Episode 200: Java & Spring AI Are Winning the Enterprise AI Race — with James Ward & Josh Long

About this episode

It's a milestone — episode 200! And to mark the occasion, we're doing something we've never done before: hosting two guests at the same time. James Ward (Principal Developer Advocate at AWS) and Josh Long (Spring Developer Advocate at Broadcom, Java Champion, and host of 'A Bootiful Podcast') join Romain for a wide-ranging conversation about why Java and Spring AI are becoming the go-to stack for enterprise AI development. We kick off with Spring AI's rapid evolution — from its 1.0 GA release to the just-released 2.0.0-M3 milestone — and why it's far more than an LLM wrapper. James and Josh break down how Spring AI provides clean abstractions across 20+ models and vector stores, with type-safe, compile-time validation that prevents the kind of string-typo failures that plague dynamically typed AI code in production. The numbers back it up: an Azul study found that 62% of surveyed companies are building AI solutions on Java and the JVM. James and Josh explain why — enterprise teams need security, observability, and scalability baked in, not bolted on. We dive into the Agent Skills open standard from Anthropic and James's SkillsJars project for packaging and distributing agent skills via Maven Central. We also cover Spring AI's official Java MCP SDK (now at 1.0) and how MCP and Agent Skills complement each other for building capable, composable agents. The performance story is striking: Java MCP SDK benchmarks show 0.835ms latency versus Python's 26.45ms, 1.5M+ requests per second versus 280K, and 28% CPU utilization versus 94% — with even better numbers using GraalVM native images. Josh and James also walk us through Embabel, the new JVM-based agentic framework from Spring creator Rod Johnson, featuring goal-oriented and utility-based planners with type-safe workflow definitions built on Spring AI foundations. We close with a look at running Spring AI agents on AWS Bedrock AgentCore — memory, browser support, code interpreter, and serverless containers for agentic workloads.

Links

Here are the links to the tools, technologies, or articles we mentioned in this episode.