Uploaded August 2026 | Updated September 2026, 2 weeks ago
Platform link: career.krishnaik.in/dashboard/hackathons?h=smartreco-build-challenge-2026
his is not a simple "related products" widget. You are building an agentic recommendation system: a backend agent that continuously observes a user's activity, understands their interests, retrieves the most relevant products from a knowledge base, and generates personalized, convincing recommendations that update as the user's behavior changes.
A user lands on your platform and starts exploring — browsing products, searching, clicking around. Every meaningful action is tracked. Behind the scenes, an AI agent watches this activity build up, reasons over that behavior, retrieves the most relevant products, and generates a personalized recommendation — not a bare list, but a compelling message tailored to that user's journey. These recommendations are stored, shown on the site, and refresh as the user's behavior evolves
Platform link: career.krishnaik.in/dashboard/hackathons?h=smartreco-build-challenge-2026
his is not a simple "related products" widget. You are building an agentic recommendation system: a backend agent that continuously observes a user's activity, understands their interests, retrieves the most relevant products from a knowledge base, and generates personalized, convincing recommendations that update as the user's behavior changes.
A user lands on your platform and starts exploring — browsing products, searching, clicking around. Every meaningful action is tracked. Behind the scenes, an AI agent watches this activity build up, reasons over that behavior, retrieves the most relevant products, and generates a personalized recommendation — not a bare list, but a compelling message tailored to that user's journey. These recommendations are stored, shown on the site, and refresh as the user's behavior evolves
