🔸 TLDR
Java Champion Otavio Santana makes an important point:
Enterprise Java does NOT need to reinvent itself for AI.
You can add LLMs, assistants and agents while keeping the architecture, security, observability and governance you already trust.
And that may be Java’s biggest advantage. 👇
🔸 AI DOES NOT KILL ENTERPRISE ARCHITECTURE
AI demos are easy.
AI in production is not.
The moment an LLM can access data, call tools or execute actions, the old enterprise questions come back immediately:
▪️ Who is allowed to do what? 🔐
▪️ What happened and why? 👀
▪️ Can we audit it? 📋
▪️ Can we control failures? 🛡️
▪️ Where are the boundaries? 🧩
AI does not make those problems disappear.
It makes them MORE important.
And Java has spent decades solving them.
🔸 YOU CAN ALREADY DO AI WITH JAKARTA EE
No massive rewrite required.
You can choose your level of abstraction:
▪️ OpenAI / Anthropic / Google / Bedrock APIs
Maximum control. Maximum coupling.
▪️ OmniHai
A lightweight AI abstraction built for Jakarta EE and MicroProfile.
▪️ LangChain4j CDI
Define AI services as Java interfaces and let the infrastructure wire the implementation.
The real architectural question becomes:
CONTROL vs PORTABILITY.
🔸 THEN COMES AGENTIC AI
Jakarta Agentic AI wants to bring agents into the Jakarta EE programming model.
Not by replacing LangChain4j.
Not by replacing provider SDKs.
But by defining stable abstractions for agents, tools and workflows inside enterprise applications.
And that is where things get interesting.
🔸 TAKEAWAYS
▪️ Java is not “catching up” with AI.
▪️ Enterprise Java already provides many foundations AI production systems need.
▪️ AI should become another capability, not another architecture.
▪️ Agents make security, governance and observability even more critical.
▪️ The next battle is not Java vs AI.
It is unmanaged AI vs enterprise-grade AI.
Great article by Java Champion Otavio Santana:
https://lnkd.in/ezC2hzwm
#Java #JakartaEE #AI #EnterpriseJava #SoftwareArchitecture #LangChain4j #AgenticAI #GenerativeAI #JavaDevelopers
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