Breaktime Tech Talks

Breaktime Tech Talks

A bite-sized tech podcast for busy developers where we’ll briefly cover technical topics, new snippets, and more in short time blocks. Your host, Jennifer Reif, is an avid developer and problem-solver with special interest in data, learning, and all things technology.

Episodes

May 30, 2025 9 mins
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 f...
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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 –...

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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 ...

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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 ...

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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:

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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...

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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. Navigat...

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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.

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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...

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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.

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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.

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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 e...

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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 betwee...

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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 int...

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January 31, 2025 10 mins

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 art...

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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, ...

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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 cha...

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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...

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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.

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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.

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