Scale Agentic Workflows Without Scaling the Overhead

AI coding agents can get a lot done. But if every new issue starts with another blank prompt, another round of context-setting, and another decision about which agent or model to use, you’re still doing a lot of the work yourself.

The next step isn’t just running more agents. It’s building a repeatable way to work with them.

On October 7 at 1:00pm ET, we’ll show how GitKraken Kepler and Insights for Developers can help you turn the agent workflows that work into patterns you can use again and keep improving.

With Kepler, see how to take real issues and pull requests into agent-driven work with the right repo context already attached. We’ll walk through reusable Actions for the work you do over and over. Planning, implementing, reviewing, addressing feedback, or creating your own, so every task doesn’t have to start from scratch.

Then we’ll look at GitKraken Insights for Developers to understand what happens across that work: which models and skills you’re using, how much autonomy agents have, what they cost, and where the results suggest there’s room to adjust.

The goal is to move from “What should I ask the agent this time?” to a development workflow that gets more consistent every time you run it.