Best Neo4j Podcasts (2025)

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Ep60: Langchain4j & Neo4j Integration Breakthroughs + The Decade of Agents in AI 13:02

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2d ago13:02

13:02

Welcome to Breaktime Tech Talks! In this episode, dive into the latest updates and challenges in the world of developer tools, AI, and graph databases. Episode Highlights: Overcoming technical hurdles with Langchain4j and Neo4j, including the new support for read-only Neo4j databases in vector indexing (Github feature pull request). Navigating vers…

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Ep59: NODES 2025 Highlights + Solving Graph Problems with Cypher 25 11:02

16d ago11:02

11:02

In this episode: Recap of NODES 2025 and standout sessions How AI and music graphs are shaping new tech (featuring Luanne Misquitta’s talk) Exploring RushDB: open source tools for graph data Developer advocacy in the classroom: inspiring the next generation Updates on Spring AI, Langchain4j, and upcoming workshops Blog post on new Aura Fundamentals…

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Ep58: Hybrid Search Headaches + GraphRAG as MCP Server 10:30

1M ago10:30

10:30

In this episode of Breaktime Tech Talks, dive into the real-world challenges and discoveries from my recent work with Langchain4j, Quarkus, and Neo4j. If you’re a developer navigating the evolving landscape of AI, vector search, and graph databases, this episode is packed with practical insights and lessons learned. Highlights: Struggles with confi…

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Ep57: Developer Advocacy Realities + Conditional Logic in Cypher 12:22

2M ago12:22

12:22

In this episode of Breaktime Tech Talks, I share an inside look into developer advocacy, discuss the highs and lows of the role, and review new features in the Cypher query language. Highlights: 🔎What it’s really like to be a developer advocate: the good, the bad, and the “meh” 🧗🏼‍♀️Common challenges: overwhelm, travel fatigue, balancing diverse re…

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Ep56: Java and Langchain4j Releases + GraphRAG with Langchain4j 10:53

2M ago10:53

10:53

In this episode of Breaktime Tech Talks, we focus on frameworks, libraries, and integrations that streamline workflows and enable more powerful applications. Key Technical Topics Covered: Releases! Java 25 and Langchain4j 1.5 Spring Initializr Java version default from 17 to 21 New blog post! Spring AI with MCP text-to-cypher Generating Ollama embe…

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

3M ago13:14

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 …

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

3M ago13:10

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, wh…

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

4M ago12:43

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…

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

4M ago13:26

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 defau…

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

5M ago8:39

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…

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

5M ago9:50

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, specific…

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

5M ago9:41

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: In…

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

5M ago12:08

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 R…

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

6M ago7:38

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 s…

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

6M ago9:21

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 Quar…

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

6M ago10:03

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 compar…

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

6M ago10:58

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 ful…

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

7M ago11:18

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 unpa…

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

7M ago12:33

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 inte…

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

7M ago11:46

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 p…

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

8M ago10:24

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 …

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

8M ago13:36

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 bl…

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

8M ago13:25

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 en…

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Ep37: Vector Database Frustration + Microsoft LazyGraphRAG 12:22

8M ago12:22

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 challen…

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

9M ago11:27

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.By jmhreif

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Ep35: Vector Databases + Building Effective Agents 8:53

9M ago8:53

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 d…

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

9M ago13:21

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 Gr…

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

10M ago8:58

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 confer…

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Ep32: Official CLI + Bread Code Framework 10:32

10M ago10:32

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 th…

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Ep31: Database CLI + Containerization Refcard 9:31

10M ago9:31

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 container…

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

10M ago9:06

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 Deve…

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

11M ago10:16

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 t…

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2024 Recap: Favorite highlights! 49:36

11M ago49:36

49:36

Topics: Trends/Events over the year GQL release https://neo4j.com/blog/cypher-gql-world/ GraphRAG https://neo4j.com/blog/graphrag-manifesto/ Memorable events/experiences NODES 2024, obviously :) https://neo4j.com/nodes2024/agenda/ GenAI Graph Gathering AI Eng World Fair Neo4j product releases? New Aura console LLM KG Builder https://neo4j.com/labs/…

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

11M ago12:32

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.By jmhreif

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

11M ago8:54

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.By jmhreif

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

12M ago11:43

11:43

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

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NODES 2024 Recap 40:01

12M ago40:01

40:01

Speaker Resources: NODES 2024 YouTube playlist: https://www.youtube.com/playlist?list=PL9Hl4pk2FsvU6t-fXNeQfkpnmgMm4w5h3 NODES 2024 agenda webpage: https://neo4j.com/nodes2024/agenda/ Highlighted sessions: Building a Perfect Supply Chain Chatbot: https://www.youtube.com/watch?v=ksbfgGYQy5M&list=PL9Hl4pk2FsvU6t-fXNeQfkpnmgMm4w5h3&index=27 Fireside C…

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Ep25: Github Actions + AI Coding Assistant 8:56

12M ago8:56

8:56

In this episode, hear some positive tech experiences from the week: the upgrade from GitHub Actions (upload/download artifact) to v4 through a 3rd party repo, and the new AI coding assistant feature in IntelliJ IDEA.By jmhreif

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Ep24: Graph Data Science + Building Knowledge Graphs 9:57

1y ago9:57

9:57

This episode, my refresher with the Graph Data Science library with highlights and challenges. Then an overview of the Building Knowledge Graphs book, a guide on everything from concepts to technical details.By jmhreif

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Ep23: Spring Data Neo4j course + Event recap 14:58

1y ago14:58

14:58

Hear learnings from the new Spring Data Neo4j course - building blocks, updates/deletes, and modeling. Then recap XtremeJ and NODES 2024, + upcoming at CJUG.By jmhreif

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Ep22: LLM Graph Builder + Devrel unlocks “aha” moment 11:12

1y ago11:12

11:12

In this episode, get my latest experiences with the Neo4j LLM Graph Builder, both the benefits and challenges. Then, an article focusing on the concept of the "Aha moment"—a key moment when developers discover the value of a technology.By jmhreif

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Ep21: Data is cool + NODES 2024 preview 9:32

1y ago9:32

9:32

In this episode, hear why data (a less glamorous topic) is actually fascinating and crucial. Then, look forward with a preview of next week's NODES 2024 event, which features a range of sessions on graph technologies, AI, data science, and security. Finally, get a teaser for the next episode.By jmhreif

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Catching Bad Guys using Graph Entity Resolution with Paco Nathan 46:31

1y ago46:31

46:31

Speaker Resources: Neo4j+Senzing Tutorial: https://neo4j.com/developer-blog/entity-resolved-knowledge-graphs/#neo4j When GraphRAG Goes Bad: A Study in Why you Cannot Afford to Ignore Entity Resolution (Dr. Clair Sullivan): https://www.linkedin.com/pulse/when-graphrag-goesbad-study-why-you-cannot-afford-ignore-sullivan-7ymnc/ Paco’s NODES 2024 sessi…

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Ep20: What is a graph + Goodhart’s Law 8:24

1y ago8:24

8:24

Cover the basics of graphs, explaining mathematical roots and applications. Introduce Goodhart's Law and highlight the risks of over-focusing on metrics, whether in tech or personal growth.By jmhreif

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Ep19: RAG vs Agents + Naming Things 10:21

1y ago10:21

10:21

Explore agents in AI, distinguishing them from RAG (article1, article2). And discuss naming and the importance of conveying relevance and clarity.By jmhreif

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Ep18: What is Vector search + JConf/Dev2next experiences 10:59

1y ago10:59

10:59

Want to take our previous vector topic a step further with vector similarity search. Then, I’ll give my thoughts on 2 recent tech conferences - JConf and dev2next.By jmhreif

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Ep17: Using Asciidoc for Tech Content + Current Productivity Reads 10:19

1y ago10:19

10:19

The Asciidoc markup language is powerful and useful for developers and technical writing. Also highlighting productivity books - Atomic Habits and Deep Work - and applications for a developer.By jmhreif

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Graph Visualization and Storytelling with Michela Ledwidge 50:19

1y ago50:19

50:19

Speaker Resources: Mod: https://mod.studio/rd/grapho/ Michela's NODES 2024 session: https://neo4j.com/nodes2024/agenda/spatial-graph-visualisation-and-storytelling-with-grapho-xr/ NeoDash: https://neo4j.com/labs/neodash/ Tools of the Month: Google Notebook LM: https://notebooklm.google/ HeyGen (AI Digital Avatar): https://www.heygen.com IntelliJ ID…

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Ep16: Mapping Relationships in Applications + Software Estimates 10:23

1y ago10:23

10:23

Documenting how to map relationship entities from a database to an application. Then, delving into one author’s viewpoint on software project estimates and some ideas to adapt this inaccurate process for better results.By jmhreif

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Ep15: What is GraphRAG + Developing Better Software 11:36

1y ago11:36

11:36

The term GraphRAG has recently popped up in the current AI industry, so I review a blog post on what it is and how it fits into the current landscape. I also read an article on ways to improve software development.By jmhreif