Cross-Functional Feature Discovery: How AI Teams Extract Product Priorities from Customer Conversations and Department Insights

Cross-Functional Feature Discovery: How AI Teams Extract Product Priorities from Customer Conversations and Department Insights

ByDarko Kolev

An AI startup engineer sits in a roadmap meeting with 47 feature requests spread across a Notion board—15 from the sales team promising they’ll close deals, 12 from support tickets about edge cases, 20 from the CEO’s conversations with design partners. Every stakeholder insists their requests are critical. The engineer, knowing they can ship maybe 3 features this quarter, faces the paralyzing question: which ones actually matter?

Take your RAG system to the next level

Take your RAG system to the next level

ByDarko Kolev

Retrieval-Augmented Generation (RAG) must be one of the most widely used systems in the world of Large Language Models to date. At its core, RAG combines the generative abilities of LLMs with a dynamic knowledge retrieval system, allowing models to access up-to-date, relevant knowledge base during generation. This knowledge base can be updated daily, without…

How to go from Jupyter notebook to Production AI system

How to go from Jupyter notebook to Production AI system

ByDarko Kolev

Let’s go over the few crucial steps when trying to build a real AI system people can use out of your precious AI demo. Start fresh The journey from a proof-of-concept Jupyter notebook to a production-ready AI system begins with a crucial decision: starting fresh. While your prototype notebook served as an invaluable experimental ground,…