Wayfair AI Agent Engineering for Business Intelligence

Status: 🏗️ In-Progress

This repository documents an 8-week technical externship focused on building autonomous AI agents to solve high-scale e-commerce challenges for Wayfair.

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🎯 Project Milestones:

• Project 1: Moodboard Agent(The Creative Foundation) – Transforming style prompts into curated visual outputs.

  • Lab 01 Moodboard Generator AI Agent
  • Product Requirement Document

• Project 2: Market Trend Discovery – Building agents to scrape and analyze product data and social media.

  • Lab 02 Discovery AI Agent
  • Product Requirement Document

• Project 3: Competitor Benchmarking (Monitoring Agent) – Tracking competitor launches and pricing to identify "whitespace" opportunities.

  • Lab 03 Competitor Monitoring AI Agent
  • Product Requirement Document

• Project 4: AI Insight & Content Agent – Using Gemini to turn raw signals into marketing content and campaign ideas.

  • Lab 04: Content Strategy AI Agent
  • Product Requirment Document

• Project 5: Unified Market Intelligence Dashboard – Designing a live, auto-updating Google Sheets tool for supply chain managers.

  • DEMO: UI Prototype Walkthrough using Base44
  • Read about Prototype
  • PRD Case Study DEMO | PRD Case Study Presentation PDF
  
  
  • Lab 05: Final AI Agent
  • Final Deliverables
    • EXTERNSHIP PROJECT DEMO
    • View JSON: Updated Market Trend AI Agent
    • View JSON: Updated Competitor Monitoring AI Agent
    • View JSON: Dashboard Builder AI Agent

View All Labs & Artifacts: Agentic Workflow Hub

🛠️ Skills Gained

• AI Agent Development: Building autonomous workflows using n8n.

• Market Intelligence: Scraping and analyzing competitor data for whitespace discovery.

• Prompt Engineering: Designing high-fidelity prompts for Gemini to ensure brand-aligned outputs.

• Dashboard Design: Visualizing real-time data pipelines for business stakeholders.

• Infrastructure & DevOps: Deploying and managing Docker containers to maintain a consistent, isolated development environment for n8n.

• Orchestration: Designing multi-agent systems and complex agentic workflows using n8n.

• LLM Implementation: Advanced prompt engineering and model benchmarking with Gemini 2.0 and Mistral.

• Data Engineering: Automated web scraping, attribute extraction, and structured data processing.

• Generative Media: Integration of vision-language models (FLUX via Hugging Face) for automated asset creation.

Key Technical Details

• Automation Engine/Orchestration: n8n (Self-hosted via Docker)

• LLM: Google Gemini (via Google AI Studio)

• Dashboard: Google Sheets API

• Hardware Baseline/Environment: Local execution (8GB RAM / Intel i3 or above)

• Memory: Logginh, Wait, and Merge/Code Nodes

• Infrastructure: Docker (Containerized workflow management)