If you’ve ever been a Scrum Master, you’ll know the ritual.
Sprint ends. Tickets closed (hopefully). Jira updated (mostly). Charts generated (eventually). And then comes the pièce de résistance: the Sprint Review presentation.
A solid hour of assembling burndown charts, checking what actually got deployed, chasing developers for just one more detail, and pulling everything into a vaguely coherent PowerPoint. It’s a labour of love. Or at least… labour.
So naturally, we asked ourselves a simple question:
What if we just… didn’t?
The Problem We All Quietly Accept
Every two weeks, like clockwork, someone takes on the responsibility of:
- Extracting sprint data from Jira
- Rebuilding burndown and burn up visualisations
- Summarising ticket activity
- Cross-checking deployment data
- Formatting everything into a presentation
And while it’s all entirely necessary, it’s also:
- Repetitive
- Time-consuming
- Interrupt-driven (“Quick one, did this actually go live?”)
- Not exactly the best use of a technical team’s time
So instead of accepting it as part of the job, our AI team did what any curious engineers would do.
They treated it as a problem worth solving.
Enter: The AI Sprint Review Assistant
During some quieter hours, read after 6pm when curiosity tends to flourish, the team started experimenting.
The goal?
Automate the entire Sprint Review process.
Not just parts of it. The whole thing.
Here’s what they built.
- Jira Deep Dive using MCP Server tech
The AI agent connects into Jira and:
- Identifies the relevant sprint
- Scrapes all ticket data
- Understands status changes, story points, and completions
No manual exports. No copying and pasting. No wondering which filter was used last time.
- Chart Generation with No Excel Required
From that data, the agent generates:
- Burndown charts
- Burn up charts
Automatically. Accurately. Every time.
And yes, they actually reflect reality, not the presentation-friendly version we sometimes end up with.
- Deployment Intelligence via Octopus
Because a sprint isn’t just about what’s done, it’s about what’s delivered.
The AI integrates with Octopus Deploy to:
- Pull deployment information
- Match it to sprint tickets
- Provide a clear view of what actually made it out into the wild
No more detective work required.
- PowerPoint Generation, Fully Branded
Finally, the magic moment.
With all that structured data in place, the AI generates:
- A fully branded tSB Sprint Review deck
- Complete with charts, summaries, and deployment insights
- Ready to present, share, or archive
No formatting. No slide copying. No last-minute tweaks to font sizes.
The Outcome
What used to take an hour, and several interruptions, now takes effectively nothing.
The Scrum Master doesn’t have to:
- Chase updates
- Build charts
- Assemble slides
Instead, they get a finished, consistent, data-driven presentation every sprint.
The Unexpected Benefit
Yes, we saved time.
But more interestingly, we also gained:
- Consistency with every sprint review following the same high standard
- Accuracy with less human error and more direct use of data
- Transparency with fully auditable, end-to-end visibility
- Focus with the team spending time discussing the sprint, not building the slides
And perhaps most importantly, we freed people up to do work that actually requires people.
A Glimpse of What’s Next
This wasn’t about building a flashy AI demo.
It was about solving a real, slightly annoying, very familiar problem.
And in doing so, we’ve learned something valuable:
The best internal AI use cases aren’t always big and transformational.
Sometimes they’re just about removing friction from everyday work.
At The Software Bureau, this is exactly how we’re approaching AI:
- Start with real problems
- Build practical solutions
- Learn by doing
- Then apply those lessons externally
Final Thought
Sprint Reviews aren’t going anywhere.
But the hours spent building them might just be a thing of the past.
And honestly, no one’s going to miss them.
