All Episodes
Breaktime Tech Talks — 83 episodes
Ep83: Book Writing Progress + GraphRAG & DevRel in the AI Era
Ep82: AI and Code Generation + Code Reviews in a Changing Landscape
Ep81: Curating NODES 2026 + The Software Industrial Revolution
Ep80: Rethinking AI Intelligence + Developer Careers After Code Generation
Ep79: Reducing Agent Token Costs + RAG Beyond Semantic Search
Ep78: AI-First Java Book + Embabel for Enterprise Agents
Ep77: Spring AI Memory Bug + LLMs, Skills, & Your Dev Career
Ep76: Batching in Native Cypher + Avoiding Injection Vulnerabilities
Ep75: Versioning AI Models + Define Schema for Better Knowledge Graphs
Ep74: Building without a Blueprint + Scaling Graphs with Infinigraph
Ep73: Cypher Query Tuning + Does Language Still Matter in the Age of AI?
Ep72: Live Coding Fails and Fixes + Why LLMs Lose the Plot
Ep71: GraphRAG Learnings + Langchain4j Apps for Production
Ep70: Devnexus Conference Recap + No-LLM Agentic Workflow
Ep69: Growth through Challenge + Rise of Agentic AI
Ep68: Career Highlights + OGM Alternatives
Ep67: Conference Recap + Cypher Query Patterns
Ep66: Neo4j Data Loading at Scale + Vector Search Filtering
Ep65: RAG Filtering + Context Graphs with Neo4j
Ep64: Neo4j Vector Migration + Learning in the AI Era
Ep63: MCP Integration Success + Advancing Semantic Search
Ep62: Quarkus Langchain4j Updates + Production-Ready Agents on JVM
Ep61: William Lyon on Knowledge Graphs + Agentic Memory
Ep60: Langchain4j & Neo4j Integration Breakthroughs + The Decade of Agents in AI
Ep59: NODES 2025 Highlights + Solving Graph Problems with Cypher 25
Ep58: Hybrid Search Headaches + GraphRAG as MCP Server
Ep57: Developer Advocacy Realities + Conditional Logic in Cypher
Ep56: Java and Langchain4j Releases + GraphRAG with Langchain4j
Ep55: Demystifying MCP + Future of Vibe Coding and RAG
Ep54: Spring AI Integrations + Real-World RAG Challenges
Ep53: Language Models for Data Tasks + MCP Journey Begins
Ep52: Enhancing AI with Spring Advisors + GraphRAG Python Adventures
Ep51: Exploring AI Agents + Agentic GraphRAG in Java
Ep50: GraphRAG with Advisors + Spring AI Concepts
Ep49: Moving toward AI Tools/Agents + Local RAG app with Quarkus
Ep48: Java GraphRAG and Langchain4j 1.0 + Thoughts on conversational interfaces
Ep47: Langchain4j GraphRAG Friction + MCP Authorization Headaches
Ep46: Quarkus Neo4j Application + Development Lessons Learned
Ep45: Exploring Java Frameworks + Launch of Spring AI 1.0
Ep44: Updates in Java tools + MCP and Security
Ep43: MCP Java SDK + Naive RAG vs GraphRAG
Ep42: RAG and Java + AI-generated content and MCP
Ep41: Spring AI M7, NODES, RAG + Neo4j, Quarkus, and Intelligent Apps
Ep40: Recent AI learnings + More than a vector database
Ep39: Why embedding models should match + Advice for starting a blog
Ep38: Spring AI Debugging + How to Contribute to Open Source
Ep37: Vector Database Frustration + Microsoft LazyGraphRAG
Ep36: What is a Developer Advocate + Balancing Digital Consumption
Ep35: Vector Databases + Building Effective Agents
Ep34: Outlines and Iterating + Lessons from Grace Hopper
Ep33: Cypher DSL examples + Crowd-source AI hacking
Ep32: Official CLI + Bread Code Framework
Ep31: Database CLI + Containerization Refcard
Ep30: SDN update entity + Knowledge Graph ebook
Ep29: Neo4j GenAI plugin + How-To for Technical Content
Ep28: 2024 Recap, 2025 Look-Ahead + Always Be Launching
Ep27: Lexical vs Semantic Search + Downside of Vector Databases
Ep26: Git Troubles + Dungeons & Dragons Graph
Ep25: Github Actions + AI Coding Assistant
Ep24: Graph Data Science + Building Knowledge Graphs
Ep23: Spring Data Neo4j course + Event recap
Ep22: LLM Graph Builder + Devrel unlocks “aha” moment
Ep21: Data is cool + NODES 2024 preview
Ep20: What is a graph + Goodhart’s Law
Ep19: RAG vs Agents + Naming Things
Ep18: What is Vector search + JConf/Dev2next experiences
Ep17: Using Asciidoc for Tech Content + Current Productivity Reads
Ep16: Mapping Relationships in Applications + Software Estimates
Ep15: What is GraphRAG + Developing Better Software
Ep14: Making Tech Relatable + Java Entity Mapping
Ep13: GraphQL vs GQL vs Cypher + Road to NODES
Ep12: What is RAG + Case for Conferences
Ep11: What is a Knowledge Graph + DevUp Conference
Ep10: What are embeddings + LLM use case and prompt
Ep9: Graphs for Conference Scheduling + Spring AI 1.0
Ep8: Luck Favors the Prepared + LLM Graph Builder Tool
Ep7: Deploying Neo4j on Kubernetes + Parallel Relationship Loading
Ep6: Maintaining Personal Website + Git Submodules
Ep5: What are vectors + KCDC Highlights
Ep4: Where’s the Graph Data Type in Programming Languages?
Ep3: Current Tech Read and Exploring Kubernetes
Ep2: Spring AI Debugging and Query Tune-Up
Ep1: Meet Breaktime Tech Talks + Devnexus Summary