Next month we’re launching a platform we’ve been quietly building for a while — but before talking about the product itself, I wanted to share the real story behind why we built it.
Over the past month, more than 200 developers and founders joined our Beta list. Most of our time since then has been spent in calls, DMs, and long user interviews trying to understand a simple question:
“Why does it still take so long to turn an idea into a working product — even with all the AI tools available today?”
What we found was surprisingly consistent across teams, solo devs, and early-stage founders.
đź“ť 1. Requirements Are Still the Silent Bottleneck
Most people assume coding is the slow part.
But again and again, devs told us:
- I don’t know if my requirements are complete until something breaks.
- We start building and realize half the details were missing.
- Stakeholder to developer translation is still… messy.
Ambiguous requirements were causing delays, rework, and sometimes entire feature rewrites. It’s interesting because this is one of those problems developers know exists but rarely frame as the real cause of slowdown.
Turns out, the cost of vague requirements isn’t just confusion — it compounds as the project grows.
🔧2. Tools Are Everywhere… and That’s the Problem
One developer showed us their setup: Notion for notes, Jira for tasks, Draw.io for flows, Figma for UI, and three different AI tools for generating snippets.
All useful tools — but together they create fragmentation.
Every jump between tools is a small interruption, and those interruptions pile up:
- Notes get outdated
- PRD changes don’t sync with tasks
- UI decisions get lost
- AI output lives in random chat windows
Developers told us they lose hours every week just finding where things were written.
Context switching might be the most underrated productivity killer in software.
🤖 3. AI Helps… Until It Doesn’t
This one was universal.
Everyone uses AI now — and everyone has stories about it producing:
- Missing logic
- Wrong assumptions
- Unusable code
- Or outputs that “kinda” help but still require rewriting
AI is great at generating code, but not great at understanding the full ecosystem of a feature.
And without context, the AI output becomes shallow. Many devs described it as “copy/paste with extra steps.”
The real bottleneck wasn’t code generation — it was building the right thing, in the right structure, with the right context.
🛠️ 4. Workflows Meant to Help Often Slow Everything Down
A lot of teams said something like:
“Our workflow is more work than the actual work.”
When your process involves updating Jira, writing requirements, syncing design, documenting APIs, and then coding — every step becomes a chance to lose alignment.
The tools aren’t the problem.
The distance between them is.
🧩 Why We Started Building a Unified System
After enough conversations, a pattern was clear:
Modern development isn’t slowed down by coding.
It’s slowed down by everything around coding.
So we started building a platform — which we’re calling Scrum Buddy — to connect all those steps into one guided flow. Think of it like simulating the work of a small dev team around you:
- Turning your idea into clear requirements
- Refining user stories
- Checking story completeness
- Generating UI
- Building backend logic (with Claude)
- Reviewing PRs via GitHub
Not as a replacement for developers — but as a way to reduce chaos and give builders a smoother path from idea → production.
We’re not sure we’ve solved it perfectly yet. That’s why we’re sharing everything openly and asking for feedback while we build.
CHECK OUT SCRUMBUDDY : https://scrumbuddy.com/
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