Proven builders.
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Shreya Gupta

India

“The heatmap was the feature I was most proud of. Getting the GitHub-style contribution graph working with proper date math was satisfying. I also added haptic feedback on habit completion — small detail but it makes the app feel premium. The accountability partner feature needs more work but the foundation is there.”

Karthik Reddy

India

“I focused heavily on the gamification loop — XP for completions, levels, milestone badges. Users in my test group said the level-up animation was what kept them coming back. The weekly review screen with completion percentages was well received. Main weakness: I rushed the notification scheduling.”

Shreya Gupta

India

“Getting the AI to output structured JSON for map plotting was the key insight. Once I had reliable lat/lng data from the LLM, the interactive map with day-by-day route drawing came together beautifully. The budget breakdown feature surprised me by being the most-used feature in testing. Export to Google Calendar was easy once the data was clean.”

Aditya Joshi

India

“I focused on making the itinerary feel human — not just a list of places but a story of the day. Added weather data integration and local cuisine recommendations that made each day feel curated. The shareable trip card for social media was a last-minute addition that turned out great.”

Karthik Reddy

India

“The ATS keyword matching algorithm was my main focus. I built a side-by-side diff view showing exactly which keywords from the job description are missing from the resume and where to add them. The cover letter generator produced surprisingly natural output. PDF parsing remains the hardest problem — used a two-pass approach that catches most formatting.”

Aditya Joshi

India

“I approached this as a coaching tool, not just a formatter. The AI gives section-by-section feedback with specific rewrite suggestions. The interview prep module — generating likely questions from the job description — was my favorite feature to build. Would add salary negotiation templates in v2.”

Karthik Reddy

India

“The ingredient recognition from fridge photos was the hardest feature. Used a two-step approach: general object detection then food-specific classification. The meal plan auto-generator with grocery list was the most satisfying feature — one tap and the whole week is planned. Dietary filters are comprehensive and work reliably.”

Pooja Singh

India

“I focused on the social cooking experience. Users can share recipes, fork and modify them, and follow each other's meal plans. The AI recipe generation from leftovers idea was fun to build. My brother used the app for two weeks and said the leftover suggestions alone saved him money. Needs more recipes in the starter database.”