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. Navigate the evolving landscape of LLMs, generative AI, and modern infrastructure with me in this episode.

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.

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 credibility within the community, it's a series of steps that gets better with time and practice!

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.

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.

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 examples. The article highlights the importance of starting simple, adding complexity only as needed.

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 between her insights and modern challenges in technology.

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.

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 article about a GitHub repository that combines coding and sourdough baking. It’s a cool reminder that the skills we learn in coding can apply to all sorts of other areas, even in the kitchen!

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, making complex concepts more accessible for developers.