Forem: Goutham Rayaprolu

Building AI-Powered Apps with Spring AI and Spring Boot

Goutham Rayaprolu — Thu, 08 Jan 2026 17:09:51 +0000

We've seen how quickly AI is changing the game. Just a couple of years ago, integrating large language models (LLMs) into Java apps felt clunky—relying on Python wrappers or direct REST calls to external APIs. But in 2026, Spring AI (integrated seamlessly with Spring Boot 4) makes it feel natural, almost like adding any other Spring dependency.

If you're building microservices, chatbots, recommendation engines, or even intelligent data processors (common in India's fintech and e-commerce boom), Spring AI is the tool that's making AI accessible without leaving the Java ecosystem.

Why Spring AI Matters Now

Spring AI abstracts away the complexity of working with AI providers like OpenAI, Anthropic, Hugging Face, or even local models via Ollama. It follows the familiar Spring pattern: portable APIs across providers, just like Spring Data or Spring Security.

Key wins in 2026:

Provider Agnostic: Switch from GPT-4o to Claude or a local Llama model with minimal code changes.
RAG Made Easy: Retrieval-Augmented Generation for grounding responses in your data (e.g., company docs or databases).
Integration with Spring Ecosystem: Works beautifully with Spring Boot's observability, security, and cloud-native features.
Production-Ready: Built-in support for metrics, tracing, and rate limiting.

Combined with Spring Boot 4's modularization and Java 25 support, it's lighter and faster than ever.

Quick Start: A Simple Chatbot Endpoint

Add dependencies (Spring Boot 4 starter):

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>

Configure your API key in application.yml:

spring:
  ai:
    openai:
      api-key: ${OPENAI_API_KEY}
      chat:
        options:
          model: gpt-4o-mini

Create a service:

@Service
public class AiService {

    private final ChatClient chatClient;

    public AiService(ChatClient.Builder chatClientBuilder) {
        this.chatClient = chatClientBuilder.build();
    }

    public String generateResponse(String userInput) {
        return chatClient.prompt()
                .user(userInput)
                .call()
                .content();
    }
}

Expose via a controller:

@RestController
@RequestMapping("/ai")
public class AiController {

    private final AiService aiService;

    public AiController(AiService aiService) {
        this.aiService = aiService;
    }

    @PostMapping("/chat")
    public String chat(@RequestBody String message) {
        return aiService.generateResponse(message);
    }
}

That's it—a fully functional AI endpoint in under 50 lines!

Going Further: RAG with Your Data

For real-world apps, use vector stores (e.g., PGVector, Pinecone) to add context:

chatClient.prompt()
    .user(userInput)
    .documents(retrievedDocs)  // From your vector DB
    .call()
    .content();

Spring AI handles embedding models automatically.

Why This Excites a Java Dev

No more context-switching to Python for AI prototypes. We can now build end-to-end AI features in pure Java/Spring, leveraging our existing skills in dependency injection, validation, and testing.

In fast-growing AI startup scene, this levels the playing field—faster iteration, lower costs with local models, and enterprise-grade reliability.

Get Started Today

Check out the official Spring AI docs or start a new project on start.spring.io with the AI starters. Experiment with local LLMs via Ollama for zero-cost testing.

Have you tried Spring AI yet? What's your favorite use case—chat interfaces, code generation, or data summarization? Share in the comments!

Why Project Valhalla Will Revolutionize Java Performance in 2026

Goutham Rayaprolu — Tue, 06 Jan 2026 18:15:08 +0000

Java has powered enterprise systems for decades, but let's be honest—it's often criticized for memory overhead and performance bottlenecks compared to languages like Rust or Go. Enter Project Valhalla, one of the most exciting OpenJDK initiatives that's finally approaching reality in 2026.

If you're still on Java 21 or even 25 (the latest LTS as of early 2026), Valhalla's value classes could be the game-changer that makes your code faster, leaner, and more efficient—without rewriting everything in a new language.

What Is Project Valhalla, Anyway?

Project Valhalla aims to augment Java's object model with value objects (also called value classes). Right now, every non-primitive object in Java has:

An object header (for identity, locks, etc.)
Reference semantics (passed by reference)
Potential heap allocation overhead

This "object tax" adds up in performance-critical apps like data processing, games, or financial systems—common in booming fintech and e-commerce sectors.

Value classes flip this:

They behave like primitives (int, double) under the hood: no identity, no headers, flattened in arrays.
But they look like regular classes to you: with fields, methods, generics.

Example (preview syntax in early-access JDK 26 builds):

value class Point {
    private final int x;
    private final int y;

    public Point(int x, int y) {
        this.x = x;
        this.y = y;
    }

    public int distance() {
        return Math.abs(x - y);
    }
}

An array of Point would store the x and y directly inline—no pointers to separate objects!

Why 2026 Is the Tipping Point

Recent Progress: JEP 401 (Value Classes and Objects) has early-access builds in JDK 26 (expected later in 2026). Combined with updates from 2025, it's moving from "research project" to usable preview.
Synergy with Loom: Virtual threads (stable since Java 21) handle concurrency beautifully, but Valhalla tackles the data side—reducing GC pressure and improving cache locality.
Real-World Impact:
Memory Savings: Arrays of value objects can be 2-10x denser.
Speed Boosts: Better CPU cache usage means faster computations (think big data with Spark or machine learning libs).
Frameworks Benefit for Free: Libraries like Jackson, Hibernate, or even Spring will get performance wins automatically.

Hands-On: Trying It Today

Download an early-access JDK 26 build from jdk.java.net. Enable previews:

java --enable-preview --source 26 YourValueClass.java

Experiment with simple benchmarks—compare Point[] as a regular class vs. value class. You'll see the difference!

Should You Care as a Java Dev in 2026?

Absolutely. Trends show Java dominating cloud-native (Quarkus, Micronaut) and AI integration (Spring AI, LangChain4j), but performance remains key for scaling apps cost-effectively on AWS/Azure.

Valhalla isn't just another feature—it's Java admitting primitives aren't enough for modern hardware. Paired with Vector API (for SIMD) and Leyden (faster startup), it's keeping Java relevant against newer rivals.

If you're building microservices, Android apps, or processing large datasets, start exploring Valhalla previews now. Your future self (and your employer's cloud bill) will thank you.

What do you think—excited for value classes, or waiting for full stability? Drop your thoughts below!

Published on Dev.to – January 2026