Big Ideas 2026: The Enterprise Orchestration Layer

2026 is when multiplayer mode comes into gear. If you have a bunch of agents autonomously working, isn't there potential for a huge, you know, multi agent cascade of failures? There's a lot of narrative around AI helping automate work and reducing cost. But I think in instances where AI is actually reinforcing the business model in driving revenue, there's really no limit to the amount that customers may wanna adopt that technology. It's not AI that's the competition. It's your competitors using AI. Every year, we step back and ask a simple question. What will builders focus on next? Our twenty twenty six big ideas bring together the themes our investing teams believe will shape the coming year in tech. This episode is built around one big idea. AI is becoming an orchestration layer inside the enterprise, not a collection of standalone tools, a coordinated system of agents that can plan, analyze, and execute work across departments and software. You'll hear four perspectives of what changes when AI starts running the workflow, how organizations extract context, why legacy replacement accelerates, what multiplayer AI looks like in practice, and what makes these systems commercially defensible. To understand the shift, we start with the enterprise wide view. Seema Amble argues that the move from experimentation to coordinated multi agent systems will force organizations to extract tacit knowledge from documents, processes, and people's heads, turning it into usable operational context. Here's Seema. Hi. I'm Seema Amel, a partner on our apps investing team. My 2026 big idea is that AI will create a new orchestration layer and new roles, particularly in the Fortune 500. In 2026, enterprises will shift further from isolated AI tools to multi agent systems that'll need to behave like coordinated digital teams. As agents start to manage complex, interdependent workflows, like planning, analyzing, and executing together, organizations will need to rethink how work is structured and how context flows across these systems. The Fortune five hundred will feel this shift most acutely. They sit on the deepest reservoirs of siloed data, institutional knowledge, and operational complexity, much of which sits in people's brains. To get this context out of people's brains, it's some combination of collecting documentation and watching human actions. What's the documentation? It could be onboarding videos, written instructions, full documentation that's been written up. And then the watching human actions is literally watching how humans are clicking on to their browsers, the actions they take, the phone calls they make, etcetera, and then piecing this together as shared context. What needs to be solved across these agents? It's providing the feedback across the agents and being able to ultimately determine, in this case, who is a good customer and are we getting the ROI, how we're spending our dollars or our time. To put that even more concretely, customer support needs to be able to say, this is a bad customer, sales. You should spend less time prioritizing customer a and go for a customer …