Eighteen years ago, we built Hootsuite because social was changing how the world communicated. The goal back then was simple: Help brands show up and not miss the moment. I came back a few months ago. One of the first calls we made was harder to explain. We took apart products that worked. Not because they were broken. Because “working” wasn’t going to be enough for what’s coming, and I’d rather risk confusion now than wake up irrelevant later. Why we broke something that worked The honest version: The market didn’t give us a choice. Here’s the thing I keep sitting with. Most AI is trained on the past. It’s very good at summarising, drafting, and reasoning over what already happened. But it’s close to blind on what’s happening right now: What people are saying about your brand this morning, the trend that lands and is gone by lunch, the narrative forming before anyone on your team flags it. Every AI vendor is promising intelligence. Most are delivering pattern recognition trained on public data that’s weeks or months old. That gap – between what the model knows and what’s actually happening in your market – is huge, and getting wider. We have something they don’t: a live signal layer built over eighteen years, across 150 million sources, 187 languages, and every major platform. That’s not a dataset. It’s the closest thing to a real-time read on what people actually think that exists in a commercial product. The signal most AI can’t see Social-first AI is built on top of live social intelligence, not a general-purpose language model with social features bolted on. The difference matters: General AI tells you what was true. Social-first AI tells you what’s true right now, in your market, about your brand. The signal is there.