Downland

Downland is an early-stage platform exploring how retiring farmers can transition land ownership to aspiring farmers. The initial vision included AI-based matching, legal documentation workflows, and full dual-sided user journeys.

Within a four-week delivery window, our goal was not to simulate a complete product, but to define and ship a credible MVP that could validate demand and generate structured leads.

• Team: 4 designers
• Constraint: Demo tied to fixed program completion
• Initial Scope: AI matching, legal tooling, two complete user journeys

Given the timeline and level of product maturity, we made an early scoping decision:
Focus on validating demand and structured intake before attempting automation or legal tooling.

This reduced delivery risk and allowed us to ship something coherent and defensible.

Shipped

• A market-facing marketing site clarifying Downland's value
• A structured intake flow for aspiring farmers
• A framework for future expansion (AI, legal workflows)

Explicitly Deferred

• AI-based matching logic
• Legal documentation tooling
• Complete retiring farmer journey

These were acknowledged as future investments requiring additional validation, legal review, and technical feasibility assessment.

Note: A Desktop prototype was developed as an MVP. Full prototype can be seen on a larger screen.

Input

Research conversations indicated that aspiring farmers lacked clarity on where to begin and needed structured guidance.

Decision

Instead of attempting matching logic, I led the design of a stepped intake questionnaire that:

• Reduced cognitive load
• Produced structured, comparable profiles
• Created usable lead data for Downland

This allowed the MVP to serve both user and business needs without overextending scope.

I owned the aspiring farmer intake experience end-to-end:

• Synthesized interview inputs into intake criteria
• Designed and implemented the stepped questionnaire
• Established a shared component library to reduce UI divergence
• Advocated for accessibility improvements within the existing brand palette

Ownership was integrated within team consensus decisions rather than operating independently of them.

System & Governance Considerations

Brand constraints were respected rather than redesigned. Where tonal similarity in the color palette risked accessibility issues, I adjusted contrast within the brand system rather than deviating from it.

The component library reduced fragmentation across contributors and improved consistency ahead of delivery.

Testing focused on intake clarity and perceived usefulness.

Observation

Users were uncertain whether the milestone timeline presented at the end of the questionnaire represented fixed requirements.

Adjustment

We clarified the timeline as a flexible guide and revised copy to reduce prescriptive interpretation.

No additional features were added at this stage to protect scope.

What Was Not Validated

• Whether structured intake would produce high-quality matches long-term
• Whether the dual-audience value proposition (aspiring vs. retiring farmers) was sufficiently clear
• Downstream operational feasibility of manual matching

If shipped, the next phase would focus on validating lead quality and alignment with business capacity before introducing automation.

The team delivered a focused MVP that:

• Shipped within a fixed timeline
• Reduced scope responsibly
• Preserved brand alignment
• Produced structured intake data usable for future iteration

Client feedback reinforced our ability to avoid scope creep and maintain customer focus.