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September 29, 2026 · 6pm CET / 9am PT

Put AI to work in real Java systems. Spot shipping code you can't trust.

AI works great in a demo, then falls apart on your real codebase. In this episode, three practitioners show you how to modernize large legacy systems with AI, get AI agents to actually ship working code, and get AI writing code that passes your own review. Live demos, real code, honest about what still breaks.

AI works in demos. See how three practitioners modernize legacy systems, run coding agents, and get AI-written code through review.

Live + Q&A

Save your spot in under a minute.

Register once to join Episode 8 live on September 29 and get the recording and materials even if you cannot attend.

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What are the talks about

Three practical answers to the same problem: making AI work on real code.

AI agents02

More With Less: A Lean Software Factory Made of Rival Coding Agents

Rival coding agents, one shared context, and independent review gates shipped a real MVP in three days without a human at the keyboard. Baruch opens the rules, review layers, and failures behind the software factory.

AI-assisted coding03

My Standards, Their Keyboard: Four AI Processes, and Then There Was One

Five ways of working with AI, four dead ends, and one process that produced code worth shipping. Pasha shows the prompts, artifacts, and decision-making workflow he now uses in real Java development every day.

What you will walk away with

A clearer way to put AI to work in real Java systems.

Episode 8 is about the AI questions Java teams actually hit in production: what to build on, what to hand off, what to keep human, and where AI still cannot be trusted.

Live + Q&A Bring your own situation and get real answers from three practitioners, live on the stream.

Three moves you can use on Monday.

  1. 01Modernize Specs AI can work from. Know where automation stops.
  2. 02Agents Run a team of AI agents that ship real code. Shared context. Independent review gates.
  3. 03Ship Code that passes your review. You decide. AI types.
Bring your case to live Q&A
01

Modernize real legacy systems with AI. Real cases.

Get a model for AI-driven modernization at scale. Learn how to write specs an agent can actually use, how much generated code is worth reviewing, and where the approach still breaks, including projects that got thrown away.

Legacy systemsSpecsReview scopeReal cases
02

Run a team of AI agents that ship real code.

See how rival coding agents share one context and check each other through independent review gates, so they ship working software instead of spinning in endless bot loops. You'll leave with a practical pattern for building your own lean setup.

AI agentsShared contextReview gatesLean setup
03

Get AI writing code that passes your review.

Learn the workflow that keeps your standards in AI-generated code. You make the decisions and AI does the typing, so you stop shipping code you would reject and stop losing time fixing it.

AI-assisted codingCode reviewDeveloper workflowHuman decisions

Headliners

The people who build the tools you use every day.

Simon Martinelli
Speaker 01

Java Champion · Oracle ACE Pro · Creator of the AI Unified Process

Simon Martinelli

Simon has three decades as an architect, consultant, and trainer, and has spent the last two years modernizing large business applications with AI across multiple teams and legacy systems. He will show what actually works at scale, what quietly wastes time, and honestly where AI still cannot do the job.Simon is an architect, consultant, and trainer with three decades of experience. Over the past two years, he has modernized large business applications with AI across multiple teams and legacy systems. At JRush, he explains what works at scale, what wastes time, and where AI still cannot do the job.

AI Unified Process

AI modernization, legacy systems, spec-driven development

Baruch Sadogursky
Speaker 02

Head of Developer Relations, Port.io · Java Champion · Co-author, “Liquid Software” & “DevOps Tools for Java Developers”

Baruch Sadogursky

Baruch did Java before generics, DevOps before Docker, and DevRel before it had a name — and led DevRel at JFrog from ten people to a $6B IPO. Obsessed with how AI agents actually write code, he built a “software factory” of rival AI agents that shipped a real MVP with no human at the keyboard. His session opens the coding-policy plugin, the review gates, and the failures behind it — a practical pattern you can build yourself.Baruch built a “software factory” of rival AI agents that shipped a real MVP with no human at the keyboard. At JRush, he opens the coding-policy plugin, review gates, and failures behind the setup.

Port.io

AI agents, context engineering, agentic workflows

Pasha Finkelshteyn
Speaker 03

Developer Advocate, BellSoft

Pasha Finkelshteyn

Pasha is relentless about code quality. After burning through four AI workflows that did not hold, he found the one that does, where AI writes but the decisions stay his, and nothing ships below his bar. His talk puts all five on screen, with the artifacts from real work.

Alpaquita Linux Liberica JDK BellSoft

AI-assisted coding, code review, developer workflow

Free Java web conference

Two focused hours. A lot less AI hype.

JRush is a free BellSoft series with expert talks, live Q&A, and technical materials for teams building, running, and securing Java applications. Episode 8 is about putting AI to work in real Java systems, from rival coding agents shipping real software, to modernizing legacy at scale, to writing code you would actually ship.

JRush workbench
Agent Shared context
Inspect service dependencies
Apply migration
Run tests
ReviewGate.java
ChangeSet.java
1package software.factory
2
3public class ReviewGate {
4
5  private final Reviewer reviewer;
6  private final Policy policy;
7
8  public Decision verify(ChangeSet changes) {
9    return reviewer.review(changes, policy);
10  }
11}
Review passed

Free Java web conference

Save your spot for Episode 8

September 29 6pm CET / 9am PT Live + Q&A
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Free Recording included Materials included
AI Unified Process BellSoft Liberica JDK Alpaquita Linux

FAQ

Yes,
free.

Register to get the broadcast link before JRush. The recording will arrive after the event.

JRush is a free online series about Java development, cloud-native engineering, and the practical tools and workflows modern Java teams use.

Yes. Registration is free. Sign up and you will get the live join link, plus the recording and materials afterward, whether or not you make it live.

Java and Spring developers, DevOps and platform engineers, architects, and technical leads working with or deciding on AI in real Java systems, from greenfield to legacy.

The live join details for September 29, a calendar invite, and after the event the full recording and materials from all three talks, even if you cannot attend live.

Final call

Save your spot. Bring your hardest AI question.

Register for JRush Episode 8. Three talks, live demos, and a Q&A where you can put your real AI problems to the people who have solved them. Free. September 29.

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We will send the live join link and calendar invite before Episode 8, then the recording and materials afterward.

AI agentsLegacy modernizationAI-assisted codingLive Q&A