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Apple Vision Pro: A Developer's Perspective

Yuval Avidani
11 min read
Apple Vision Pro: A Developer's Perspective

Living and Building in the Vision Pro for 6 Months - A Developer's Honest Review

The Vision Pro launched with massive hype, then seemingly disappeared from tech discourse. Dead on arrival? Not even close. After six months of daily development work in Apple's spatial computing headset, I'm here to tell you this device is the most transformative development platform I've used since the iPhone SDK - but not for the reasons Apple marketing suggested.

This matters to developers because we're witnessing the birth of a new computing paradigm while it's still malleable. The App Store wasn't interesting on day one of iPhone development - it was interesting because early developers shaped what mobile computing became. We're in that same moment for spatial computing, and the tools, frameworks, and design patterns we establish now will define this platform for the next decade.

The Uncomfortable Truth: It's Heavy, It's Expensive, and It's Magical

Let's address the elephant in the room - the Vision Pro costs $3,500 and weighs 600-650 grams (1.3-1.4 pounds) on your face. After a 2-hour coding session, I feel it. After 4 hours, I need a break. This isn't the all-day computing device Apple showed in their marketing videos where people casually wear it for hours.

But here's the thing: when I'm deep in a debugging session, walking through a 3D visualization of a neural network architecture, or manipulating spatial data structures with my hands, the discomfort becomes background noise. The device is simultaneously the worst and best piece of tech I own. Worst in ergonomics, best in capability.

The magic is real. The first time you compile visionOS code and see your app materialize as a floating window in your living room, then extend it into a volumetric 3D object you can walk around, something clicks. This is a new dimension of human-computer interaction, and we're the first generation of developers to have access to it.

Developing for visionOS: SwiftUI on Steroids

Apple made a brilliant architectural decision: visionOS is built on SwiftUI, the same framework used for iOS, iPadOS, and macOS. If you know SwiftUI, you're 60% of the way to shipping visionOS apps. The remaining 40% is learning spatial concepts, but the learning curve is surprisingly gentle.

Here's what blew my mind:

import SwiftUI
import RealityKit

struct NeuralNetworkView: View {
    var body: some View {
        VStack {
            Text("Neural Network Visualizer")
                .font(.extraLargeTitle)
            
            Model3D(named: "TransformerArchitecture") {
                // Model loaded successfully
                model in
                model
                    .resizable()
                    .scaledToFit()
            } placeholder: {
                ProgressView()
            }
        }
        .windowStyle(.volumetric)  // 👈 This one line makes it 3D
    }
}

That .windowStyle(.volumetric) modifier is where the magic happens. Your SwiftUI view transitions from a flat window to a true 3D volumetric space. You can walk around it, view it from different angles, scale it with gestures.

RealityKit and Spatial Computing

For more advanced 3D work, RealityKit gives you the full power of a game engine integrated with SwiftUI:

import RealityKit

struct TransformerVisualization: View {
    @State private var modelEntity: ModelEntity?
    
    var body: some View {
        RealityView { content in
            // Load and configure 3D model
            let transformer = try! await ModelEntity(named: "transformer")
            
            // Add interactivity
            transformer.components.set(InputTargetComponent())
            transformer.components.set(CollisionComponent(shapes: [.generateBox(width: 1, height: 1, depth: 1)]))
            
            // Add to scene
            content.add(transformer)
            modelEntity = transformer
        } update: { content in
            // Update scene when state changes
            if let entity = modelEntity {
                entity.transform.scale = [1.5, 1.5, 1.5]
            }
        }
        .gesture(
            DragGesture()
                .targetedToAnyEntity()
                .onChanged { value in
                    // Rotate model based on hand drag
                    value.entity.transform.rotation *= simd_quatf(angle: Float(value.translation.width) * 0.01, axis: [0, 1, 0])
                }
        )
    }
}

This code creates a 3D transformer architecture model you can grab and rotate with your hands. The physics, collision detection, and gesture recognition are built-in.

Real Projects I've Built

1. Neural Network 3D Visualizer

My flagship project: a tool that takes trained neural network models and renders them as interactive 3D structures. Each layer is a spatial object, connections flow between neurons with animated particles showing activation patterns during inference.

Why spatial computing matters here: On a 2D screen, complex networks are visual spaghetti. In 3D space, I can walk into the middle of a transformer's attention mechanism, see which heads are activating for a given input, trace information flow through residual connections.

// Simplified version of my network layer renderer
struct NetworkLayer: View {
    let neurons: Int
    let layerIndex: Int
    
    var body: some View {
        HStack(spacing: 0.2) {
            ForEach(0..<neurons, id: \.self) { neuronIndex in
                Sphere(radius: 0.05)
                    .foregroundStyle(.blue.opacity(0.7))
                    .overlay {
                        // Activation glow effect
                        Sphere(radius: 0.06)
                            .foregroundStyle(.white.opacity(activation(neuronIndex)))
                    }
            }
        }
        .position(z: Float(layerIndex) * 0.5)
    }
    
    func activation(_ neuronIndex: Int) -> Double {
        // Fetch from model inference
        modelState.layerActivations[layerIndex][neuronIndex]
    }
}

Result: Understanding transformer attention mechanisms went from abstract math to visual intuition. I now "see" what my models are doing.

2. Spatial Code Editor Experiment

I built a prototype code editor where different files float as panels in 3D space around you. Related files cluster together. You can "pin" frequently accessed files to specific spatial locations.

The insight: our mental model of code often isn't hierarchical (file tree) or flat (tabs). It's spatial. "The authentication logic is over there, the database models are behind me, the API routes are to my right." Vision Pro lets you externalize this spatial mental model.

Turns out, I don't actually code this way daily (decades of muscle memory for traditional editors). But for architectural reviews and onboarding new developers to complex codebases? This is incredibly powerful. Walking someone through "where everything lives" has new meaning when you can literally point at floating code modules in shared space.

3. Data Visualization Dashboard

Financial time series data rendered as 3D landscapes where peaks and valleys represent values over time. Multiple data streams float as layers you can peel apart and examine.

Why this works: Financial analysts already use the metaphor of "landscape" for market trends. Making it literal - where you can fly through the data, zoom into specific time periods, overlay multiple metrics spatially - changes how you spot patterns.

What I Learned About Spatial UI Design

Traditional UI/UX rules break in spatial computing:

1. Z-Depth Is a First-Class Dimension

On flat screens, z-depth is simulated (shadows, size, blur). In visionOS, it's real. Important content should be closer, contextual info further away. UI elements have real distances between them.

VStack {
    PrimaryContent()
        .position(z: 0)  // Front
    
    SecondaryContext()
        .position(z: -0.5)  // Behind
    
    BackgroundInfo()
        .position(z: -1.0)  // Far back
}

2. Gaze + Pinch Replaces Mouse Clicks

The Vision Pro's interaction model: you look at something (gaze), then pinch your fingers (selection). This is more fatiguing than clicking a mouse but more direct. Design for larger hit targets, clear focus indicators, and minimal fine motor control requirements.

3. Ergonomics Trump Aesthetics

Cool architectural visualization where you have to look straight up? Neck pain in 30 seconds. Amazing effect that requires holding your arms extended? Fatigue in 2 minutes. The "comfort zone" is roughly 0-20 degrees below eye level, arms at sides. Design within these constraints.

4. Spatial Audio Is Critical

Sound sources in 3D space help with orientation and feedback. When I tap a UI element, the click sound comes from its spatial location. When a notification arrives, I can tell which window it's associated with by audio position.

Button("Submit") {
    // Play spatial audio at button location
    audioEngine.play("click.mp3", at: buttonPosition)
    submitForm()
}

The Developer Ecosystem: Early but Growing

Current State:

  • ~600 visionOS apps on App Store (as of Dec 2025)
  • Most are ports of iPad apps (2D compatibility mode)
  • ~50 truly spatial-native apps that use volumetric or immersive features
  • Strong SwiftUI developer community sharing knowledge

Tools:

  • Xcode with Vision Pro simulator (surprisingly good)
  • Reality Composer Pro for 3D asset creation
  • TestFlight for visionOS beta testing
  • Spatial Personas for multiplayer testing

Challenges:

  • Physical device required for final testing ($3,500 barrier)
  • 3D asset creation requires new skills (or hiring 3D artists)
  • App Store discovery is terrible (like early iPhone days)
  • Market size is tiny (estimated 200k-500k Vision Pro users globally)

Performance Characteristics

What's Fast:

  • SwiftUI rendering (60fps for complex UIs)
  • RealityKit 3D rendering (90fps for moderate complexity scenes)
  • Hand tracking (essentially instant, better than I expected)
  • Passthrough video (imperceptible latency)

What's Slow:

  • Large 3D model loading (multi-GB assets take seconds)
  • Complex physics simulations (frame drops with 100+ physics bodies)
  • Computer vision tasks (running CoreML models on Vision Pro is resource-constrained)

Battery Life:

  • 2-2.5 hours of active development use
  • Tethered to battery pack (annoying cable)
  • Development with Xcode wireless debugging drains faster

Business Reality: Should You Build for visionOS?

Build visionOS apps if:

  • You're in enterprise (training simulations, 3D design, architecture, medical visualization)
  • You're building developer tools (code visualization, debugging, system monitoring)
  • You're experimenting with spatial computing for future platforms (Quest 4, Meta's devices, eventual AR glasses)
  • You have budget to invest in future platforms (not expecting ROI in 2025-2026)

Don't build visionOS apps if:

  • You need mass consumer reach (market is tiny)
  • You're bootstrapped (device cost + development time is significant)
  • Your app doesn't benefit from spatial interaction (most apps don't)
  • You expect App Store revenue (current user base doesn't support most apps)

What Spatial Computing Teaches Us About the Future

The Vision Pro is not the final form factor - it's too heavy, too expensive, too isolating. But it's a functional preview of computing in 2030-2035. Here's what I believe based on my development experience:

1. Ambient Computing Is Coming Apps that float in your peripheral vision, providing context-aware information without demanding attention. I have a terminal window that hovers to my left - I can see build status without switching focus.

2. Multiplayer Will Define Spatial Apps The killer apps for spatial computing will be collaborative. Shared 3D workspaces where distributed teams manipulate data together. Apple's Spatial Personas are primitive now, but the direction is clear.

3. AI + Spatial = Powerful Combination Imagine asking an AI to "show me how this code works" and having it generate an interactive 3D execution visualization. Or debugging by pointing at a floating object and saying "why is this value wrong?" Voice + gesture + spatial + AI is the next interaction paradigm.

4. Not Everyone Will Use Headsets Just like not everyone uses smartphones the same way, spatial computing will be one of many interfaces. But for specific tasks (design, data analysis, complex debugging, training), it will become standard. Like how video editors all use color-graded displays - spatial computing will become the professional tool for certain jobs.

My Honest Recommendation

Buy a Vision Pro if:

  • You're a professional developer curious about the future
  • You work in 3D (CAD, animation, game development, scientific visualization)
  • You have the $3,500 + don't mind being an early adopter
  • You want to shape a new platform while it's malleable

Wait for Vision Pro 2 if:

  • You want lighter, more comfortable hardware
  • You want more apps and content
  • You want lower price ($2,000-2,500 expected for next gen)
  • You're not a developer (consumer case is weak right now)

Skip Entirely if:

  • You don't see specific use cases for spatial computing in your work
  • You're motion sensitive (some people get nausea)
  • You need mobility (tethered battery, not portable like laptop)

After six months living in this device, I'm convinced spatial computing is the future - but we're in the "iPhone 1" phase. It's incredible technology with obvious limitations. The Vision Pro showed me what's possible. Future devices will make it practical.

For developers willing to invest in learning this platform now, there's a massive opportunity. The visionOS ecosystem is so early that individual developers can still create category-defining apps. That window won't last long.

The future of computing is spatial. The Vision Pro lets you build that future today, even if you have to tolerate a few pounds on your face to do it.

Build something spatial. You'll never look at human-computer interaction the same way again.