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  • Cross-Functional Feature Discovery: How AI Teams Extract Product Priorities from Customer Conversations and Department Insights
    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?
  • From 40+ Hours to 4 Clicks: How AI Transformed Client Reporting for a Marketing Agency
    What would your team do with an extra 20 hours each month? For one marketing agency, this wasn’t a hypothetical question—it was a business transformation I helped deliver. The Reporting Nightmare Recently, I partnered with a mid-sized marketing…
  • Take your RAG system to the next level
    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…
  • How to go from Jupyter notebook to Production AI system
    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…

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