AI agents for Scrum teams, pulling real stories off your board while you learn to run them.
We deploy AI agents for Scrum teams, and the people on those teams end up with a skill the market is short of. Developers, Scrum Masters, testers: whoever learns to run agents and show the gain in the board is the person who gets kept, promoted and recruited. That is a skill, not a threat. You point us at one machine, we load the agents and attach them to your board, and they start pulling stories off your backlog. The nine sprints of trial and error are already behind us, so you start from the configuration rather than the experiment.
Free for beta participants. Places are limited by how many teams we can support at once.
What happened on our own team
Nine weekly sprints, June to August 2026, measured in Jira. Our agent, Sophie Hermes, worked the same board as everyone else. These are our numbers, not a vendor projection, and we wrote up the whole thing in our AI agent series.
Agent story points
3 → 24
Per sprint, sprint 146 to sprint 154. The first completed story landed in the first week.
Team throughput
+73%
44 to 76 completed points, first sprint to last. Human-assigned output ended higher than it started, not lower.
Share delivered by the agent
33.8%
Of assigned story points by sprint 154, up from 7.69%. Capacity the Scrum Master added to the team.
Agent-completed story points per sprint
Sprints 146 to 154 · weekly sprints · 16 June to 11 August 2026
3
5
4
9
9
12
18
18
24
The ramp is the cost of discovery: agent setup, Jira wiring, and learning which backlog patterns feed agents. That is the part we packaged, so you skip the nine weeks. Nobody on the team lost work: human-assigned output ended higher than it started, 36 points to 47. Treat +73% as first sprint to last rather than a steady weekly rate. Counts are assignment-based, so they measure work handed to the agent, not all AI assistance, and unassigned points sit outside both figures.
Our blog series reports a different count: how many sprint issues the agent created. Creation and completion are tracked separately, so those figures and these will not match.
Source: our internal Human vs AI Delivery Report, Sprints 146 to 154, with Jira as the source of truth. What actually changed over those sprints, including what went wrong.
What you are actually buying
Not this
Nine sprints of your team’s time spent finding a working agent configuration, wiring up Jira, and discovering which backlog patterns feed agents and which starve them.
This
That configuration, deployed remotely onto your machine and your board, plus the backlog work that makes it produce anything at all. The result is a line on your résumé that reads in numbers: agents on the team, AI points rising, throughput up, in the board’s own data.
Why AI agents for Scrum teams work where AI pilots fail
MIT’s NANDA initiative found that 95% of enterprise GenAI pilots deliver no measurable impact on the P&L. Their diagnosis was not model quality. It was brittle workflows and tools that sit to one side of how work actually moves.
Which makes this a Scrum problem before it is an AI problem. Companies buy a static tool, change nothing about how work flows to it, and then conclude the technology does not work.
An agent is only as productive as the stories it is handed. That is why the backlog step below decides the outcome, and it is the step almost every AI rollout skips. Backlog quality is something your team owns, not something a vendor can supply, which is exactly where the fear turns into leverage.
How it works
Five steps. Four of them are ours. The operating loop we run is documented publicly, so none of this is a black box.
You point us at a machine
One box inside your environment. No procurement cycle, no new platform to buy, nothing for your team to install.
We load the agents remotely
Setup is our work, not your team’s. They stay on delivery while we do it.
We attach them to your Jira board
They work where the team already works. No parallel tool, no second place to check.
Agents start taking stories
Off the same backlog as everyone else, assigned the same way. Their output lands in your velocity data as AI points, so you can see exactly what came from where.
We work the backlog with you
Well-formed stories are what make agents productive. This is your team’s work rather than ours, it is the step most AI efforts skip entirely, and it is the reason the numbers above happened at all.
Why this matters to you
Your executives are asking for an AI story and most teams have nothing measurable to show. Whoever can stand up in a review and say that agents delivered a third of the team’s points this sprint, and that human output did not drop, is the person that organisation does not want to lose.
For a developer, this is the difference between using a chatbot in another tab and being the person who put agents on the board and made them productive. For a Scrum Master or Product Owner, backlog quality becomes a throughput input you control. Either way it is the part the automation cannot do for you, and it is the reason this is a skill rather than a replacement.
If you train or coach teams, this is a data-backed answer to the fear conversation blocking them, and a coachable, measurable lever. What you can promise is a team everyone wants to hire.
What happens after you sign up
Three steps, and none of them is a sales call.
We reply to you personally
A real person from the team, not an automated sequence. We will ask a few questions about your board and your backlog.
A short call to check fit
Thirty minutes. If your backlog is not ready for agents, we will say so and tell you what would need to change. That is useful either way.
We schedule your first sprint
You point us at the machine, we load the agents and attach them to your board. Your team keeps delivering while we do it.
A challenge to change
Resistance to this is reasonable and it is also expensive. Three things move a person from resistance to action, and they are worth naming plainly.
Attitude. An attitude of resistance keeps you stuck, and the useful question is why it is there rather than how to argue you out of it. Motivation. People move for what matters to them personally, not for someone else’s throughput target. Responsibility. You have a duty to build something better for yourself, your family and the people you work with, and that includes not being the person who sat out the change.
Every industry has the people who resisted the last one. This is the moment where the fear is still convertible into a skill, and the beta is free while that is true.
Prove it on your own board
The question you actually have
The figures on this page come from one team, ours, over nine sprints. The question you have is not whether it worked for us. It is whether it works on your board, with your backlog, on your team.
The beta is built to answer that question, on your own board and in your own Jira data, at no cost. We are not asking you to trust our curve. We are giving you the means to produce your own.
Who these AI agents for Scrum teams suit
AI agents for Scrum teams only work where there is a real backlog in Jira to pull from. If the backlog is thin or the board is decorative, the agents will have nothing to take and this will not work.
Developers, Scrum Masters, Product Owners and coaches, rather than procurement teams. If it takes six months of committee approval to put one box in your environment, the beta is not the right moment to try this.
Questions
What does the beta cost?
Nothing. Beta participants take part free. The beta exists to prove the system on real teams and real boards, and your results are what let us do that for the teams who come after you. That is worth more to us right now than a fee.
Will an agent make my role redundant?
The opposite is the argument on this page, and the data is the reason. Someone has to decide what an agent works on, review whether its output is good enough to close, and work out how the team changes around it. None of that gets easier as the agent gets better, and all of it is work your team does rather than work the agent does.
Does this replace team members?
It did not on our own team. Human-assigned story points ended the nine sprints higher than they started, while the agent share of assigned work rose from 7.69% to 33.8%. What we can say is that human output did not fall as the agent took on more.
What we cannot honestly claim from one team is that the same holds everywhere, which is part of what the beta is for.
Do we need to change tools?
No. The agents attach to your existing Jira board and appear in your existing velocity data. If you are on a different tracker, tell us when you sign up. That is useful information for us either way.
How much of our team’s time does this take?
Setup is ours. The backlog work in step five needs your Product Owner, because it is a conversation about your stories and nobody outside your team can have it for you.
What if it does not work on our team?
Then we will have learned something worth knowing and you will have an honest answer about your backlog, which is usually the real finding. We would rather hear a no with a reason than sell you a maybe.
Claim a free beta place
We are taking a limited number of teams into the free beta for AI agents for Scrum teams. Developers, Scrum Masters, Product Owners, coaches with a team that fits. Leave your details and a real person will get back to you. No commitment, no cost, and if it is not a fit for your backlog we will tell you that too.