It's demo day. Claude Code knocked out the data layer migration in two days. So the team pulled in more backend work—cleaner API contracts, better abstractions. Might as well use the time.
The product manager asks: "So what can users do now that they couldn't do before?"
Silence.
"Nothing yet. But the next feature will be way faster to build."
She nods. You can tell she's already thinking about how to explain this to stakeholders.
A full sprint of AI-accelerated work. Users have seen nothing. Feedback: zero. And you're moving faster than ever—on top of assumptions you've never validated.
The Real Constraint Isn't Coding Speed
Your developers can now code faster with AI coding assistants. That's incredible. But faster coding doesn't automatically lead to better products.
The real waste in software development isn't slow coding—it's building the wrong product or feature.
As Marty Cagan from Silicon Valley Product Group puts it:
"The biggest waste in software development is building the wrong product or feature."
Think about it:
- Spending 3 months building a feature users don't want
- Shipping a "complete" solution only to discover it solves the wrong problem
- Building all of Feature A when users only needed 20% of it
Speed amplifies this risk. The faster you can code, the more time you can waste building the wrong thing.
The Solution: Break Stories into Vertical Slices
The answer isn't just faster coding—it's faster learning.
Break your epics into vertical slices: thin, end-to-end features you can ship, test, and learn from quickly.
What's a Vertical Slice?
A vertical slice delivers complete value through all layers of your system:
- It touches UI, backend, database—everything
- It's deployable independently
- It solves a real user problem (even if minimally)
- It enables you to learn whether you're on the right track
Instead of:
Sprint 1: Build entire backend (no user feedback yet)
Sprint 2: Build entire frontend (still no user feedback)
Sprint 3: Integration (finally users can try it)
Sprint 4: Discover it's not what they wanted
Do this:
Sprint 1: Ship smallest end-to-end version (get feedback immediately)
Sprint 2: Iterate based on real user feedback
Sprint 3: Add next most valuable slice
Sprint 4: You've validated direction and built only what's needed
Why This Matters with AI Coding
When issues live as markdown files in your repo (instead of buried in Jira's UI), you can use AI coding assistants to help refine your stories before you build them.
Ask your AI:
- "Break this epic into vertical slices that deliver value incrementally"
- "What's the smallest end-to-end feature we could ship to validate this?"
- "Identify the walking skeleton for this story"
The AI can analyze your story structure and suggest slices that enable fast feedback loops.
Tighten Your Feedback Loop
Kent Beck (creator of Extreme Programming) has a principle worth adapting to product work:
"Make the change easy, then make the easy change... This is true for product work too: make feedback easy, then make the easy improvement."
When your issues are markdown files next to your code:
- AI can help you refine them before development starts
- You ship in days, not weeks
- You learn what works before investing months
- You pivot quickly based on real user feedback
- You reduce waste from building unused features
The result? Smaller batches, faster feedback, better products.
Speed + Direction = Value
Charles Darwin's principle applies to software teams:
"It is not the strongest of the species that survives... It is the one that is most adaptable to change."
Fast coding is strength. But adaptability comes from fast feedback.
Combine them:
- Ship small vertical slices (days, not sprints)
- Get real user feedback quickly (not after months)
- Learn and adapt (before you've built too much)
- Iterate based on what users actually need (not assumptions)
That's how you turn coding speed into product value.
Practical Next Steps
Want to enable faster feedback loops on your team?
- Review your current stories: Are they vertical slices or horizontal layers?
- Break one epic into slices: What's the smallest end-to-end version you could ship this week?
- Use AI to help: If your issues are in markdown, ask Claude or GPT to suggest vertical slices
- Ship and learn: Deploy the smallest slice, get feedback, iterate
The teams that win aren't the ones that code fastest. They're the ones that learn fastest.
What's your experience with vertical slicing or fast feedback loops? Drop a comment below—I'd love to hear how your team balances speed with learning.
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This article is part of a series on context-driven development and enabling adaptive teams. Learn more at imdone.io.
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