Designer-led, AI-built:
Benefits enrollment experience

I designed and built an interactive, state-aware benefits enrollment platform using Lovable, with Claude as a coding partner.

Every product decision — structure, flows, state logic — was mine. AI handled implementation. This project explores what changes when execution is no longer the constraint, and where product thinking becomes the differentiator.

→ Try the prototype

The problem

Benefits enrollment is high-stakes, low-frequency, and confusing. Most platforms treat it like a form to complete rather than a decision to support.

Two user needs shaped the system:

  • Deliberate enrollees need guidance, context, and time

  • Power users want to compare options and choose quickly

More than just UI, this a product architecture problem.

Finding the product

I explored three homepage directions:

  • v1: Dashboard — familiar, but indistinguishable from existing platforms

  • v2: Enrollment flow — added progress + context, but duplicated core information

  • v3: Editorial context layer — removed selection entirely

Decision:

  • Homepage = why and when (context, deadlines, guidance)

  • Plans = what and how (selection, comparison, actions)

Each page has one job.

Key product decisions

1. State-aware system

The product adapts based on where the user is in enrollment.

  • FSA/HSA is disabled until a health plan is selected

  • Advisor messaging evolves from general → specific

  • Notifications reflect real progress

  • No UI references actions the user hasn’t taken yet

Complexity appears only when it becomes relevant.

2. Guided + self-serve paths

The system supports two modes without forcing either:

  • Guided: short assessment → recommendation with reasoning

  • Self-serve: skip directly to plan comparison

If the recommendation doesn’t change based on inputs, the flow is removed.

3. Cost as a running decision

Cost isn’t shown at the end — it updates as users choose.

  • Running cost bar reflects current selections

  • Plan details show projected annual costs (not just premiums)

  • Supports real tradeoff thinking, not surface-level comparison

What AI changed

  • Multi-page prototype in days

  • Rapid iteration across product directions

What it didn’t

  • Product decisions

  • System logic

  • Accessibility correctness

  • Pattern judgment

The outcome

A working, state-aware enrollment system that:

  • Separates understanding from decision-making

  • Adapts to user progress in real time

  • Supports both guided and self-serve behavior

Next
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NetBenefits Navigation Redesign