A practical walkthrough of using Tabnine's AI chat to generate SwiftUI views, refactor Swift code, and write tests — with the guardrails iOS developers need.
Inline completions are great for finishing lines, but some tasks need a conversation. That is where Tabnine's chat panel earns its place.
Chat is better when you want to generate a whole component from a description, explain unfamiliar code, or refactor something across several lines while stating your intent in plain English.
For SwiftUI in particular, chat lets you describe a view — its layout, state, and bindings — and get a starting scaffold you can refine.
The key mindset: chat produces drafts, not finished code. You still read, compile, and test everything it gives you, especially with fast-moving SwiftUI APIs.
In VS Code or your JetBrains IDE, find the Tabnine icon and open the chat view. It usually docks as a side panel next to your editor.
Make sure you are signed in to your Tabnine account, since chat features generally require authentication. If the panel prompts you to log in, complete that first.
Keep your relevant Swift file open and, ideally, selected. Tabnine can use the open file and selection as context, which makes answers match your actual code.
With the panel open and context available, you are ready to prompt. Treat it like a focused pair-programmer sitting next to your editor.
Start with a concrete request. Something like: create a SwiftUI view showing a list of items with a title, subtitle, and a chevron, backed by an observable view model.
Be specific about state. Mention whether you want @State, @Binding, @Observable, or an ObservableObject, because vague prompts produce vague, sometimes outdated patterns.
When the code comes back, read it before pasting. Check that it uses current SwiftUI idioms and does not reference deprecated modifiers.
Then drop it into your project and compile. SwiftUI errors surface fast, and the compiler is your best fact-checker for anything the AI generated.
Chat shines at refactoring. Select a chunk of Swift, then ask Tabnine to extract a subview, simplify a nested closure, or convert an imperative block into a more declarative form.
State your goal precisely. Turn this massive body into smaller subviews works better than just clean this up, because it tells the model what good looks like.
Review the diff carefully. Refactors can silently change behavior — a reordered modifier, a dropped animation, a changed default. Compile and run to confirm the UI still behaves.
Refactor in small steps and commit between them. That way, if a suggested change breaks something, you can revert cleanly instead of untangling a large rewrite.
Ask chat to write tests for a specific function or view model. For example: write XCTest cases for this networking parser covering success and failure.
Tests are a great use of AI because they are structured and the pass/fail signal is immediate. If a generated test compiles and passes for the right reasons, you have gained coverage cheaply.
Read each test to confirm it actually asserts meaningful behavior, not just that code runs. AI sometimes writes tests that pass without proving anything useful.
Run the tests in Xcode. Even if you author them in VS Code, the real test run happens in Xcode against the iOS simulator or a device.
When you inherit unfamiliar Swift, paste it into chat and ask for an explanation. This is one of the safest and most valuable uses because there is no risk of shipping wrong code.
Ask targeted questions: what does this property wrapper do here, why is this marked @MainActor, what happens if this optional is nil.
Use the explanations to build your own understanding, then verify against Apple's documentation for anything that affects correctness or concurrency.
This learning loop is quietly one of the best reasons to keep chat open — it shortens the distance between confused and confident.
The quality of chat output tracks the quality of your prompt. Give context, constraints, and a clear target.
Good prompts name the framework version behavior you expect, the state model you want, and any style rules — for instance, no force unwraps, prefer async/await over completion handlers.
If the first answer misses, refine rather than restart. Say that is close, but use @Observable and remove the completion handler and let it iterate.
Over time you will build a mental library of prompts that reliably produce code matching your team's Swift conventions.
Chat quality depends heavily on what Tabnine can see. A little context management goes a long way.
Before asking for a new SwiftUI view that uses your own model or view model, open those files and, where possible, select the relevant declaration. Grounding the request in real types keeps the answer from inventing names or shapes that do not exist in your project.
When you paste code into chat for refactoring or explanation, include just enough surrounding code to make it self-contained. A single function with its dependencies produces better answers than a fragment ripped out of context.
Be explicit about the SwiftUI patterns you want. If your codebase standardizes on a particular state approach or naming convention, say so in the prompt rather than hoping the model infers it. Vague requests drift toward generic, sometimes dated patterns.
And keep prompts scoped. Asking for one view, one refactor, or one set of tests at a time yields output you can actually review, compile, and trust — far better than a sprawling request that returns a wall of code you cannot verify quickly.
No matter how good a chat answer looks, it is not real until it compiles, runs, and passes tests in Xcode. That is the non-negotiable final step.
Tabnine cannot build, sign, or submit your app. It generates Swift; Xcode and the Apple Developer Program handle everything from build to App Store.
Make it a habit to move generated code into your project, build, run in the simulator, and exercise the actual UI before you trust it.
Used this way — draft in chat, verify in Xcode — Tabnine chat becomes a genuine accelerator for SwiftUI work rather than a source of subtle bugs.
One last habit is worth building: keep a short note of the prompts that reliably produce good SwiftUI for your codebase. Reusing a proven prompt beats reinventing one under deadline pressure, and it quietly encodes your team's conventions into how you work with the tool.
It can generate a solid scaffold from a clear description, but you should treat it as a draft. Compile and test in Xcode, and fix any outdated SwiftUI APIs it uses.
It can use open files and your selection as context. Keeping the relevant Swift file open and selected produces answers that match your actual code.
Yes, explanation is one of the safest uses since it does not change your code. Still verify anything correctness-critical against Apple's official documentation.
Yes. Ask it to write XCTest cases for a specific function or view model, then run them in Xcode and confirm the assertions are meaningful.
Absolutely. Chat only produces code. Building, running on the simulator, signing, and submitting all require Xcode and an Apple Developer Program membership.