Snapshot

Challenge

Reefkeepers were splitting decisions across isolated forums, chat groups, and static care guides. Help existed, but advice quality and context were inconsistent, and there was no connected system to track coral growth, pricing trends, and collection strategy.

Objective

Create an AI-assisted reefkeeping platform that combines trusted support, community intelligence, and personal collection tracking in one experience.

Product Direction

• Designed a dual-purpose product model that combines AI guidance with experienced community insight in one workflow.
• Assistant mode for fast guidance on reef care, equipment, and issue diagnosis.
• Community mode for thread-based support, peer learning, and specimen exchange.
• Structured responses around context (tank state, species, history) instead of generic one-off prompts.
• Built trust cues directly into the UX so users can evaluate recommendations with confidence.

Design Constraints

• Delivered v1 in an 8-week solo sprint from design through development.
• Designed for a broad user spectrum from beginner to advanced reefkeepers.
• Kept v1 intentionally focused on guidance, community, and tracking loops to maintain execution quality.

Key UX Decisions

• Kept assistant and community in one product flow so users can move from quick guidance to peer validation without context switching.
• Framed assistant responses around tank context and history to reduce generic advice patterns.
• Positioned collection tracking as part of the decision flow, not a separate utility, so monitoring and action stay connected.

System Decisions

• Introduced a local LLM strategy that learns from validated community patterns and interaction trends.
• Designed a collection tracker for:
  • Growth monitoring
  • Price movement awareness
  • Personalized specimen suggestions
• Established modular UI blocks so assistant, community, and tracking workflows can evolve without redesigning the full product.

Outcome Signals

• Unified advice, community context, and collection intelligence into a single workflow.
• Reduced friction for users moving between learning, asking for help, and taking action.
• Prepared a scalable base for future recommendation quality improvements and richer marketplace/community capabilities.

V1 Scope Decisions

• Deferred third-party integrations to keep v1 stable and coherent within the solo timeline.
• Prioritized depth in core workflows over breadth of integrations.

Build Notes

• Delivered v1 end-to-end solo across product direction, UX/UI, and frontend implementation.
• Built reusable UI blocks and shared interaction states so assistant, community, and tracking flows stay consistent.
• Structured the app for future expansion without requiring a full redesign of core surfaces.

Next Phase

• Add integrations with external reef applications and tools.
• Extend ReefBrain into reef hardware workflows to bring AI guidance closer to real-world tank operations.