200+ BETA users already signed up in just one month 🎉
After speaking with a ton of founders and developers, we kept hearing the same issues again and again:
• Requirements start out unclear, causing confusion later
• Work gets scattered across tools, docs, and notes
• AI coding tools often generate code that’s messy or incomplete
• Existing workflows slow teams down more than they help
So we built ScrumBuddy, an all-in-one AI platform designed to act like a full development team, and take your idea from a rough concept to production-ready code.
What ScrumBuddy handles for you:
- Robust requirements: transforms loose ideas into structured, detailed specs
- Backlog grooming: quickly create and refine user stories
- Story Quality Score: checks for gaps and missing pieces
- UI Generator: turns stories into usable front-end layouts
- Automated Backend (Claude): generates backend logic and APIs
- AI PR reviews + GitHub integration: catches issues before they reach production
The mission is simple: save costs, reduce friction, eliminate context switching, and help you ship real, working products much faster.
👉 Register for the beta: https://scrumbuddy.com/
If you try it out, we’d love your feedback. It helps us shape ScrumBuddy into the most powerful companion for founders, solo devs, and small teams.
Getting 200 beta signups is a great early signal — the real clarity usually comes from who shows up again.
At this stage, what’s the one behavior you’re watching to decide if this is real demand — users activating quickly, coming back for a second session, or asking for specific features?
Totally agree! The number matters far less than who comes back and why.
The behaviour we’re watching most closely is whether users push through requirements friction and then reuse the output. If someone takes a rough idea, lets ScrumBuddy interrogate it, produces a solid spec, and then comes back to refine another story or trigger code from it. Ideally, we'd like users to go from end-to-end and generate their code, but there is a cost involved so we understand their hesitation.
Feature requests matter too, but less in isolation and more in where they appear in the workflow. Requests that show up after users have felt the cost of bad requirements are very different from “nice to haves.”
In your experience, what’s been the earliest behaviour that told you something had real pull?
For me, the earliest real pull shows up when users start reframing their own work around the tool, not just using it.
Concretely: when someone returns with a second problem that’s better structured than the first — fewer ambiguities, clearer constraints, or explicitly referencing how the tool helped last time — that’s usually the signal.
Another strong one is when users accept a bit of friction (waiting, limits, manual steps) without complaining because the output is “worth it.” At that point, it’s no longer curiosity — it’s utility.
Congrats on launching! I’m also building my MVP and this is very inspiring. What was the hardest part of validation for you?
Thanks, Alexandr, and congrats on building your MVP too! That phase is exciting and brutal at the same time.
The hardest part of validation for us wasn’t getting interest, it was validating the right problem. Early on, people were enthusiastic about “AI building software faster,” but that signal is misleading. Everyone likes speed. Very few can articulate where things actually break.
What took the most work was digging past surface feedback and identifying the root cause: poor requirements are what quietly kill most projects. Not code quality, not tooling, not even AI capability. Once we focused validation on where teams lose clarity, the conversations got much more honest and actionable.
Another challenge was resisting premature validation from prototypes. It’s easy to validate a demo. It’s much harder (and more valuable) to validate whether something would survive real-world complexity: changing scope, edge cases, hand-offs, and long-term maintenance. We're using this beta as a trial to figuring that out.
Our biggest learning: validation isn’t about “would you use this?” it’s about “what breaks when you try to scale this?” The moment we reframed questions that way, the signal got much stronger.
Happy to share more if it helps, and good luck with your MVP. That grind is worth it.