"11 months ago I wasn’t using AI at work—at all. My team and I were building AI products used by tens of thousands of people. But when it came to using AI in my own job, I was a proud Luddite. I didn’t want to sound like 'the average of the internet.' I was worried that if I let AI tools do things for me, I’d lose my edge. When I tried using ChatGPT, I found it disappointing for strategic and innovative work—like consulting a chatty Wikipedia. Deep down, I felt discouraged that I didn’t know the exact magic spells of prompting that only influencers seemed to know. Then my eng manager showed me how to write perfect user stories by just talking to ChatGPT with context. I realized that AI tools had felt like blunt, generic instruments because I wasn’t providing enough context. LLMs can be highly effective for intelligent knowledge work, but only when we provide them with the same background knowledge that any person would need to do the same work. When LLMs have this valuable and ongoing context about our goals, our strategy, our role, our projects, and our wider org, they become our 'AI copilot'—a real thinking partner for long-term, complex work. Regardless of company size, vertical, or fluency in AI, many tech workers today are missing out for the same reason I was. They’re not giving LLMs the context needed to experience their full potential. Context changes everything." @talraviv has taught over 20,000 people how to build their own AI copilot. In today's 🔥 post, Tal shares how to change the way you think about working with AI, and how to practically construct your own AI copilot: