I call this the “gossip workflow” - basically keeping my AI copilot updated with every hallway conversation, stakeholder interaction, and project update as they happen. Here’s how it works: When the founder dropped an urgent request for “low data mode” at Riverside, I immediately shared that context with my copilot. Then throughout the initiative, I kept gossiping to it. When I sent the initial context, it reminded me to involve our CRO, early - something it knows I’m bad at because I’ve shared my performance review feedback. When the head of marketing caught me in the hallway worried about brand impact, I told my copilot right away: “I just had this hallway conversation with our head of marketing, and he’s really concerned that releasing a feature like this could hurt our brand.” The copilot remembers all these interactions. It knows our product principles, stakeholder preferences, and my growth areas. It can generate a one-on-one agenda for my head of marketing or adapt when I say “actually, he’s really busy - what would I say if I only have 5 minutes at lunch?” At project end, when our feature didn’t get adopted (hosts used it once but not twice), I asked it to summarize all lessons learned. It created a document with checklists and qualifying when to apply these lessons. One click adds this back to project knowledge, instantly informing all future initiatives. ➡️ Instead of treating AI as a one-off tool, treat it like a team member you keep in the loop. The more context it has throughout the product lifecycle, the better it gets at anticipating what you need and who you should talk to.