6 months ago, my AI setup would get me maybe 20% of the way there. But I’d still have to do the heavy lifting to finish anything useful. At Raleon, we would run dozens of internal agents. A few of them worked beautifully. The rest would give me something half-baked, and for a while, I genuinely couldn’t figure out what was breaking. Although I had all the context I thought I needed, the AI kept stalling. Turns out, it was a lack of context. The agents knew essentially everything about Raleon, which was great. But it couldn’t accurately forecast where we needed to go. I was failing to feed it the broad context, like: • Where are we going with the product? • How are our sales calls actually going? • What am I thinking about for the roadmap? It was all just cluttered up in my head. It wasn’t until I realized that these things run on text, and almost everything I do is text or can become text. So I changed my approach and spent more time treating it like team members I was onboarding. I built out a real knowledge base with everything: ...