I was thinking about this because it sounds like such a small product decision, but I don t think it actually is.
Someone signs up with Google. Six months later they are on their iPhone and tap Sign in with Apple. Same person, different identity provider. And if they use Hide My Email, you may not even get the same email address.
So what should the product do?
Creating a new account feels wrong because now their history, billing, settings, or subscription can end up split across two profiles. But automatically linking accounts based on email also feels risky, because now you are assuming that matching email addresses are enough proof that both identities belong to the same person. And then Apple makes it even messier because the emails may not match at all.
I have run a software company, a care home, and a cafe at different points, sometimes more than one at once. None of the numbers I actually watched closely lived in a report. Revenue and margin mattered, obviously, but the thing that actually kept me up was smaller than that, a client who had gone quiet, a shift that was one call away from falling apart, a lead I told myself I would follow up with and then did not. None of that shows up on a P&L until it already cost something.
Curious how other people running a small or solo operation actually track that layer. Do you keep it in your head, write it down somewhere, or has anyone found something that actually surfaces it before it becomes a problem?
Hi all, there's a distinction I keep thinking about: apps built with AI (Cursor, Claude, Copilot writing the code) vs apps that depend on AI APIs at runtime to function.
I'm in the first camp. I used AI-assisted coding heavily to build Briskly (a cleaning app that scans your room and generates a timed task list), but the app itself makes zero LLM API calls. The scanning runs on Apple's Vision framework, entirely on-device. No tokens, no per-user inference costs, no latency, works offline, and my privacy label is basically empty.
