Post by Insight Partners

We're entering the third phase of AI, where outcomes matter more than adoption. First came the push to adopt AI. Then came the wave of tools, pilots, and proofs of concept across every function. Now comes the harder question: What did all of that actually deliver? For many organizations, the answer is better individual productivity, but little enterprise-wide impact. The context layer is emerging as the foundation for enterprise AI: a shared source of organizational knowledge that improves every AI workflow over time. Led by Insight Partners' Travis Kassay and Jack Rohrer, joined by VenturEd Solutions' Robert Rainey, last week's Onsite Hour covered what a context layer is, how to stand up a v1 in a few hours, and what it looks like at scale. Three takeaways for operators: • Context is how your company makes decisions, written down where your AI can read it. Models commoditized raw intelligence; the edge is the curated knowledge about your business that the model can't infer. • The context layer has three scopes: org, function, and user. No new infrastructure, and no fleet of agents required to get to value. A few good skills on a shared context layer are the whole Level 1 play. • Governance is what makes it compound. One named owner per file, clear update triggers, a light cadence. Do that, and every session runs smarter than the last. Roles don't disappear; they elevate. Most teams are one week away from a working context layer. The barrier isn't technical; it's deciding to treat context as an asset worth maintaining. Want more conversations like this? Join us at ScaleUp:AI on October 6, where top founders, executives, and AI innovators share practical lessons on building, deploying, and scaling AI. Learn more and register: https://scaleup.events/