Git issues, finally resetting local branch, cherry-picking, and cleaning up. Then a fun graph presentation - Dungeons, Dragons, and Graph Databases.

In this episode, hear some positive tech experiences from the week: the upgrade from GitHub Actions (upload/download artifact) to v4 through a 3rd party repo, and the new AI coding assistant feature in IntelliJ IDEA.

This episode, my refresher with the Graph Data Science library with highlights and challenges. Then an overview of the Building Knowledge Graphs book, a guide on everything from concepts to technical details.

Hear learnings from the new Spring Data Neo4j course - building blocks, updates/deletes, and modeling. Then recap XtremeJ and NODES 2024, + upcoming at CJUG.

In this episode, get my latest experiences with the Neo4j LLM Graph Builder, both the benefits and challenges. Then, an article focusing on the concept of the "Aha moment"—a key moment when developers discover the value of a technology.

In this episode, hear why data (a less glamorous topic) is actually fascinating and crucial. Then, look forward with a preview of next week's NODES 2024 event, which features a range of sessions on graph technologies, AI, data science, and security. Finally, get a teaser for the next episode.

Cover the basics of graphs, explaining mathematical roots and applications. Introduce Goodhart's Law and highlight the risks of over-focusing on metrics, whether in tech or personal growth.

Explore agents in AI, distinguishing them from RAG (article1, article2). And discuss naming and the importance of conveying relevance and clarity.

Want to take our previous vector topic a step further with vector similarity search. Then, I’ll give my thoughts on 2 recent tech conferences - JConf and dev2next.

The Asciidoc markup language is powerful and useful for developers and technical writing. Also highlighting productivity books - Atomic Habits and Deep Work - and applications for a developer.