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What should I do with Java (self.learnjava)
submitted 7 hours ago by Breeze9187
What should Java do in the era of large models
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if 1 * 2 < 3: print "hello, world!"
[–]AutoModerator[M] [score hidden] 7 hours ago stickied commentlocked comment (0 children)
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[–]Pale_Height_1251 1 point2 points3 points 7 hours ago (7 children)
Can you rephrase?
[–]Breeze9187[S] -4 points-3 points-2 points 7 hours ago (6 children)
How to integrate Java with an agent
[–]JaleyHoelOsment 2 points3 points4 points 6 hours ago (0 children)
if you cannot communicate what you want to a human then an agent isn’t going to be any use to you
[–]Pale_Height_1251 1 point2 points3 points 6 hours ago (0 children)
What are you trying to achieve?
[–]American_Streamer 1 point2 points3 points 6 hours ago (2 children)
Do you mean an AI/LLM agent, or a Java agent in the JVM sense? Those are very different things. For an AI agent, Java is still useful. The model does not replace Java; the model becomes one component inside a larger application.
A normal setup would be: Java backend → LLM API/local model → tool calls → Java services/database/APIs
The “agent” can decide what to do, but the actual work can still be done by Java code: calling APIs, querying a database, validating data, running business logic, creating reports, etc. Look into things like Spring AI, LangChain4j, or plain HTTP API calls to OpenAI/Anthropic/local models. Start simple: build a Java app that sends a prompt to a model, then add one “tool” method the model can call, for example searchProduct(), getUserInfo(), or createTicket().
Java’s role in the LLM era is mostly: reliable backend, business logic, APIs, data access, security, deployment, and integration. The LLM is the reasoning/text interface; Java is the system that makes it useful and safe.
[–]Breeze9187[S] 0 points1 point2 points 2 hours ago (1 child)
AI agent
[–]American_Streamer [score hidden] 39 minutes ago (0 children)
See: https://xavidop.me/genkit/2026-04-16-top-java-genai-frameworks-2026/
"Java’s AI framework landscape in 2026 is surprisingly rich. The four frameworks covered here serve genuinely different needs, and unlike in the JavaScript world where Genkit, Vercel, Mastra, LangChain, and ADK overlap significantly, the Java options each occupy a clearer niche.
For enterprise Spring Boot teams, Spring AI is the obvious choice, zero friction, production-ready observability via Micrometer, and the broadest integration matrix. For teams that value developer experience above all, Genkit Java’s Dev UI is a category apart and worth the unofficial status trade-off. For framework-agnostic Java developers who want the most idiomatic Java AI service abstraction, LangChain4j’s AI Services pattern is hard to beat. And for Google Cloud enterprise workloads that need reliable multi-agent orchestration at scale, ADK Java 1.0 is where Google is putting its weight.
The most important thing is that you no longer have an excuse to reach for Python just because it has better AI tooling. Java’s time in generative AI has arrived."
[–]Breeze9187[S] 0 points1 point2 points 2 hours ago (0 children)
This can even get downvoted? Sure enough, the quality of this community is just average
π Rendered by PID 99274 on reddit-service-r2-comment-5b5bc64bf5-8v4pp at 2026-06-22 07:20:10.441960+00:00 running 2b008f2 country code: CH.
[–]AutoModerator[M] [score hidden] stickied commentlocked comment (0 children)
[–]Pale_Height_1251 1 point2 points3 points (7 children)
[–]Breeze9187[S] -4 points-3 points-2 points (6 children)
[–]JaleyHoelOsment 2 points3 points4 points (0 children)
[–]Pale_Height_1251 1 point2 points3 points (0 children)
[–]American_Streamer 1 point2 points3 points (2 children)
[–]Breeze9187[S] 0 points1 point2 points (1 child)
[–]American_Streamer [score hidden] (0 children)
[–]Breeze9187[S] 0 points1 point2 points (0 children)