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Java Articles by Foojay.io

October, 2025

  • 20 October

    Foojay Podcast #80: AI4Devs Interviews – Part 2

    Author: Frank Delporte Original post on Foojay: Read More Table of Contents VideoPodcast (Audio only)Content This is part 2 of the interviews recorded on September 19th, 2025, at the first AI4Devs conference in Amsterdam. In Part 1, we explored many AI-related topics as libraries, security, infrastructure, use cases, and more. In this second part, we’ll dive into data science, tools …

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  • 16 October

    Beyond Keywords: Implementing Semantic Search in Java With Spring Data (Part 1)

    Author: Ricardo Mello Original post on Foojay: Read More Table of Contents The magic behind vector searchPrerequisitesEmbeddings with Voyage AIPreparing the datasetMongoDB Atlas Vector Search (index and retrieval)Building the movie search app Configuring the application The document model Wire the request DTO Communicating with Voyage AI The EmbeddingService Querying with Spring Data Vector Search operation The MovieController Running the application …

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  • 16 October

    How Chat Memory Manipulation Can Ruin Your AI System

    Author: Brian Vermeer Original post on Foojay: Read More Table of Contents Do LLMs have any conversational memory?Implementing chat memory in your AI app Chat messages with Java’s Langchain4J LLM chat memory injection Chat memory injection: Proof of concept Preventing chat memory manipulation is key Do LLMs have any conversational memory? With the use of ChatGPT, Claude, and Copilot, we …

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  • 15 October

    7 Habits of Highly Effective Java Coding

    Author: Jonathan Vila Original post on Foojay: Read More Table of Contents From AI User to AI Pro 1. The Golden Rule: Take Pride and Ownership in Your Craft 2. Feed the Beast: Your Project’s Context is its Fuel 3. Dodge the “Ball of Mud”: Keep Your Code Maintainable 4. Clean Your Room: No Stray Code or Sketchy Dependencies 5. …

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  • 14 October

    The Cost of Not Knowing MongoDB – Part 1: appV0 to appV4

    Author: Artur Costa Original post on Foojay: Read More Table of Contents The application: finding fraudulent behavior in transactionsThe load testInitial scenario and data generatorThe instances configurationApplication Version 1 (appV1) Schema Bulk upsert Get reports Indexes Initial scenario stats Load test results Issues and improvements Application Version 2 (appV2) Schema Bulk upsert Get reports Indexes Initial scenario stats Load tests …

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  • 14 October

    JC-AI Newsletter #7

    Author: Miro Wengner Original post on Foojay: Read More Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence. Beyond focused tutorials that can enhance your understanding of AI applications, this newsletter concentrates on Hallucination, Java Code Generation, Testing, Agentic System Architecture and LLM benchmarking …

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  • 13 October

    What Happens When 10,000 JVMs Collaborate in One Production Environment

    Author: Simon Ritter Original post on Foojay: Read More Table of Contents Limitations of OpenJDK How Azul Platform Prime removes the limits of traditional JVMs A large global enterprise achieved a performance and efficiency milestone, running 10,000 Java Virtual Machines (JVMs) that collaborate and share optimizations with one another, using Azul Platform Prime’s Optimizer Hub. The enterprise improved application responsiveness and …

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  • 13 October

    BoxLang v1.6.0 – Performance, AI-Powered Docs, and Advanced Async Monitoring

    Author: Cristobal Escobar Original post on Foojay: Read More Table of Contents What’s New in 1.6.0? We’re thrilled to announce BoxLang 1.6.0, a release that delivers massive performance improvements, intelligent developer tooling, and enhanced async capabilities. This release focuses on making BoxLang faster, smarter, and more observable than ever before. 🚀 What’s New in 1.6.0? 🤖 BoxLang Documentation Meets AI: …

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  • 9 October

    Keywords Meet Vectors: Hybrid Search on MongoDB

    Author: Arek Borucki Original post on Foojay: Read More Table of Contents What is hybrid search?How does it work in MongoDB? Why movies collection are the perfect demo Inspecting the anchor document Sanity checks Step 1: Prepare the query vector Step 2: Run semantic search Step 3: Apply hybrid scoring Step 4: Hybrid ranking with Reciprocal Rank Fusion (RRF) Wrap-up …

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  • 7 October

    Working with Geo Location Data

    Author: Justin Jenkins Original post on Foojay: Read More MongoDB makes it really easy to work with location data (sometimes called Geo Data) by simplifying how to store this type of data and streamlining how you query for it so you can easily create “find nearby” queries, or plot your location data with ease! Let’s start with the basics: modeling …

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