AI Research Hub
Resarch The Concept
Product Design | 2026
Background
As AI became a larger part of our daily workflow, we identified a recurring challenge: every new project required providing the same company, product, and user context to AI tools. This slowed down research and often led to inconsistent outputs. To solve this, I created a centralized research framework that gives AI tools a shared understanding of our products, users, competitors, and design principles.
The Mission
Work Process
The idea was to create one centralized repository containing all the context required for AI tools to understand our business, products, users, competitors, and design principles. Before starting a new project, I can run a dedicated workflow that analyzes this information and generates an initial research report, providing a broader perspective for product and design decisions.
Building the Knowledge Base
To support this workflow, I created a structured repository containing:
*README Documentation – Defines the workflow structure and helps AI tools navigate the repository efficiently while reducing token consumption.
*AI Agents – Four specialized agents (PM, UX, UI, and Development) work in parallel, while a Team Lead agent consolidates all findings into a final report with recommendations and next steps.
*Product Documentation – Detailed information about each product, including goals, features, audiences, and business context.
*Competitor Research – A continuously updated database of competitors, feature comparisons, and market insights gathered through ongoing research.
*Design Guidelines – Documentation of each product’s design system, including visual rules, typography, colors, and constraints.
*User Research – A centralized collection of user interviews, insights, and pain points to ensure user needs remain at the center of every decision.
All of this information is maintained in a dedicated repository shared across the team. I also created a custom workflow that can access the entire knowledge base in a single execution, allowing the research process to be completed much faster while maintaining consistency and depth.
Outcome
The result is a powerful research engine that combines company knowledge, user insights, competitor analysis, and AI automation into one workflow. It significantly improves research quality, accelerates project kickoffs, and helps the team make more informed product and design decisions with greater confidence.
For more work
noyadani3010@gmail.com