An AI agile coach for engineering teams
Aurora Coach is agile coaching software: an AI coach that runs a continuous improvement loop with every team, every period. It does what a good coach does between visits, and it never decides over the team's head.
| AI features in meeting tools | Aurora Coach | |
|---|---|---|
| AI’s role | Summarizes the meeting | Analyzes, recommends, follows through |
| Scope | One ceremony | Six domains, the whole practice |
| Grounding | The transcript | Team context plus delivery signal |
| Decisions | Not its job | Never the AI’s. The team votes and commits |
| For coaches and scrum masters | Another tool to run | Leverage: one coach can support many more teams |
Wondering about human coaching? That comparison has its own page: an AI coach is not a replacement, it is the habit between engagements. And our advisory couples expert human coaches with the product.
What is an AI agile coach?
An AI agile coach is software that does the recurring work of coaching: gathering context from the team, analyzing how the team is working, recommending small concrete improvements, and following up on whether they happened. Aurora Coach does this as one improvement loop per period for every team, across six domains of team effectiveness. The AI never decides; the team votes and commits.
Does an AI coach replace scrum masters or agile coaches?
No. Human coaches are best at facilitation, hard conversations, and organizational change. What an AI coach changes is the economics of the routine work: every team can run a real improvement loop every period without waiting for a coach to be available. A coach working with Aurora Coach can support far more teams than they could alone, and our advisory services couple expert human coaching with the product.
How does Aurora Coach make its recommendations?
Each period the team answers a short check-in, and Aurora Coach combines that with delivery signal from the tools the team already uses. The analysis covers six domains of team effectiveness and ends in a handful of concrete recommendations. The team discusses, votes, and commits to a few. The next period starts by looking at what changed.