0-to-1 AI Product · Built with Lovable

PackWise — AI Packing Assistant

Start with where you're going. PackWise checks the local weather and your trip mood to build a personalized, weather-aware packing checklist — instead of a generic template or a list dug up from your last trip.

Role
Solo builder — problem to working prototype
Method
Problem discovery, weather-aware flow design, prompt engineering
Scope
Travel, AI packing assistant
The problem

Packing lists don't know where you're going

A generic checklist treats a beach trip and a hill-station trip the same way. By the time you've cross-referenced the weather forecast yourself and adjusted for the kind of trip it actually is, you've spent more time planning the bag than packing it.

Solution

PackWise: place first, then mood, then weather-built list

DESTINATION-FIRST

Weather starts the checklist, not an afterthought

Every list is built from the actual local weather for the destination — temperature range and rain chance — instead of a generic template applied everywhere.

MOOD-AWARE

Packs for the trip you're actually taking

A relaxed hill-station trip and an adventure-heavy one need different bags even at the same destination — the mood you set shapes the list, not just the climate.

AI SUGGESTIONS

A checklist that adapts, not just lists

Beyond the base checklist, AI suggestions fill in the items that are easy to forget for that specific combination of place and mood.

Prototype

A working app, not just a flow diagram

PackWise is built and live — destination and mood setup, weather-aware checklist generation, and AI suggestions all work end to end in the prototype below.

Live prototype — PackWise Open full screen ↗
Open interactive prototype ↗
Process

Started from why packing lists feel generic, not a feature list

Discovery
Problem discovery — started from how much manual cross-referencing (weather, trip type) goes into a packing list before a single item gets written down.
Flow
Weather-aware flow design — mapped destination → mood → weather-built checklist as one continuous setup, not three separate steps.
Prompts
Prompt engineering — wrote the prompts that turn destination, weather and mood into a coherent, non-generic suggestion set.
Build
Prototype — shipped a working, clickable app on Lovable rather than leaving the concept as a deck.