Offline by default
No required account. Sensitive tracking data is designed to stay on-device.
Ayush MishraMobile Product Engineer
I build mobile products and spend a lot of time on the messy parts that show up after people start using them: product behavior, edge cases, debugging, testing, releases, and iteration.
Primary product proof
Creator & Mobile Product Engineer · June 2025—Present
A privacy-first, offline period and cycle tracker shipped on iOS and Android. I own the product from behavior and architecture through React Native / Expo delivery, debugging, releases, monetization, and iteration.
Privacy is product behavior.

Six-month Google Play view
265K
Play impressions
~3K
Device acquisitions
900+
Monthly active devices
The engineering story
Petal Chan has changed a lot since its first version. Real user feedback exposed assumptions in the tracking model that looked fine on paper but did not work for everyone.
People with irregular cycles, people using birth control, and people focused on symptoms needed something more flexible than conventional calendar predictions. That led to context-sensitive and symptom-only tracking modes, with changes to the product behavior underneath the interface.
No required account. Sensitive tracking data is designed to stay on-device.
Different tracking modes changed underlying assumptions instead of adding a cosmetic setting.
Edge cases move through reproduction, review, hands-on testing, and production validation.
Store releases, a one-time upgrade, user feedback, and production iteration are part of the work.
How I work
My strongest work is deciding what a product should do, finding why it does not do that yet, and staying with the problem until the fix holds up in real use.
Start with what the user should be able to do, what can go wrong, and which edge cases actually change the product.
Make architecture and data-flow decisions around the real behavior, including offline state, integrations, and release constraints.
Use agent-assisted implementation and independent reviews, then reproduce warnings and failures instead of accepting a clean-looking diff.
Test the actual flow, correct what breaks, ship carefully, and let production feedback decide what needs to change next.
AI-augmented workflow
I use coding agents heavily for implementation and independent review. The product decisions, failure investigation, hands-on testing, and responsibility for what ships stay with me.
More shipped work
Smaller utilities still matter. They show repeatable product delivery across different workflows without competing with the depth of the Petal Chan story.
An offline iOS utility for deposition timekeeping, objection logging, and export-ready session records.
A local viewer for Instagram export data with search, media browsing, and biometric protection.

Professional profile
I work best where product judgment and engineering meet: defining a useful behavior, shaping how it should work, finding the failure nobody expected, and seeing the fix through to production.
Current experience
June 2025—Present
Product behavior, architecture, releases, debugging, testing, monetization, and user-led iteration across iOS and Android.
Supporting client proof
A mobile scan-to-record workflow connecting real-world access events with database-backed information for an operational use case.
Available for the right fit
I'm open to remote mobile and product engineering roles, with full-time and strong long-term contracts preferred. I'm based in India and also open to European relocation with sponsorship.
Email AyushSelective client work
Have a focused product problem that needs an owner?