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Yevgen Somochkin

"ESSO"

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Building the Future of AI & Automation | Full-stack & DevOps Architect | n8n | Scalable, Data-driven Web & Mobile Apps | Salesforce x2 certified

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Yevgen Somochkin

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Software Engineer & Architect

Hamburg, Germany

Strategic Use of AI Models in Web & Mobile App Development (2025 Edition) 🌐📱

Oct 12, 2025

Artificial Intelligence has become a cornerstone of modern software development. Whether you are building a web app, a mobile product, or an entire ecosystem, large language models (LLMs) can help at every stage — from brainstorming and prototyping to deployment and support.

With so many options available today — GPT-5, Claude 4, Gemini 2.5, Grok 4, and open-source models like LLaMA 4 or Qwen 2.5 — the key question is: which model should you use, and when?


1. Idea Validation & Product Planning

Goal: Rapid prototyping, brainstorming features, drafting requirements.

  • Claude 4 Opus → excels at long-form reasoning and structured PRDs.
  • GPT-5 Pro → turns vague ideas into concrete technical roadmaps.
  • GPT-5 Mini → lightweight for quick brainstorming and comparing multiple feature sets.

💡 Pro Tip: Use Claude for deep narratives and GPT-5 Mini for fast iterations before committing to architecture decisions.


2. UI/UX Design Assistance

Goal: Wireframes, user flows, design-to-code transitions.

  • Gemini 2.5 Pro → best for multimodal workflows (text + image).
  • GPT-5 Pro → generates React Native / Flutter boilerplate.
  • Gemini Flash Lite → fast iteration and multiple UI variants.

🎨 Design Tip: Generate 3–5 UI variants quickly with Gemini Flash Lite and iterate with your team.


3. Backend & API Development

Goal: Writing scalable backend code, database schemas, integrations.

  • GPT-5 Pro → complex backend logic.
  • Claude Sonnet → logic validation and error reduction.
  • LLaMA 4 (open-source) → private, on-premise workflows.

⚙️ Backend Tip: Use Pro models for critical logic, Mini/Open-source for repetitive CRUD or unit tests.


4. Mobile Development (iOS & Android)

Goal: Platform-specific code, SDKs, smooth UX.

  • GPT-5 Pro → Swift/SwiftUI and Kotlin/Compose.
  • Gemini 2.5 Pro → cross-platform integration (React Native / Flutter).
  • GPT-5 Mini → boilerplate code.

📱 Mobile Tip: Reserve Pro models for tricky UI states; use Mini for scaffolding views/forms.


5. Debugging & Refactoring

Goal: Improve performance, readability, maintainability.

  • Claude 4 Sonnet → step-by-step debugging.
  • GPT-5 Pro → automated refactoring.
  • LLaMA 4 → local/private debugging.

🐞 Debugging Tip: Ask Claude Sonnet to explain refactor suggestions to help new developers understand architecture decisions.


6. Deployment & DevOps

Goal: Infrastructure scripts, CI/CD pipelines, container orchestration.

  • GPT-5 Pro → Terraform, Kubernetes, Docker scripts.
  • Claude Sonnet → security checks and validation.
  • Grok 4 Heavy → live monitoring, system alerts.

🚀 DevOps Tip: Automate routine scripts with Mini/Flash models, but review sensitive infra with Pro.


7. Continuous Monitoring & User Feedback

Goal: Real-time insights, analytics, user feedback.

  • Grok 4 Light → streams & analytics.
  • GPT-5 Mini → feedback classification.
  • Gemini Flash → visual dashboards.

📊 Monitoring Tip: Combine Grok streams with Gemini Flash dashboards for faster team decisions.


8. Cost-Effective Workflows

  • Pro models (GPT-5 Pro, Claude Opus, Gemini Pro) → high-stakes tasks: architecture, critical code.
  • Mini/Light models (GPT-5 Mini, Gemini Flash Lite, Grok Light) → repetitive, high-volume tasks.
  • Open-source (LLaMA 4, Qwen 2.5, DeepSeek) → privacy, local workflows, cost savings.

📊 Model Comparison (2025)

CategoryModelsStrengthsBest Use CasesCost
Pro / HeavyGPT-5 Pro, Claude Opus, Gemini 2.5 Pro, Grok 4 HeavyHigh accuracy, complex reasoningBackend, architecture, security-critical code💰💰💰
Mini / LightGPT-5 Mini, Gemini Flash Lite, Grok 4 Light, Claude HaikuFast, cheap, scalableChatbots, boilerplate, bulk content💰
Balanced Mid-TierClaude Sonnet, Gemini Flash, GPT-5 DistilledStable reasoning, moderate costDebugging, medium automation, UX flows💰💰
Open-SourceLLaMA 4, Qwen 2.5, Gemma, DeepSeekPrivate, customizable, localConfidential workflows, on-premise apps💸

🗝️ Legend (Model Badges)

  • 🟢 Pro / Heavy Models → high accuracy, mission-critical tasks
  • 🔵 Mini / Light Models → fast, cheap, repetitive tasks
  • 🟣 Open-source / Local Models → private, on-premise, cost-efficient

Pro models → mission-critical tasks
Mini/Light → repetitive & fast tasks
🔒 Open-source → private & local workflows


🛣️ Horizontal AI Development Roadmap

💡 Idea / Planning
  ──> 🟢 GPT-5 Pro | 🟢 Claude 4 Opus | 🔵 GPT-5 Mini
       │
       ▼
🎨 UI/UX Design
  ──> 🟢 Gemini 2.5 Pro | 🟢 GPT-5 Pro | 🔵 Gemini Flash Lite
       │
       ▼
⚙️ Backend & API
  ──> 🟢 GPT-5 Pro | 🟢 Claude Sonnet | 🟣 LLaMA 4 / Qwen 2.5
       │
       ▼
📱 Mobile Development
  ──> 🟢 GPT-5 Pro | 🟢 Gemini 2.5 Pro | 🔵 GPT-5 Mini
       │
       ▼
🐞 Debugging & Refactoring
  ──> 🟢 Claude Sonnet | 🟢 GPT-5 Pro | 🟣 LLaMA 4
       │
       ▼
🚀 Deployment & DevOps
  ──> 🟢 GPT-5 Pro | 🟢 Claude Sonnet | 🟢 Grok 4 Heavy
       │
       ▼
📊 Monitoring & Feedback
  ──> 🟢 Grok 4 Light | 🔵 GPT-5 Mini | 🔵 Gemini Flash
       │
       ▼
💸 Cost / Privacy Layer
  ──> 🔵 Mini/Light Models | 🟣 Open-source Models