Devnexus 2026
2026-03-04..2026-03-06
Atlanta, United States
Devnexus ·
[Devnexus 2020, Devnexus 2021, Devnexus 2022, Devnexus 2023, Devnexus 2025, Devnexus 2026]
| title | author | length |
|---|---|---|
| Agents, Tools, and Mcp, Oh My! Next Level AI Concepts for Developers | Jennifer Reif | 53m |
A Spring Boot demo wires an LLM to a Neo4j-backed vector store and executes vector search plus a graph RAG traversal to return context-aware book… | ||
| Architecting Microservices for Agentic AI Integration | Rohit Bhardwaj | 59m |
Practical, production-proven guidance for integrating agentic AI: teams run 40 to 50 agents in production and move from chat-driven fans-out to deterministic… | ||
| Building AI Agents with Spring & MCP | Josh Long, James Ward | 49m |
Shows a runnable Java stack that wires Spring AI to Amazon Bedrock models and a Postgres + PGVector store to build a RAG chat assistant that finds adoptable… | ||
| From Monolith to AI Agent Modernizing Java Systems with MCP | Théo Lebrun | 32m |
MCP (Model Context Protocol) provides a concrete path to add LLM-driven agents to legacy Java monoliths without full rewrites by adding a separate MCP server… | ||
| Integrating LLMs in Java A Practical Guide to Model Context Protocol | Dan Vega | 57m |
Claims that the Model Context Protocol standardizes how LLMs access tools and data and that a Java SDK (donated by Spring) makes enterprise MCP servers… | ||
| Tools & Tips to Modernize Your Java code with AI | Jonathan Vogel, Vinicius Senger | 59m |
Live demo shows an agent that ingests a JFR file, maps hotspots to known anti‑patterns, edits source, then builds and tests the fixes automatically, cutting a… | ||
| AI Agents for Java Devs From Demo to Deployment | Brian Benz | 54m |
A working end-to-end invoice pipeline parses PDFs with an external GPU parser, validates totals and line items, and flags anomalies automatically. It uses a… | ||
| Brokk, an AI Native Code Platform for Java, in Java | Jonathan Ellis | 53m |
A standalone Java Swing IDE named Brokk supervises AI coding by combining Eclipse JDT static analysis, dependency decompilation and a pure‑Java LLM runtime… | ||
| Connecting the Dots with Context Graphs | Stephen Chin | 56m |
Argues that durable Context Graphs—combining knowledge graphs, embeddings and tool traces—fix fragmented enterprise context and improve explainability… | ||
| Choose Your Fighter Spring AI vs LangChain4j | Malavika Balamurali | 30m |
Compares Spring AI and LangChain4j by showing working code: a chat client that calls a local Ollama Mastral model to explain integrals. Spring AI uses… | ||
| Design Patterns for Multi Agent Systems | Brian Sam-Bodden | 56m |
Compares three concrete orchestration styles by building a runnable demo that wires Spring AI, LangChain4j, and Embabel into separate services talking to a… | ||
| Keynote - Hacking AI How to Survive the AI Uprising | Gant Laborde | 37m |
Walks through concrete attacks and defenses: jailbreaks like copyable DAN prompts and a greedy coordinate gradient exploit that is reported 100% effective… | ||
| Keynote - Its Up To Java Developers to Fix Enterprise AI | Rod Johnson | 50m |
Argues that enterprise AI succeeds only when engineering replaces ad hoc prompts and shows a Java-first solution: a server framework called imbabel that uses… | ||
| Fundamentals of Software Engineering In the age of AI | Nathaniel Schutta, Dan Vega | 56m |
Distills an eight-hour workshop into practical claims: fundamentals still matter even as GPT/Claude and LLM-based agents speed code generation; examples… | ||
| Hands on Embabel | Rod Johnson | 59m |
Embabel is a JVM framework that demos a working Java Spring Boot starter template, LLM starters for OpenAI and Anthropic, and a fluent AI interface that… | ||
| Performant GraphRAG Improving Neo4j to Drive Autonomous AI ... | Brandon Tylke, Jon Gentsch | 30m |
Neo4j is reshaped to power fast GraphRAG pipelines by building materialized views, search nodes and graph diffs that turn a 120 hour manual workflow into ~20… | ||
| The Anatomy of Memory in Humans and AI Agents | Raphael De Lio | 54m |
A concrete memory stack: the Radius agent memory server stores session/working memory (namespace, session ID, user ID, messages, TTL) and a long-term store… | ||
| Stop Fighting Your AI Engineering Prompts That Actually Work | Martin Rojas | 48m |
Argues that prompts should be engineered like code and shows techniques that make outputs predictable: using a persistent system message, explicit context… | ||
| From Microservices to Agent Services Architectural Patterns for Autonomous System.. | Mo Haghighi, Prasanth Pari | 52m |
Shows concrete failure modes and defenses: autonomous agents caused real incidents — colluding trading algos (Dec 2025), 24 banking chatbots all exploitable… | ||
| 10 Things I Hate About AI | Laurie Lay, Cody Frenzel | 39m |
Lists ten concrete failures: top‑down mandates that create fake buy‑in, useless vanity metrics like “percent AI code,” LLM hallucinations that are confidently… | ||
| The Golden Path Starts at Home Engineering Developer Experience from Laptop to Prod | Tim Sparg, DaShaun Carter | 01h 02m |
Shows a concrete golden path: use mi to declare and install per-repo toolchains and auto-install git hooks (HK), run linters and cached binaries, and enable an… | ||
| Staying Current A Journey in Software Maintenance | Ho Jong Yu, Shriyu Gaglani | 34m |
Describes a concrete maintenance pipeline that centralizes common libs and replaces a parent POM with an automated toolchain: a homegrown fly CLI that… | ||
| Spring Cloud Supercharged for Production Ready Apps | Ryan Baxter, Chris Sterling | 01h 00m |
A concrete demo builds a three-app poll system (poll UI, poll service, results service) wired with Eureka + Spring Cloud Config + Spring Cloud Stream, using… | ||
| Refactoring the ROI of Software Continuous Mondernization with Tanzu Platform | DaShaun Carter | 52m |
Demonstrates continuous migration using VMware Tanzu Application Advisor and OpenRewrite to upgrade a Spring Boot 1.5 Java 8 app through a 17 automated steps… | ||
| Modern API Versioning and Enterprise Ready AI Enablement with Spring Cloud Gateway | Spencer Gibb, Chris Sterling | 01h 00m |
Demonstration shows Spring Cloud Gateway adding first-class API versioning with built-in negotiation and improved route matching, autogenerated OpenAPI via… | ||
| Life After Dad Joke Apps Building “Enterprise Grade” AI Frameworks for Java | Kevin Strohmeyer, Josh Long, Rod Johnson, Adib Saikali | 52m |
Covers how to move prototypes into production using Java and the JVM: concrete patterns include Spring AI integrations, using on‑prem models for data tenancy… | ||
| Enabling High Throughput, Low Latency Inference for Your AI Applications | Cora Iberkleid | 01h 02m |
Demonstrates a hybrid architecture that runs lightweight models inside the JVM for millisecond inference and pushes computation into an in‑memory data grid… | ||
| Building AI Agents with Spring AI and Tanzu Platform | Josh Long, Adib Saikali | 54m |
Claims that the JVM plus Spring AI and Tanzu Platform let teams move from experiments to production with concrete results: a benchmark shows Java <1ms P95 and… | ||
| The Modern Spring Workflow Enterprise Ready Delivery & AI Boosted Coding with Tanzu | Chris Sterling, Cora Iberkleid | 01h 06m |
Tanzu Application Advisor generates a continuous upgrade plan (example: a 9‑step path from Java 8 → 11 → 17 → Spring Boot 4 / Spring Framework 7) using an… | ||
| Intros his workshop | Venkat Subramaniam | 01m |
Workshop covers Java 9–25 features with concrete examples and actionable guidance on applying recent language changes to real codebases. It claims to show… | ||
| nothing matches | ||