Why does ADIF export matter so much?

Because a log is a lifetime record and operators know it. ADIF is the interchange format every desktop logger and awards service reads, so supporting it is what makes your app safe to try. An app that can only export its own format reads as a trap, and in this community that objection will be the first reply to your launch post.

Do I need real-time callsign lookup?

Not for version one. Lookup services are useful but they need an account, a network connection, and a paid tier for the good data — none of which you have on a hilltop. Ship fast offline entry first and treat lookup as an enhancement that fills in a name and grid when there happens to be signal.

How to Build a Ham Radio Log App with AI (2026)

What a ham radio log app needs

Two-field QSO entry: callsign and report, everything else prefilled
Band, mode, frequency, and grid square per contact
QSL sent and received status per contact and per method
Worked-and-confirmed counts by band, mode, country, and grid
ADIF import and export so the log is never trapped

The screens

Screen	What it does
Log	Reverse-chronological contacts with band, mode, and QSL state
New QSO	Fast entry with station defaults prefilled and a running clock
Contact Detail	Full record, notes, and QSL tracking
Awards	Worked/confirmed counts by band, mode, DXCC entity, and grid
Station	Your callsign, rig, antenna, grid — the defaults every QSO inherits

The data model

Station: callsign, gridSquare, rig, antenna, power, operatorName
Qso: stationId, workedCallsign, startedAtUtc, band, mode, frequency, rstSent, rstReceived, gridSquare, dxccEntity, notes
Qsl: qsoId, method, direction, status, sentAt, receivedAt
AwardProgress: stationId, awardType, band, mode, workedCount, confirmedCount

The build prompt (copy this)

Paste this into ShipNative and it becomes a working React Native app with these screens, navigable in a live preview, in about two minutes:

“An amateur radio contact logger. The operator sets up a station once — callsign, grid square, rig, antenna, power — and every new contact inherits those as defaults. New QSO is the screen that matters and must be fast: the callsign field is focused on open, the UTC time is captured automatically and shown running, and band, mode, and frequency default to the last used values so a typical contact is two fields and a save. Signal reports default to 59 and are editable. Optional fields are the other station’s grid square, name, and free-text notes. The Log lists contacts newest first with band, mode, and QSL state, and is searchable by callsign. Contact Detail shows the full record and tracks QSL status separately for each method — paper card, electronic, or logbook service — in both directions. An Awards screen counts worked and confirmed contacts broken down by band, mode, country, and grid square. The whole log must import and export ADIF, because operators will not adopt a logger they cannot get their data out of. All times are stored and displayed in UTC. Works fully offline; there is no signal on a hilltop. Screens: Log, New QSO, Contact Detail, Awards, Station.”

Then iterate with small, screen-specific prompts (“make the primary button bigger”, “add an empty state”), preview on your own phone, and export the full Expo project whenever you want. The full method: how to build an app with AI.

How it makes money

A one-off unlock of roughly $10–20 rather than a subscription. This audience is technical, long-tenured, and openly hostile to renting a logbook, and there are free desktop loggers they already trust. Sell the phone-shaped convenience once, keep ADIF export in the free tier so nobody feels held hostage, and let awards tracking and cloud backup be the paid half.

Implementation and the revenue math for every model: how to make money from an app. When you’re ready to ship: App Store and Google Play publishing guides.

Build it now

The prompt above is free to run at shipnative.dev — working ham radio log app on your phone today, full code export, no credit card.

How to Build a Ham Radio Log App with AI