Dual Track Agile: Balancing Discovery and Delivery on Your Roadmap

Dual track agile sounds elegant in theory: one track validates what to build (discovery), another track builds it (delivery). Two parallel streams feeding each other continuously.

In practice, most teams struggle with it. Discovery either gets squeezed out entirely (“we don’t have time for research”) or it becomes an excuse for indefinite exploration (“we’re still in discovery”). Neither extreme works.

The problem isn’t the concept—it’s the capacity allocation. Discovery and delivery compete for the same finite resource: your team’s time.

What Is Dual Track Agile?

Dual track agile, sometimes called dual track development or dual track scrum, is an approach where:

Discovery Track: Validates problems and potential solutions before committing to building them. Includes user research, prototyping, experiments, data analysis.

Delivery Track: Builds validated solutions and ships them to users. Includes development, testing, deployment, monitoring.

The tracks run in parallel, with discovery feeding a pipeline of validated work into delivery.

Discovery: Research → Prototype → Validate → (validated idea)
                                                    ↓
Delivery:                                    Spec → Build → Test → Ship

The idea is straightforward: don’t build things that haven’t been validated. Do the validation work ahead of delivery so there’s always a pipeline of good ideas ready to build.

RoadmapOne and the SVPG product model both emphasise this approach. When you give teams outcomes to achieve (not features to build), they need discovery to figure out what solutions might work.

Why It’s Essential for Empowered Teams

If you’re doing outcome-based roadmaps , dual track is non-negotiable.

When the roadmap says “Increase conversion from 15% to 25%,” the team needs to figure out HOW to achieve that. They don’t know in advance which solutions will work. Discovery is how they find out.

Without discovery, you’re back to feature factory mode—building pre-determined features without validating whether they’ll achieve the outcome.

The SVPG model is explicit: empowered teams own problems, not solutions. Owning a problem means validating solutions before building them. That’s discovery.

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The Capacity Problem Everyone Ignores

Here’s what most dual track guidance misses: discovery consumes the same capacity as delivery.

When your product manager does user interviews, they’re not writing specs. When your designer creates prototypes, they’re not polishing shipped features. When your senior engineer evaluates technical feasibility, they’re not writing code.

This isn’t a criticism—it’s physics. You have a finite number of people-hours. Every hour on discovery is an hour not on delivery.

Most teams don’t account for this. They try to do discovery “on the side” or “between sprints.” What actually happens:

• Discovery gets squeezed out entirely when delivery pressure increases
• Discovery happens but delivery slows down, surprising stakeholders
• Discovery generates a pile of validated ideas that take years to build
• Team members burn out trying to do both tracks full-time

The solution isn’t to abandon discovery. It’s to budget for it explicitly.

Budgeting Discovery Capacity

How much capacity should go to discovery? It depends on your context, but here’s a starting framework:

For Established Products (Product-Market Fit Achieved)

Discovery: 15-25% of capacity Delivery: 75-85% of capacity

Most work is executing on known approaches. Discovery is for incremental improvement and exploring new opportunities.

For Growth-Phase Products

Discovery: 25-40% of capacity Delivery: 60-75% of capacity

More validation needed as you scale and enter new markets. Higher investment in understanding new customer segments.

For Early-Stage Products (Pre-PMF)

Discovery: 40-60% of capacity Delivery: 40-60% of capacity

You’re still finding what works. Heavy investment in validation before committing to build.

For a deeper dive, see allocating discovery capacity .

The WIP Problem

Here’s the subtle trap: discovery generates work in progress.

Every validated idea waiting to be built is WIP. If your discovery track is validating ideas faster than delivery can build them, you’re accumulating a backlog of validated-but-not-built work.

That WIP has costs:

• Staleness: A validated idea from 9 months ago may no longer be valid
• Context switching: When you finally build it, everyone has to re-learn the context
• Opportunity cost: You validated things you never built instead of validating things you will build

The solution is to cap your discovery pipeline. Don’t validate more than you can build in the next 1-2 quarters.

For more on managing WIP, see why WIP limits matter .

The Near-Term Focus Principle

This leads to a critical principle: only do discovery on things you’ll implement soon.

If an outcome is 6 months out, don’t start discovery now. The world will change. Customer needs will evolve. Your understanding will shift. Discovery done too early becomes stale.

Instead:

• For Now outcomes: Discovery should be wrapping up, delivery starting
• For Next outcomes: Discovery should be active
• For Later outcomes: Discovery is premature

This keeps discovery focused and prevents the pile-up of validated ideas that never get built.

How Dual Track Appears on the Roadmap

The roadmap should show outcomes, not discovery activities. But timing should account for the discovery phase.

For example, if Q2 is when you’ll pursue “Improve retention,” discovery for that outcome should be happening in late Q1.

Q1:
- Deliver: Q1 outcomes (shipping)
- Discover: Q2 outcomes (validating)

Q2:
- Deliver: Q2 outcomes (shipping)
- Discover: Q3 outcomes (validating)

This creates a steady pipeline where discovery feeds delivery one quarter ahead.

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The “Just a Few Hours” Fallacy

Teams often underestimate discovery effort.

“It’s just a few user interviews—maybe 10 hours total.”

But it’s never 10 hours. There’s recruitment, scheduling, preparation, synthesis, socialisation, iteration. What was “10 hours” becomes 40.

Then multiply by the team members involved. The PM spends 20 hours. The designer spends 15. A senior engineer joins for feasibility assessment, that’s another 10.

What sounded like “just a couple of hours from a few senior folks” is actually 45+ person-hours—more than a full sprint’s worth of delivery capacity for one person.

I’m not saying don’t do it. I’m saying budget for it honestly.

Structuring the Week

One practical approach: dedicate specific time to each track.

Option 1: Discovery Days

Monday and Tuesday are discovery-focused. Wednesday through Friday are delivery-focused.

This creates clear boundaries and prevents discovery from bleeding into every moment. For more approaches, see product discovery in roadmaps .

Option 2: Discovery Sprints

Alternate sprint focuses: Sprint 1 is discovery-heavy, Sprint 2 is delivery-heavy.

This allows deeper immersion but may create pipeline gaps.

Option 3: Dedicated Discovery Role

A PM or designer is primarily responsible for discovery, feeding validated work to the team.

This centralises discovery but can disconnect the team from user understanding.

Option 4: Continuous Small Allocation

10-20% of every sprint is discovery, spread across the team.

This maintains continuous flow but discovery can get squeezed.

There’s no universally correct structure. What matters is being explicit about the allocation.

Making Discovery Feed Delivery

The handoff between discovery and delivery is where dual track often breaks.

Good Handoff

Discovery completes with:

• Clear problem statement (validated)
• Solution hypothesis (validated with prototypes/experiments)
• Success metrics (defined)
• Technical approach (feasibility confirmed)
• Open questions (acknowledged)

Delivery begins with clear direction and confidence that the work is worth doing.

Bad Handoff

Discovery completes with:

• Vague conclusions (“users seem interested”)
• Multiple competing solutions (“we could do A, B, or C”)
• No success metrics (“we’ll know it when we see it”)
• Technical uncertainty (“engineering will figure it out”)

Delivery begins with confusion and inevitably revisits discovery questions.

The Discovery Artifacts

What should discovery produce?

1. Problem validation: Evidence that the problem is real and worth solving
2. Solution hypothesis: A specific approach to try first
3. Prototype/mock-up: Something concrete enough to build from
4. Success criteria: How we’ll know if it worked
5. Risks and unknowns: What we’re still uncertain about

If discovery can’t produce these, it’s not ready to hand off. If it produces more than these, it’s probably over-engineering the handoff.

Common Dual Track Failures

Failure 1: Discovery Is Optional

When delivery pressure rises, discovery gets cut. “We’ll validate after we ship.”

You won’t. And you’ll ship things that don’t work.

Fix: Protect discovery capacity explicitly. It’s not optional overhead—it’s how you ensure delivery is worthwhile.

Failure 2: Endless Discovery

“We’re still in discovery” becomes a permanent state. Ideas are researched but never built.

Fix: Time-box discovery. If validation isn’t complete in X weeks, make a decision with available information.

For more on this, see time-boxed discovery .

Failure 3: Discovery Detached from Delivery

Discovery happens, but the team building the solution wasn’t involved. Context is lost. Misunderstandings occur.

Fix: Include delivery-track people in discovery. Engineers joining user interviews. Designers seeing build constraints.

Failure 4: Sequential Not Parallel

Discovery finishes completely before delivery starts. You get perfect validation but slow throughput.

Fix: Stagger the tracks. As one outcome moves from discovery to delivery, the next outcome enters discovery.

Failure 5: No Capacity Accounting

Both tracks run “full speed” without acknowledging the trade-off. Burnout ensues.

Fix: Budget capacity explicitly. If you’re doing 30% discovery, you’re doing 70% delivery. Not 100% of both.

Measuring Dual Track Health

Track these indicators:

Discovery Health:

• % of delivered features that were validated
• Time from discovery start to delivery complete
• Validation to delivery ratio (ideas validated vs ideas built)

Delivery Health:

• Delivery velocity (story points, features shipped)
• Time from validated idea to production
• Rework rate (work that needed revisiting due to poor validation)

Overall Health:

• Outcome achievement rate (did shipped work achieve intended results?)
• WIP age (how old are your validated-but-not-built ideas?)

If validation-to-delivery ratio is high, you’re validating more than you build—reduce discovery or increase delivery capacity.

If rework rate is high, discovery isn’t sufficient—invest more in validation.

Conclusion

Dual track agile is essential for empowered product teams pursuing outcomes. You can’t achieve outcomes without figuring out what solutions might work. That’s discovery.

But discovery isn’t free. It consumes the same finite capacity as delivery. Teams that ignore this end up with squeezed discovery, burned-out teams, or piles of validated ideas they never build.

The solution:

• Budget discovery capacity explicitly (15-40% depending on maturity)
• Focus discovery on near-term outcomes (not 6+ months out)
• Time-box discovery to prevent endless validation
• Handoff clearly between tracks
• Monitor the pipeline to keep it flowing

Dual track isn’t two tracks running independently. It’s one team balancing two essential activities with finite capacity. Get the balance right, and you ship things that actually work.