Live-Coding with AI: Stop Prompting. Start Building Software Factories
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About this event
We're excited to launch a new format for JUG Oberpfalz: Online Live Coding Sessions!
While our regular JUG meetups will continue to take place locally with talks in German or English, this new online format will always be held in English so that developers from everywhere can join.
This is our very first online live coding session and if the format proves successful, many more will follow.
You can participate live through the provided YouTube stream. No registration beyond Meetup is required.
Most importantly: please ask questions! Whether you're an AI expert or just curious, feel free to ask as many questions as you like. There are no stupid questions, live discussions are what make these sessions valuable.
Since the stream will be on YouTube, you will not be able to ask questions through audio and video, but only through chat.
This session will be hosted by Johannes Rabauer. Most episodes will feature guests from the Java and AI community. For our first session, Johannes is joined by Ingo Eichhorst.
Another small difference to the usual sessions: This session will be recorded and can be viewed later on.
Session Topic
AI can write code. Most developers have seen that.
The harder question is: How do we make AI produce good software consistently?
In this live coding session, we'll explore the idea of Software Factories for Java development.
Instead of asking an AI to implement a feature and hoping for the best, we'll first define what a successful result looks like. We'll establish quality criteria, create ways to evaluate the implementation, and then let AI do the coding.
Using a real open-source Java project, we'll implement a new feature while exploring a different approach to AI-assisted software development. The goal is not to build an autonomous developer—the goal is to build a repeatable engineering process that consistently delivers useful results.
What we'll do
- Select a real feature to implement
- Define the desired outcome
- Establish measurable quality criteria
- Let AI implement the feature
- Evaluate the result against our criteria
- Improve the process based on what we learn
Topics
- Software Factories
- AI-assisted software development
- Evaluation-driven development
- Claude Code and AI agents
- Defining software quality
- Human oversight and feedback loops
- Practical Java engineering
Whether you're a Java developer, software architect, engineering leader, or simply interested in practical AI workflows, we'd love to have you join us.
See you in the live chat!
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