The Challenge
Existing health and nutrition apps focus on calorie counting — not health intelligence. Families with different dietary needs have no platform that adapts to each member individually while keeping everyone coordinated.
- No existing platform supports multiple dietary approaches within a single household
- Current tools lack educational depth — they track numbers without teaching the science
- Most apps use shame-based compliance instead of building sustainable habits
- Solo founder building complex SaaS requires a fundamentally different approach
The Solution
I designed and am building NourishIQ — a comprehensive health intelligence platform using AI-augmented development:
- Multi-member architecture — individualized settings within a unified household experience
- Health intelligence layer — data visualization that surfaces meaningful insights, not just numbers
- Integrated LMS — structured education built with instructional design methodology
- Behavior-first design — gamification that celebrates consistency over perfection
AI Development Workflow
This isn’t “asking ChatGPT for help.” This is systematic, context-managed software development using parallel AI agents:
What I Built
- Multi-member architecture — each family member has individualized settings within a shared household
- Health intelligence layer — data visualization and tracking that goes beyond simple logging
- Dynamic theming engine — UI adapts content and visual design contextually
- Tiered SaaS model — progressive feature access from free to premium
- Integrated LMS — structured education platform using ID methodology
- Behavior-first gamification — applying ID principles to drive sustainable adoption
NourishIQ includes a built-in Learning Management System designed using instructional design methodology — not a bolted-on FAQ section, but a structured education platform with progressive learning pathways and competency-based content delivery. This directly maps to my Master’s coursework at UCF — EME 6613 (Instructional Systems Design) and EME 6507 (Multimedia for Education & Training).
I don’t just recommend AI adoption — I’ve lived it. I direct AI agents to build production-grade applications, which means I can design realistic adoption strategies because I understand the actual capabilities and limitations firsthand. “Technology adoption isn’t a slide deck problem — it’s a build problem.”
Skills Demonstrated
Key Takeaway
I’ve spent 25 years building things — trade schools, software systems, training programs, marketing campaigns, operational workflows. NourishIQ is the latest, but the pattern is the same: identify a gap, learn the domain, build the solution. AI-augmented development didn’t change what I do. It accelerated how fast I can do it.