing for an upcoming conference with insights on how outlines enhance presentations and blog posts, as well as code and architecture. Also discuss how constant improvement is key with an online course as an example. Finally, I highlight a historical read on cryptography , and share reflections from Grace Hopper's 1982 lecture on data, hardware, and software , drawing connections between her insights and modern challenges in technology.…

Breaktime Tech Talks

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Ep33: Cypher DSL examples + Crowd-source AI hacking 8:58

לפני 32 weeks8:58

8:58

In this episode, I share recent blog posts. The first is about tackling challenges with GitHub repositories , offering solutions on syncing forks and using git rebasing, diffs, and pruning. Next, I created examples with Cypher DSL , providing beginner-friendly details to help users get started. Additionally, I started prepping for the Devnexus conference , where I'll be delivering my first keynote. I also read an article about an intriguing AI testing project where a user successfully manipulated an AI to break its rules and win a $50,000 prize, illustrating the potential challenges AI systems face in handling sensitive tasks.…

Breaktime Tech Talks

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Ep32: Official CLI + Bread Code Framework 10:32

לפני 33 weeks10:32

10:32

In this episode, I’m following up on a few things I’ve mentioned before. I dive into some updates on the Aura CLI (the official product version). I also explored the Neo4j GenAI Java library a bit more, including a connection hiccup I ran into with Neo4j Desktop. Then, I get into my experience with the Cypher DSL library and how Cypher fits into the retrieval part of RAG systems. Finally, I take a fun detour into an interesting article about a GitHub repository that combines coding and sourdough baking . It’s a cool reminder that the skills we learn in coding can apply to all sorts of other areas, even in the kitchen!…

Breaktime Tech Talks

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Ep31: Database CLI + Containerization Refcard 9:31

לפני 34 weeks9:31

9:31

In this episode, hear updates on a few projects, including Neo4j's new Aura CLI and NeoConverse . Plus, the promised blog post from last week's episode on Spring Data Neo4j entity updates . Shout-out to the JAXJUG and TampaJUG groups. If you're not involved with a tech group, there are options! Finally, a review of the DZone RefCard on Java containerization with its clear guidance on Docker containers, native builds, and deployment, making complex concepts more accessible for developers.…

Breaktime Tech Talks

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Ep30: SDN update entity + Knowledge Graph ebook 9:06

לפני 35 weeks9:06

9:06

Dive into my latest experiences with Spring Data Neo4j, specifically exploring new methods for updating nodes. After revisiting my 2023 blog post on this topic, I share insights on custom Cypher queries and projections . I also discuss the challenges of finding good examples for update operations. In addition, Neo4j announced the release of The Developer's Guide: How to Build a Knowledge Graph , a new ebook I co-authored. Hear my challenges of writing the book, including finding the right dataset for graph queries, working through product updates during the writing process, and the complexities of collaborating across different perspectives. Stay tuned for future updates, as we continue to refine this ever-evolving resource.…

Breaktime Tech Talks

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Ep29: Neo4j GenAI plugin + How-To for Technical Content 10:16

לפני 36 weeks10:16

10:16

In this episode, dive into a few exciting areas I've been exploring, including generative AI and graph technologies. I worked with Neo4j’s generative AI plugin for an experiment, and it wasn't all smooth sailing. Next, my highlights from an article in the Descript community on how to expand your educational YouTube audience —especially applied for those creating technical content. Key tips include thinking like a viewer to ask great questions, tweaking video intros to keep people engaged, and channeling viewer interests to strengthen connections.…

Breaktime Tech Talks

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Ep28: 2024 Recap, 2025 Look-Ahead + Always Be Launching 12:32

לפני 38 weeks12:32

12:32

Take a moment to reflect on 2024, exploring highlights in AI advancements, personal growth, and professional achievements, along with exciting 2025 goals. Then delve into an article that discusses marketing strategies but aligns well with developer advocacy.

Breaktime Tech Talks

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Ep27: Lexical vs Semantic Search + Downside of Vector Databases 8:54

לפני 39 weeks8:54

8:54

Explore the distinction between lexical and semantic search technologies, the growing use of vector databases , and the potential challenges and solutions that may arise as these technologies mature.

Breaktime Tech Talks

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Ep26: Git Troubles + Dungeons & Dragons Graph 11:43

לפני 41 weeks11:43

11:43

Git issues, finally resetting local branch , cherry-picking , and cleaning up . Then a fun graph presentation - Dungeons, Dragons, and Graph Databases .

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Breaktime Tech Talks « » Ep4: Where’s the Graph Data Type in Programming Languages?

Ep4: Where’s the Graph Data Type in Programming Languages?

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Ep4: Where’s the Graph Data Type in Programming Languages?