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?
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…
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…
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…