AI features don't behave like static software. The prompt, model, or threshold that works today may not work tomorrow, and most teams have no way to change it without a full redeploy.
Join us for a live demo of AI Configs, Harness's answer to controlling AI behavior with the same discipline you apply to feature releases: progressive rollout, experimentation, and kill switches, all governed by the same pipeline as the rest of your delivery process.
What you'll take away:
- Why hardcoded prompts and models create hidden release risk, and why AI behavior needs the same governance as any other production change
- How to adjust AI behavior at runtime (prompts, models, routing) without a redeploy, and propagate that change globally in under a minute
- How progressive rollout and experimentation let you validate AI behavior with real users before committing to it broadly
- How kill switches and rollbacks give you an instant safety net when AI behavior drifts
- How to close the governance gap between the code your teams ship and the AI they run, all through one pipeline
We look forward to seeing you there!
Questions? Contact [email protected]
