Breaktime Tech Talks

Ep65: RAG Filtering + Context Graphs with Neo4j

This week has been a whirlwind. From starting a new RAG project to getting involved in other community events, there is so much to learn and do. This week had the following highlights:
🎤 Glasgow Meetup Adventures Navigating venue challenges, DJ booth speaking setups, and live coding without a mic stand—lessons in developer advocacy resilience.
🔍 RAG Experimentation Working with Quarkus to ingest unstructured data into Neo4j. Exploring filtering strategies and data model alignment for better retrieval.
💡 Live Interaction Tracer Combining naive RAG with a graph-based interaction tracer—early progress on a promising approach.
🧠 Context Graphs Deep Dive Why context graphs matter for AI: documenting the "how" and "why" behind data decisions, not just snapshots in time. Perfect for providing business logic and tacit knowledge to AI systems.
Resources
Hands-on with Context Graphs and Neo4j by William Lyon
William Lyon's podcast episode (previous month)
Context Graphs demo application
Lots of 2026 projects kicking off—stay tuned for updates on RAG experiments, context graph implementations, and upcoming events!

Ep64: Neo4j Vector Migration + Learning in the AI Era

Welcome back to Breaktime Tech Talks for 2026! In this episode, dive into the technical challenges I faced with GenAI procedure migrations, and the workarounds needed for Ollama embeddings. Then, explore the evolving landscape in the age of AI, including new terms like AEO (Answer Engine Optimization) that are changing how we think about discoverability.
Highlights:
Neo4j Vector Migration: Understanding the shift from list-based storage to the new vector data type in Neo4j
GenAI Procedures Evolution: Navigating multiple versions of GenAI procedures and their current limitations (v2025.11.2)
Ollama Workarounds: Using APOC library procedures when bleeding-edge syntax doesn't support your use case
Large-Scale Data Loading: Loading 2+ million books from the Goodreads dataset
Learning vs. Creating: Finding balance between content consumption and production in a rapidly evolving tech landscape
Lenny's Podcast: "The Leadership Skill AI Can't Replace" with Molly Graham
Lenny's Podcast: "The Ultimate Guide to AEO: How to Get ChatGPT to Recommend Your Product" with Ethan Smith

Ep63: MCP Integration Success + Advancing Semantic Search

Welcome to Breaktime Tech Talks! In this episode, get my latest breakthroughs and insights with Quarkus and Langchain4j, a new vector data type in Neo4j, and details on other projects and events I'm working on.
Highlights:
MCP Integration Success. Integrating MCP with Quarkus and Langchain4j (Github project). I overcame dependency issues and implemented custom wrapper methods for RAG tools.
Advancing Semantic Search. Dive into the new native vector data type in Neo4j, as introduced in a recent developer blog post. One benefit of this new data type for vector search includes data integrity, plus it includes nice migration from the old list format.
AI-First Java Book. Hear about my upcoming book, "AI First Java," co-written to help newcomers learn Java with an AI-first approach. I share my perspective on teaching foundational programming concepts in the age of AI-powered tools.
Upcoming Events. Preview my speaking engagements for early 2026, including the Glasgow meetup, Jfokus, and Devnexus.
Podcast Updates: Hear my thoughts on future guests and feel free to add your thoughts in the BTT feedback form.

Ep62: Quarkus Langchain4j Updates + Production-Ready Agents on JVM

In this episode, hear my latest adventures in the world of Java development, focusing on integrating Langchain4j with Quarkus, tackling dependency management, and exploring the evolving landscape of generative AI in production systems. Plus, I highlight upcoming community events and must-watch videos for developers.
Highlights:
Langchain4j + Quarkus: Read-Only Database Success & Dependency Challenges - progress on a read-only Neo4j database with Langchain4j and Quarkus, caveats around configuration, and the "dependency hell" encountered when adding the MCP server for text-to-Cypher capabilities.Project link: Langchain4j Quarkus Graph RAG app
Upcoming Events
O'Reilly Graph RAG Fundamentals workshop (virtual, Dec 18)
Global Big Data Conference (virtual, Dec 15th)
Recommended Videos
"Gen AI Grows Up: Building Production Ready Agents on the JVM" by Rod Johnson (GOTO Chicago 2025)
Focus: Integrating generative AI into existing Java business solutions, and the new open source project Embabel.
"Spring in Autumn with Neo4j" by Gerrit Meier (NODES 2025)
Focus: Spring projects and frameworks for integrating with Neo4j, plus tips for other tech stacks.

Ep61: William Lyon on Knowledge Graphs + Agentic Memory

For the first time ever, Jennifer welcomes a guest to the show! William Lyon gives us a deep dive into the evolving world of AI agents, knowledge graphs, and the concept of memory in artificial intelligence.
Episode highlights:
William’s career journey: from Neo4j to startups and back again
The role of knowledge graphs in agentic memory and reasoning
Types of memory in AI agents: episodic, procedural, and more
How knowledge graphs can model both user-facing and operational memory
The importance of domain-specific data modeling for AI memory systems
William’s AI Memory Landscape project: cataloging tools, frameworks, and services in the AI agent memory space
Contributions to the project are open, so submit a PR or request!
Advice for developers architecting AI agents with memory
Other referenced links:
GraphStuff.FM podcast
AI Memory Landscape project: https://ai-memory-landscape.netlify.app/
Connect with William Lyon:
Website: https://lyonwj.com/

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

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 versioning headaches and framework differences between Spring AI and Quarkus for AI-powered applications.
Lessons learned from hands-on work with Neo4j GraphAcademy courses (GraphAcademy GenAI Fundamentals), including AI and knowledge graphs.
Key takeaways from the Andrej Karpathy interview (YouTube interview link), including:
The strengths and limitations of large language models (LLMs) for developers.
The concept of the “decade of agents” and how agents are shaping the future tech stack.
The importance of teaching as a way to deepen technical understanding.
Upcoming events and workshops:
Neo4j Fundamentals & GenAI hands-on workshop (learn more about workshop) – December 11th, virtual and free.
GraphRAG Fundamentals course on O’Reilly (course details) – December 18th.
NODES 2025 conference session recordings now available (full YouTube playlist).

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

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 course
Solving tough graph problems with Cypher 25
Resources Mentioned:
NODES 2025 playlist (only keynotes at this time)
Luanne Misquitta’s Music Graph session
RushDB session by Artemiy Vereshchinskiy
Langchain4j read only db issue (solved!)
Neo4j Graph Academy Aura Fundamentals blog post
Solve Hard Problems with Cypher 25 blog post
Advent of Code (2025)
Thanks for listening!

Ep58: Hybrid Search Headaches + GraphRAG as MCP Server

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 configuring hybrid search (vector + graph retrieval) in Langchain4j and Quarkus
Pain of setting up Neo4j vector stores, especially for read-only databases
Data importer docs difference (standalone vs Aura)
Why current frameworks make it hard to customize retrieval workflows
Discovery of Neo4j’s MCP Cypher server for vector search as a tool
Blog post on implementing GraphRAG retrievers as an MCP server for reusable, agentic applications
Updates on the GraphRAG Fundamentals online course and the upcoming NODES 2025 conference
My new new Java book project
Tune in for practical advice, honest roadblocks, and new ideas for building smarter, more flexible developer tools!

Ep57: Developer Advocacy Realities + Conditional Logic in Cypher

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 responsibilities, and learning to say “no”
🏢Why developer advocacy is often a “departmental orphan” and how that brings unique value
🏆The rewarding aspects: variety, constant learning, connecting with the developer community, playing to your strengths, and prioritizing high-impact work
👩🏽‍💻Updates on Jennifer’s current projects, including work on Spring AI Advisors and an upcoming conference appearance
⚙️A deep dive into Christoffer Bergman’s blog post on Cypher Conditional Queries
 🎊What’s new in Cypher 25: the WHEN THEN ELSE syntax and how it improves query readability and maintenance
Every tech role has its ups and downs, but I've found my place. Don’t miss my insights on Cypher’s latest features and stay tuned for more updates on my projects and events. Thanks for listening, and happy coding!

Ep56: Java and Langchain4j Releases + GraphRAG with Langchain4j

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 embeddings for Neo4j (Cypher vs APOC)
Spring AI advisors (QA advisor and RAG advisor)
NODES 2025 - free, online technical event!
Content: Integrating Neo4j with Langchain4j for GraphRAG Vector Stores and Retrievers - GraphRAG with Langchain4j and Neo4j in a Spring app