Developer AI Ranges

What are Developer AI Ranges?

Developer AI Ranges let your developers practice building safely alongside an AI assistant, using a normal tech stack from IDE through to deployment. Instead of learning about AI assistants in theory, your team works in a realistic environment with an assistant built in, so they experience both the benefits and the risks first-hand.

You learn how different AI models and assistants behave when you build with them, how to work with them effectively, where they go wrong (hallucinations, mistakes, copied or rewritten code), and what they cost to run.

Before you start

• Available on Immersive One Advanced.
• No setup or configuration is needed. Each range gives you a scenario and a pre-built environment to work from.
• Because ranges are provisioned ahead of time, exercises are typically scheduled rather than started on demand.

What you'll get out of it

• A scenario run as a team, with a choice of AI provider.
• A live view (for facilitators) of how teams are progressing.
• A debrief at the end with high-level metrics: cost and token usage broken down per team and per model, and tasks completed. You can also export this data from Data Explorer.

How to take part

1. Open the scenario overview page before joining.
   
2. Join the exercise to be taken into your range.
   
3. Work through the exercise in the development environment, using the AI assistant alongside your normal tools (IDE, deployment pipeline, and the deployed application).
   
4. Review your debrief afterwards, including cost and other metrics such as tasks completed.
   

Note: during the exercise you won't see whether your answers are right or wrong. Your team decides on its best submission, and feedback comes in the debrief.

What you'll see on screen

The key screens on each path, and what to look for on them.

Scenario page (facilitator). Before you run anything, opening a scenario shows its details in one place: the scenario, the infrastructure it stands up, the MITRE ATT&CK mappings it covers, and the AI providers available. Use this page to decide whether a scenario fits your team before you configure it.

Configuration form (facilitator). Where you set up a run: choose your teams, set the schedule, and pick your AI provider. Once you submit, the platform handles scheduling – you don't start the exercise manually.

Facilitator view (during the exercise). A view-only mode showing live team scoring, cost, and token usage as teams work. From here you can watch progress, troubleshoot, and join the exercise to see how each team is doing inside their range.

Developer range (participant). Where you do the exercise: a normal development stack – an IDE, a deployment pipeline, and a deployed application – with an AI assistant built in. You work through the scenario using the assistant as you would in your real workflow. You won't see whether individual answers are right or wrong here – that's by design.

Cost and token usage. Each team has a cost cap per exercise. As a team works, its token usage counts toward that cap. If the cap is reached, the AI assistant pauses and the team continues in "human mode" for the rest of the range. Keep an eye on usage so you're not caught out.

Debrief page. Shown at the end. High-level metrics including cost and token usage broken down per team and per model, and tasks completed. This is where feedback lands. You can export the same data from Data Explorer.

Troubleshooting

Limitations

• Release one covers the developer and offensive personas only.
• Detailed after-action reporting for the AI parts is limited today, beyond the debrief page and Data Explorer export.