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To combat inefficiency, Kevin Scott is pushing for a standard protocol for all internal Microsoft agents to communicate with its systems. This is a deliberate strategy to fight Conway's Law, which suggests that systems tend to mirror the communication structures of the organizations that build them.

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To create an integrated product suite, Cisco dismantled divisional silos and restructured into a platform-based organization. An org chart directly dictates product architecture, so leaders must design their organization to produce the desired integrated outcome, not just individual products.

Microsoft canceled internal licenses for tools like Cloud Code not for cost reasons, but as a strategic "dogfooding" mandate. The move forces its developers to use and improve Microsoft's own Co-pilot CLI, accelerating internal product development by making engineers their own first customers.

The need for a Solution Architect often signals a failure in organizational design. It's a workaround for teams not communicating effectively, a problem better solved by applying principles from frameworks like Team Topologies to foster cross-team collaboration directly.

Customers interact with a company as a single entity, but internally, separate departments like sales and support optimize for their own conflicting metrics. This creates a confusing and inefficient experience, a direct result of Conway's Law in action.

To design a company for AI agents, enforce a culture of clear, precise writing in public channels like Slack. This "ambient signaling" creates a rich, contextual knowledge base for future agents to act upon. This is supported by a no-meetings, no-PM culture to maximize written output.

For agents to become truly powerful, they need an open ecosystem similar to the internet. Kevin Scott highlights protocols like MCP and NLweb as foundational layers that serve the same purpose as HTTP and HTML, enabling interoperability and allowing agents to take action across diverse systems.

Microservices were primarily a solution for organizing human teams and managing cognitive load (Conway's Law). Since AI agents lack these limitations, the architectural rationale weakens. Companies can revert to monolithic repositories to avoid network overhead and complexity, as an AI can manage a codebase far too large for any human.

Instead of siloing agents, create a central memory file that all specialized agents can read from and write to. This ensures a coding agent is aware of marketing initiatives or a sales agent understands product updates, creating a cohesive, multi-agent system.

Based on Conway's Law, a company's internal structure and communication paths are mirrored in the architecture of the software it produces. This means human values flow from the organization to the product. To build aligned AI, you must first solve for human alignment within the company.

Instead of creating one monolithic "Ultron" agent, build a team of specialized agents (e.g., Chief of Staff, Content). This parallels existing business mental models, making the system easier for humans to understand, manage, and scale.