Instead of each employee using their own separate AI, the more effective model is a central, multiplayer AI that acts as a shared 'company brain' or teammate. This approach, which Motion is building with its 'Runneth' agent, prevents duplicated efforts and builds a shared company-wide context.

Consumer AI like ChatGPT has broad context but lacks the specific depth needed for business problems. To get great results from enterprise AI, you must provide it with deep, rich context like unified customer data, campaign history, and internal team conversations. Quality output is a direct function of context depth.

Despite AI's capabilities, it lacks the full context necessary for nuanced business decisions. The most valuable work happens when people with diverse perspectives convene to solve problems, leveraging a collective understanding that AI cannot access. Technology should augment this, not replace it.

When everyone on the team shares the same deep understanding of the customer's world, communication can be imperfect. The shared context fills in the gaps, preventing the "translation errors" that plague teams trying to operate from detailed specs alone.

The most significant value of AI in revenue teams isn't merely automating tasks like deck creation. Based on 30,000 real workflows, top teams use AI primarily to synthesize data and understand what's happening in an account, ensuring the outputs are strategic, contextual, and aligned with sales methodology.

Capturing the critical 'why' behind decisions for a context graph cannot be done after the fact by analyzing data. Companies must be directly in the flow of work where decisions are made to build this defensible data layer, giving workflow-native tools a structural advantage over external data aggregators.

To empower a distributed team of human and AI 'makers,' strategic context can no longer be implicit or tribal knowledge. It must be explicitly codified and continuously accessible as a living document to guide day-to-day trade-off decisions for both people and automated agents.

For an AI agent to be effective, "context" isn't just data access. It's understanding an organization's fluid, internal shorthand—definitions, acronyms, and unwritten rules like "top spenders in EMEA." This evolving knowledge is often buried in emails and meeting transcripts, not formal documents.

Counterintuitively, AI's greatest value for product managers comes from ingesting and synthesizing vast amounts of context—customer calls, data, internal documents—rather than just generating artifacts like PRDs. Superior context is the foundation for high-leverage decisions that multiply a company's output.