Vibe Coding UX Spectrum: Lovable to Windsurf

How products adapt AI to user’s technical comfort levels

Designed by Young Kim

Two ends of technical expertise spectrum

'Vibe coding' spans from complete beginners to seasoned developers:

• Low-code end: Assumes no prior coding experience, functions as a "code generator"

• Pro-code end: Serves experienced developers as an "AI-assisted IDE"

Image credit: digestible UX

Different audience, different UX

Each UX tells users what to expect: ’Try it out’ or ‘Build with it’

• Lovable: Optimized for quick wins and broad adoption

• Windsurf: Crafted for complex, market-ready products

Credit: digestible UX

UX overview across user journey

Credit: digestible UX

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Let's see how they handle each UX step differently

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❶ Onboarding

💜 Lovable

• Guidance: Simple interface with placeholder prompt

• Low friction: No tutorial needed

Image credit: Lovable

🌊 Windsurf

• Familiar UI for developers with VS Code-based layout

• Onboarding wizard: Imports settings from VS Code or Cursor, lets user choose themes

Image credit: Windsurf

Key UX Difference from Onboarding

✅ Speed vs. Setup

• Lovable prioritizes immediate engagement with zero setup

• Windsurf invests in configuration that pays off for professional developers

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❷ First Prompt

💜 Lovable

• Single prompt: Generates full codebase from single high-level prompt

🌊 Windsurf

• Multiple entry points: User can start coding directly or use AI assistance via chat

Key UX Difference from First Prompt

✅ Lead vs. Assist

• Lovable leads with AI, ideal for beginners

• Windsurf supports with AI, giving developers control

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❸ Response

💜 Lovable

• Focus on visual outcome: Displays instant preview—showing what was built, not how it was built

• Black-box generation: Code created behind the scenes

🌊 Windsurf

• Code-first approach: Details code structure, styling, and functionality, focusing on codebase rather than visual preview

• Transparent process: Shows file and code creation step-by-step, explaining logic behind

Key UX Difference from Response

✅ Outcome vs. Process

• Lovable treats code generation as magic and prioritizes the working result

• Windsurf reveals the process and educates through transparency

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❹ Handoff (AI → Human)

💜 Lovable

• Hand-holding: Guides beginner through the development process, suggesting next steps such as refinement or GitHub sync

• Educational nudges: Explains in simple language and prompts to connect databases, check docs, manage knowledge

🌊 Windsurf

• Technical empowerment: Trusts developer expertise, offering control through chat or direct code editing

• Minimum intervention: Only offers suggestions when needed

Key UX Difference from Handoff

✅ Guided vs. Self-directed

• Lovable acts as a mentor explaining next steps without jargon

• Windsurf operates as a companion that respects developer autonomy

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❺ Iteration

💜 Lovable

• Chat-centric: Iteration is driven through chat conversation where AI navigates and implements changes

• Visual editing: Provides basic visual editor, while code is not directly editable

🌊 Windsurf

• Code-first iteration: Fully editable codebase allowing granular AI-assisted edit line by line

• Fluid collaboration: Smooth transitions between manual coding and AI assistance

Key UX Difference from Iteration

✅ Pair Programming vs. Co-editing

• Lovable creates a pair-programming dynamic where the human navigates and AI drives

• Windsurf blends human and AI coding so seamlessly that the boundaries blur

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❻ Fixing errors

💜 Lovable

• One-click solutions: "Try to Fix" button for immediate error resolution

• AI as expert: Handles bugs that users might not understand, focusing on making it work over explaining why

🌊 Windsurf

• AI-augmented debugging: AI detects errors and suggests corrections

• Educational fixes: Explains the "why" behind solutions, allowing users to learn from observing AI's debugging patterns

Key UX Difference from Fixing Errors

✅ Auto Fix vs. Learn

• Lovable shields users from complexity by focusing on fixes

• Windsurf educates through the debugging process, helping developers improve over time

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Key UX takeaways

• ✅ Match context to confidence: Lovable removes friction for novices; Windsurf meets developers where they are

• ✅ Abstraction vs. Transparency: Beginners benefit from abstraction, experts from transparency

• ✅ Guidance vs. Autonomy: Lovable suggests what’s next; Windsurf waits for user intent

• ✅ Progressive disclosure: Both tools reveal complexity at different rates based on user needs

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Vibe coding spectrum shows that successful AI tools adapt their entire UX to match users' technical comfort levels

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Consider these questions for your AI products

👉 Position your product

• Where does your product fall on the expertise spectrum?

• Is your UX aligned with that position?

👉 Choose transparency level

• How transparent should your AI features be?

• When is it better to reveal the process vs. just show the result?

💡
Are you using AI to give users new powers, or to amplify what they are already capable of?