Breaktime Tech Talks

jmhreif
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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.

  1. 4日前

    Ep82: AI and Code Generation + Code Reviews in a Changing Landscape

    Recap of my week, with several different topics where I expanded my knowledge or surfaced some recurring patterns in my efforts. Highlights: Repeated prompt iteration can cause LLMs to get stuck in unhelpful loops or produce slightly different code on reruns. Restoring to a checkpoint helps reset context and regenerate cleaner output. A personal AI workflow shortcut: using chat models to brain dump and organize ideas into structure before writing. Pet projects. Alongside expanding a Goodreads project, there's a potential new personal improvement app idea Other tasks: session review for NODES conference, upcoming refresh work on a Knowledge Graph e-book, and plans for short-form video content. Article: “Read Less, Steer More” by Ezyang on mentoring code reading, using LLMs to explain code, avoiding auto-accept edits, and writing code by hand when learning fundamentals.

  2. 7月3日

    Ep81: Curating NODES 2026 + The Software Industrial Revolution

    This week included reviewing abstracts for NODES developer conference returning this fall, making progress on the book, and other exciting things happening within the team. Highlights: Schedule for Neo4j’s free virtual NODES is in the process as we review and select sessions. Register now! Progress on the Java book with an aggressive schedule that is challenging, but manageable. Several colleagues are at the AI Engineer World’s Fair in California, so stop by to see them! Neo4j launched a major refresh to the GraphAcademy site, featuring a new design, AI-forward learning features. Hear my thoughts on Andy Coenen’s article “The Software Industrial Revolution". AI may reduce software costs, increase software consumption, disrupt monopolies, and potentially improve costs and experiences in areas like healthcare.

  3. 6月26日

    Ep80: Rethinking AI Intelligence + Developer Careers After Code Generation

    Wrapping up a busy week of GraphRAG training and book writing with two topics worth unpacking: what we actually mean when we call AI "intelligent," and what a recent article reveals about the shifting landscape for software developers. AI models are pattern-matching algorithms. They appear intelligent only when humans surface the right context, not on their own "Intelligent" is a term developers should use loosely and critically, not as a given I ran a GraphRAG Fundamentals online workshop (code available) and is deep in writing her AI-first Java book The article "Code is Cheap. Show Me the Talk" argues that LLM tools have fundamentally changed software development AI-generated docs and READMEs make it harder to judge how much care an author put into their work "Slop" has always existed in software. AI just makes it harder to spot The biggest cost: junior developers are losing the learning path that built strong technical foundations Senior devs have an opportunity to mentor the next generation differently The hype around AI in development cuts both ways. It lowers barriers to building, but raises the stakes for intentional learning and craft. Worth thinking about wherever you are in your career.

  4. 6月12日

    Ep79: Reducing Agent Token Costs + RAG Beyond Semantic Search

    In this episode, I sit down with Roie Schwaber-Cohen, a software engineer and developer advocate at Pinecone, to talk about smarter ways to build with AI — without burning through tokens or your patience! What we cover: Why agentic AI systems burn so many tokens (and ways to combat it) How Pinecone's Nexus pre-explores retrieval paths so agents don't have to discover them at runtime, cutting latency and token usage The problem with naive RAG ("Franken answers") and why domain-level separation of your documents matters How Pinecone Marketplace lets non-developers connect structured and unstructured data sources to build production-ready AI apps Why semantic similarity isn't the same as correctness, and how document introspection helps agents ask better questions Links & Resources: Pinecone Pinecone Marketplace (recently announced) Pinecone Nexus Roie on LinkedIn

  5. 6月5日

    Ep78: AI-First Java Book + Embabel for Enterprise Agents

    I'm back after a couple of weeks of hiatus with a packed update. From a major book deadline to enterprise graph hackathons, summer is anything but slow. AI-First Java Book. First six chapters officially submitted. They cover concept progression, real-world problem solving, and a developer's career journey Customer Graph Hackathons. First hands-on event with Neo4j at an enterprise customer site, and another one coming next week GraphRAG Fundamentals Training. Rescheduled on O'Reilly Learning Platform; available to sign up Neo4j CLI. New tool for interacting with Neo4j from the command line, with agent skill support for coding tools like Claude Agent Instruction Protocol. Open-source repo that turns skill specs into YAML-based execution graphs modeled as process flows Building Agents in Java with Embabel. Dan Vega's walkthrough of this Java AI framework. It covers actions, plans, goals, and reusable components for enterprise agents Lots of exciting things in motion — grab the links in the show notes and happy coding!

  6. 5月15日

    Ep77: Spring AI Memory Bug + LLMs, Skills, & Your Dev Career

    A packed week of travel, debugging, writing, and reading. I share what I learned and ran into this week as a developer. Highlights: 🗣️ Spoke at the JavaMUG (Java Metroplex User Group) meetup in Dallas — highly recommended for Dallas-area developers! 🐛 Discovered a bug in Spring AI's Neo4j chat memory integration with the latest Spring Boot — workaround is to use in-memory storage for now. 📖 Working on a Java book chapter covering OOP concepts (abstraction, encapsulation, polymorphism) with a focus on practical, use-case-driven learning Event updates: 📅 Session from the AI Agents conference is now on YouTube GraphRAG Fundamentals O'Reilly course rescheduled to June in APAC timezone NODES CFP open until June 15th 📝 Two recommended reads: "MCP, Skills, and Agents" by David Cramer "LLMs and Your Career" by Phil Eaton

  7. 5月1日

    Ep76: Batching in Native Cypher + Avoiding Injection Vulnerabilities

    A quieter week, but still full of forward motion — from clearing the Neo4j developer blog backlog and making progress on the upcoming Java book, to lining up upcoming speaking events. Plus, two developer-focused content pieces I hope you enjoy as much as I did. This Week's Updates: Rescheduling the GraphRAG Fundamentals training (likely June, APAC-friendly time zones) Cleared a backlog of community submissions for the Neo4j Developer Blog — open to anyone with a Medium account Cypher/SQL injection understanding from Neo4j Definitive Guide book Writing progress on a new AI-first Java learning book, drawing on literary aspirations and music pedagogy principles for a fresh teaching approach New speaking opportunities coming in May and June — stay tuned Content Pieces: "Batching Like a Pro" by Gemma Lamont — A detailed feature comparison of apoc.periodic.iterate vs. native Cypher CALL IN TRANSACTIONS, covering memory tracking, error handling, query planning, concurrency, entity rebinding, and retry strategies. The gap has largely closed — native Cypher is nearly on par. NODES AI videos now on YouTube — All session recordings from Nodes AI are publicly available. Link in the show notes.

  8. 4月24日

    Ep75: Versioning AI Models + Define Schema for Better Knowledge Graphs

    This week, I prepped for upcoming events, tweaked and strategized some existing processes, and found more data on how defining a schema can produce better knowledge graph construction. Highlights: Prepped for two upcoming events: a Graph RAG Fundamentals training on O'Reilly Learning Platform and a session at a virtual AI Agents conference. Updating repositories for the workshop surfaced a chain-reaction lesson: upgrading frameworks leads to data changes, which require config updates, which require prompt rewrites. Key takeaway — don't pin your apps to latest for AI models, just as you wouldn't for Docker image tags. Tie to a specific version so updates don't cascade unexpectedly. Also revisited my tech blogging workflow and built a template script to eliminate boilerplate setup, shaving time off the writing process without sacrificing the actual content creation. New blog post on agents, tools, and MCP published in the process! On the Neo4j side, I touched on the Neo4j Educator Program and how learning patterns among new developers are shifting — happy to accept feedback from educators teaching graphs. This week's article is Hands-on KG Relation Resolution by Mike Dillinger. It examines knowledge graph construction and why defining a narrowed schema produces cleaner, more understandable graphs. Without boundaries, LLMs and NLP processes generate overly granular, spaghetti-like structures.

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關於

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.

資料

  • 創作者
    jmhreif
  • 活躍年份
    2024年 - 2026年
  • 單集
    82
  • 分級
    兒童適宜
  • 版權
    © Copyright 2024 All rights reserved.
  • 節目網站
    Breaktime Tech Talks