Tech Spec — detailed requirements
- ·Mobile web app, entered from a shared link.
- ·Magic-link authentication (email, no password).
- ·Assessment calculations come from third-party APIs (Human Design, astrology, Enneagram). Work Skills via a licensed source; Strength via an in-house assessment under validation.
- ·Only the final Clarity Code report is AI-generated; all other results are computed or templated.
- ·No payment in V1.
- ·Coach view = email/SMS notification + a basic web dashboard with notes and transcript upload.
- ·Assessment order: Energy → Motivation → Values → Work Skills → Strength → Clarity Code.
LCP under 2.5s on a mid-range Android. No layout shift on bodygraph render.
WCAG 2.2 AA. Every assessment screen reachable by keyboard, screen-reader labeled.
Every answer autosaves. Cold-resume on any device using the user's account.
Birth data and answers are personal — encrypted at rest, never used for marketing.
One focal per screen. No notification badges, no streak mechanics, no upsell mid-flow.
Clarity Code report is structured so new chapters can be added without redesign.
In-house Strength assessment may not hold up vs. the original
Run full codes with and without it; compare resonance and accuracy.
People drop off before finishing all five
Instrument step-by-step completion; watch Energy→finish conversion against the ≥70% goal.
Third-party API cost/latency/availability at volume
Load + cost modeling against expected usage; define fallback behavior.
AI report reads generic or inconsistent
Review sample reports for voice and accuracy; decide generative vs. assembled.
Birth-time precision affects chart accuracy
Decide required vs. optional; validate degraded path if optional.
Predictive Success Assessment licensing terms shift cost or access
Lock pricing, rate limits, and termination terms in writing before V1 commits to it.
Magic-link friction (spam folders, expired links) blocks return visits
Track link-click rates and resume success; tune expiry, sender reputation, and retry UX.
Personal/birth data attracts privacy obligations (GDPR-style requests, breach risk)
Document retention, export, and delete flows; encrypt at rest; legal review before launch.
AI-generated report could surface inaccurate or harmful framing
Human-in-the-loop review for early reports; guardrails + a flag-for-Kate path on every report.
Coach becomes a bottleneck as volume grows
Measure time-per-participant; design dashboard triage and templated notes before scale.
Single-coach assumption breaks when a second practitioner joins
Confirm V1 auth + record ownership model can extend to multi-coach without a rewrite.
Vendor lock-in on Human Design / Enneagram APIs
Abstract integrations behind an internal interface; keep raw inputs so results can be regenerated.
Shared device or family using one link contaminates results
Decide account-per-person rule; detect re-entry and prompt for a fresh session.
Mobile-only assumption may exclude desktop-first users (Kate's referrals, older audience)
Validate device mix in early cohorts; confirm responsive desktop view is acceptable for V1.
Scope creep from 'just one more assessment' requests
Hold the five-step contract; route new ideas to a post-V1 backlog with explicit criteria.
- ·Data sensitivity: birth data + results are personal — privacy, retention, consent handling required.
- ·Email/SMS delivery: transactional provider for magic links and coach + participant notifications.
- ·Shared device / multiple people from one link: handle cleanly.
- ·Accessibility target for the web app: confirm.
- ·Abandoned journeys: re-engagement email, or nothing in V1?
- ·Analytics: completion rate, Energy→finish conversion, 30-day return.

