@ScribeHow just crossed $100M ARR. Today, our 90,000 enterprise customers include nearly half the Fortune 500. I shared this news with @jonfortt on @CNBC earlier today, but I still vividly remember our first deal for $7K! I’m proud of our team and grateful for our customers. The reality is, we’re just in the first inning. Most companies are still very far from the AI transformation they imagined. A lot of AI usage at work is still for personal productivity: it’s not locked into where and how an org creates its value. The models aren’t the problem. It’s that they aren’t being taught enough about the business. AI has a context problem. AI gets dropped into companies
without knowing HOW work actually gets done. That’s thousands of workflows AI can’t see. Dozens of decisions it can’t trace or recreate. AI doesn’t understand your org at all.
 Missing workflow context is now an existential problem for the enterprise. Without context, AI can’t function. It just delivers generic output, or confidently gets things wrong. For AI to actually work inside enterprises, something fundamental has to change. That’s why we’re witnessing a new layer of the enterprise stack emerge. To pull ahead companies need to map their context layer, making it legible to both humans and agents. Here's my full thinking on workflow context and why it’s the most urgent need in enterprise AI: