AI-FIRST FULL-STACK DEVELOPMENT

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About The Course

AI-First Full-Stack Development focuses on building modern web applications by integrating artificial intelligence at every stage-from backend logic to user experience. Instead of adding AI as an afterthought, this approach prioritizes AI-driven features like automation, personalization, and intelligent decision-making from the start. It combines traditional full-stack skills with tools like machine learning models, APIs, and AI frameworks to create smarter, faster, and more scalable applications.

Key points

Lessons of the Course

MODULE 1: AI-AUGMENTED FRONTEND & MODERN UI

 

The AI-First Developer Workflow

  • Setting up modern IDEs: Cursor, GitHub Copilot, and v0.dev
  • Mastering "Composer" and "Chat" modes for rapid feature scaffolding
  • Project: Scaffold a high-fidelity SaaS landing page from a text description using AI-assisted Tailwind CSS

React & Next.js Core

  • Functional components, Hooks (useState, useEffect), and Server Actions
  • Managing state in the AI era: Context API vs AI-generated state logic
  • Libraries: React, Next.js, Framer Motion for AI-driven animations

Prompt Engineering for Frontend

  • Writing "UI-System" prompts to maintain design consistency
  • Project: Build an interactive AI dashboard with real-time data visualization and responsive layout patterns
MODULE 2: INTELLIGENT BACKEND & VECTOR ARCHITECTURES
 
Server-Side Logic & LLM Integration
  • Building RESTful and GraphQL APIs with Node.js and Express
  • Connecting to leading AI APIs: OpenAI, Anthropic (Claude), and Google (Gemini)
  • Libraries: LangChain, OpenAI SDK
  • Project: Build a smart API that automatically categorizes and summarizes incoming user data
Vector Databases & RAG (Retrieval-Augmented Generation)
  • Moving beyond SQL/NoSQL to vector stores: chunking, embeddings, and semantic search
  • Databases: MongoDB Atlas (Vector Search), Pinecone, ChromaDB
  • Project: Build a "Chat with your Database" feature using natural language queries
Authentication & Secure Data Flow
  • Using NextAuth or Clerk for AI-first authentication
  • Securing API keys and managing LLM rate limits in production
MODULE 3: AGENTIC WORKFLOWS & FULL-STACK DEPLOYMENT
 
Introduction to Agentic AI for the Web
  • Building autonomous loops using the "Reason-Act" (ReAct) pattern in web applications
  • Frameworks: CrewAI (Integration), LangGraph, Vercel AI SDK
  • Project: Build an autonomous support agent that reads documentation, checks order status via API, and responds to users
Deployment & AI Observability
  • Deploying full-stack AI applications on Vercel, Railway, or Docker
  • Monitoring LLM performance and tracing hallucinations
  • Tools: LangSmith, Helicone, Arize Phoenix
Capstone: The AI-First Startup MVP
  • The Sprint: Build a fully functional AI-powered SaaS (e.g., automated SEO content engine or AI legal document auditor)
  • Deliverable: A live production URL and a system design audit proving scalability of your AI logic
TOOLS & LIBRARIES SUMMARY
 
Tools & Libraries Summary: The AI-First Stack
Category Primary Tools & Libraries
IDE / Workflows Cursor (IDE), v0.dev, GitHub Copilot
Frontend React, Next.js, Tailwind CSS, Shadcn/UI
Backend Node.js, Express, FastAPI (for Python AI scripts)
Intelligence LangChain, Vercel AI SDK, OpenAI/Claude APIs
Databases MongoDB (NoSQL), Pinecone (Vector), Redis (Cache)
Ops & Monitoring Vercel, Docker, LangSmith, GitHub Actions

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Instructor

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Fred Adams

Senior Software & Enterprise Architect

This course includes:

₹3599

₹8000