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Offline damp & mould survey app with AI report writing

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    I wanted to test mobile apps in plain English instead of relying on brittle selectors like XPath or accessibility IDs. With a vision-based agent, that part actually works well. It can look at the screen, understand intent, and perform actions across Android and iOS. The bigger problem showed up around how tests are defined and maintained. When test flows are kept outside the codebase (written manually or generated from PRDs), they quickly go out of sync with the app. Keeping them updated becomes a lot of effort, and they lose reliability over time. I then tried generating tests directly from…

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  14. 14AF

    Saw Spacial recently — it's an AI tool that helps figure out what can be built on a piece of land, based on local zoning rules. You enter a parcel and it generates 3D massing, site plans, and other planning details in a few minutes. Seems like it could be super helpful for early-stage architecture or development work.

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    I’m the CEO of AirGradient, where we build open-source air-quality monitors. Two months ago I decided to build our first native iOS app myself. I’ve been coding on the side for ~15 years, but had never touched Swift or SwiftUI. Still, I went from empty repo to App Store approval in exactly 60 days, working on it only on the side. The app itself is a global PM2.5 map with detail views, charts, and integration with our open-source sensors -straightforward, but fully native with Swift and now live on both iOS and Android (native Kotlin version). The interesting part for me was actually not so…

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