When Windsurf's Cascade agent suggests Swift code that won't compile or uses deprecated APIs, the fix is a tighter verification loop. Here's how to catch and correct hallucinated SwiftUI and Swift code reliably.
AI models generate plausible code from patterns, and Swift and SwiftUI evolve quickly. The result is that an agent can confidently produce APIs that are deprecated, renamed, or simply invented.
This is not unique to Windsurf. Every AI coding tool can hallucinate, because none of them actually compile Swift while suggesting.
Windsurf cannot run Apple's compiler, so its suggestions are unverified by definition until you build them.
The fix is not to abandon the agent. The fix is a disciplined verification loop that catches bad code fast and cheaply.
Treat every AI-generated change as a draft until it compiles in Xcode or via `xcodebuild`.
Make building a reflex after accepting edits. The compiler is your ground truth, and it will immediately flag a nonexistent symbol or a wrong signature.
Keep your build loop tight. The faster you can compile after an edit, the cheaper it is to catch hallucinations before they pile up.
Never commit AI-written Swift you have not built. An uncompiled change is an unverified change.
A common cause of wrong APIs is the model assuming the wrong platform version. Tell it what you target.
In your prompt, state your minimum deployment target and Swift version, for example the specific iOS version and Swift version your project uses. This nudges suggestions toward APIs that exist for you.
If you rely on newer APIs, say so. If you must support older versions, say that too, so the agent does not reach for symbols you cannot use.
Context does not guarantee correctness, but it meaningfully reduces version-mismatch errors.
When a build fails, copy the exact compiler error and paste it into Cascade. The error text is precise and gives the agent what it needs to self-correct.
Ask it to fix the specific error rather than to rewrite broadly. Narrow requests produce narrow, reviewable fixes.
If the same wrong API keeps reappearing, tell the agent explicitly that the symbol does not exist in your SDK and ask for the correct replacement.
This feedback loop, edit then build then paste error then fix, is the core technique for working productively with an agent on Swift.
When an API looks unfamiliar, check Apple's official documentation before accepting it. Do not assume the agent is right.
Apple's developer documentation lists availability, including which OS version introduced an API and whether it is deprecated. That availability info is exactly what catches hallucinations.
For SwiftUI especially, confirm modifier names and signatures, since these change across releases and are a frequent source of confident-but-wrong suggestions.
A quick documentation check is far cheaper than debugging a subtle runtime issue later.
Some hallucinations are sneakier. The code compiles, but it uses a deprecated API that will warn now and break later.
Do not ignore deprecation warnings in Xcode. Treat them as signals that the agent reached for an older pattern.
When you see one, ask Cascade for the modern replacement, then rebuild to confirm the warning is gone.
Keeping warnings at zero is a good habit that also keeps AI-suggested code current rather than quietly aging.
Compiling proves the code is valid Swift. It does not prove the code is correct. Those are different things.
Run the app on the Simulator and exercise the affected feature. AI can produce code that builds but behaves wrongly, like off-by-one logic or a flipped condition.
Where you can, add unit tests around AI-generated logic. Tests turn correctness into something you verify automatically rather than by hand each time.
For UI, check SwiftUI previews and real interaction, since a view can compile yet render or animate incorrectly.
Make verification structural so you do not rely on remembering it each time.
Use a clean Git state before agent edits, so you can always diff and revert hallucinated changes cleanly.
Run your test suite and your build in CI on every change, so bad AI suggestions are caught even if one slips past local review.
With these habits, Cascade becomes a fast drafting partner whose mistakes are caught quickly, rather than a source of hidden bugs. The agent writes; Apple's toolchain and your tests decide what ships.
It helps to know what wrong Swift suggestions tend to look like, because spotting the pattern is faster than discovering it through a failed build every time.
Invented symbols are the most obvious: a method or modifier that reads plausibly but does not exist in any SDK. These fail to compile immediately, which is the easy case.
Version-mismatched APIs are sneakier. The symbol is real, but it was introduced in a newer OS than you target, so it compiles on a recent SDK and then fails availability checks or crashes on older devices. Watch for anything wrapped in the wrong availability assumptions.
Renamed or restructured APIs are another recurring shape, where the agent reaches for an older spelling of something that still has an equivalent today. SwiftUI modifiers and concurrency APIs are frequent offenders, so treat unfamiliar versions of familiar calls with suspicion.
Many hallucinations trace back to missing context, and you can reduce them by feeding the agent the right inputs up front.
Open the files that contain similar, known-good code before you prompt, so the agent has real examples of the APIs your project actually uses. It is far more likely to match an existing pattern than to invent one when a correct example is in view.
State your platform target and any frameworks you rely on explicitly, and mention constraints like avoiding a deprecated API you have already removed. Specific instructions narrow the space of plausible-but-wrong answers.
When a suggestion does go wrong, do not just fix it silently; tell the agent what was wrong and why. Correcting it in the conversation makes the next suggestion in that session more likely to stay inside your real SDK.
The same logic applies to project conventions. If your codebase uses a particular networking layer, a specific concurrency style, or a house pattern for view models, say so, and the agent will lean on those instead of inventing alternatives.
Think of context as the cheapest accuracy improvement available. Every relevant detail you supply up front is one less thing the model has to guess, and guesses are exactly where hallucinations come from.
AI models generate plausible code from patterns and can't compile Swift while suggesting, so they sometimes invent or use deprecated APIs. Swift and SwiftUI evolve fast, which makes version mismatches common.
Tell the agent your deployment target and Swift version in the prompt, verify unfamiliar APIs against Apple's documentation for availability, and feed compiler errors and deprecation warnings back to Cascade for correction.
No. Compiling proves it's valid Swift, not that it's correct. Run the app on the Simulator, check behavior, and add unit tests, since AI can produce code that builds but behaves wrongly.
Copy the exact compiler error and paste it into Cascade, asking it to fix that specific error. The edit-build-paste-error-fix loop is the core technique for working productively with the agent on Swift.