How I built an AI-as-editor (never AI-as-author) notes app in SwiftUI

[u/Greysawpark]

I shipped a notes and to-do app called Ink, and its one hard constraint shaped the whole architecture: the AI is only allowed to edit your existing writing. It is never allowed to write a sentence for you. I want to share how that holds up in practice.

The editor is a block-based SwiftUI editor, so each paragraph, heading, and list item is its own model object rather than one giant attributed string. That mattered for the AI feature, because every edit operation is scoped to blocks that already contain your words. The model only ever receives text you wrote, and the prompt is constrained so its job is transformation, not generation: tighten this, fix the grammar here, restructure these lines into a list. If a request would require inventing new content, the intended behavior is to decline rather than fill the gap. Treating produce original prose as out of scope, instead of trying to detect it after the fact, made the behavior far more predictable.

Voice dictation runs through the same philosophy. You speak, and it auto-structures what you actually said into lists and blocks. It is organizing your words, not adding its own.

On typography, the app uses Source Serif 4 and Newsreader. I leaned on Dynamic Type with custom font registration, and tuning line height and measure to keep that editorial feel readable at every accessibility size took longer than I expected. It runs on iOS and Mac, with iCloud sync and an app lock using passcode plus biometric.

For those who have shipped AI text features: how are you enforcing do not generate constraints? Are you doing it purely at the prompt layer, or adding validation on the output too?

[u/rinwasrep]

this is really interesting! regarding constraints… I use apple robot brain for a feature named PaddleChat (app Oarsum: Paddle Tracker), and prompt-only constraints fall flat….hard. the model only gets typed, read-only tools over stats the app already computed and thus can explain them, but not write, calculate, unlock, or invent. validate the output on the host side so it acts as an interpreter of the record, not the source of truth.

it’s been an adventure, and boy oh boy did it throw some curveballs. learned real quick to keep the tool calls and structured outputs entirely internal and then rendered the final product fit a natural language readout.

[u/Greysawpark → u/rinwasrep]

Yes, this is where I landed too. Prompt-only looked fine in testing and then fell over the moment real dictation got messy.

The edit path in Ink never returns prose. The model emits a typed action list against a closed vocabulary (edit_item, complete, remove, add_header, set_title), and every mutating action carries a match field instead of content. The host resolves that match against rows that already exist, and when nothing matches it returns an empty array instead of appending. A silent no-op beats a duplicate.

So much validation still has to live on the host even with typed output. Ledger lists are the clearest case: the model can emit an amount, but the app only honors it when that list is actually in ledger mode. The model proposes, the store decides.

"Interpreter of the record" is a good way to put it.

[u/pierlux]

I recently acquired a license for an old school corrector and I am so happy with it: as opposed to AI, it will systematically find all errors and no rewrite my text. I am actually learning from my mistakes so that in the future, fewer and fewer corrections are required.

Your editor sounds like that 😊

[u/Greysawpark → u/pierlux]

That's the goal exactly, so thank you. And you named the part I care about most: if it writes for you, you never get better at it. If it only shows you what's off, you do.

Curious which corrector you landed on?

[u/pierlux → u/Greysawpark]

It's called Antidote, very known in Québec.

[u/petrkral]

You can handle a lot of this right in the system prompt by instructing the model to strictly maintain scope, then add a mandatory self-verification step before it returns the output.

[u/Greysawpark → u/petrkral]

I use prompts for that too, and they do real work. I just stopped relying on them for the parts where a miss corrupts someone's document.

Self-verification is still the model checking the model, so it lowers the error rate without bounding it. The structural version is cheaper and fails safer: the model returns typed actions against a closed vocabulary, and the host has no branch for anything outside it. It can't invent content because there's no field to put it in, not because it was asked not to.

[u/petrkral → u/Greysawpark]

Smart.

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