AI Stack
The collection of technologies and human inputs that work together to turn artificial intelligence into a practical tool for completing real-world work. The emerging AI Tech Stack can be understood as five layers: the AI Model provides intelligence, the AI Harness provides the environment, Model Context Protocol (MCP) provides the connection, Knowledge provides the domain expertise, and the Human provides judgment.
Putting the AI Tech Stack in Context
When most people talk about artificial intelligence, they tend to focus on the model.
- GPT.
- Claude.
- Grok.
- Gemini.
But the underlying AI model is only one piece of the system that makes modern AI useful.
A model needs an environment through which people can interact with it. It needs ways to connect with outside tools and information. For specialized professional work, it needs domain-specific knowledge, data, and methodologies. And ultimately, it needs a human to review its work and apply judgment.
Together, these layers form what we can think of as the AI Tech Stack.
A useful way to understand the emerging AI stack is:
- AI Model = Intelligence
- AI Harness = Environment
- MCP = Tools
- Knowledge = Domain Expertise via Agent Skills or Context as a service
- Human = Judgment
Each layer solves a different problem.
Frequently Asked Questions about the AI Tech Stack
What is the AI Tech Stack?
The AI Tech Stack is the collection of technologies and human inputs that work together to make artificial intelligence useful for real-world work. One way to understand the emerging stack is through five layers: AI Model, AI Harness, Model Context Protocol, Context as a Service, and Human Judgment.
What are the five layers of the AI Tech Stack?
A useful framework is: AI Model = Intelligence; AI Harness = Environment; MCP = Connection; Context as a Service = Domain Expertise; and Human = Judgment. Each layer solves a different part of the problem of turning general-purpose AI into a useful professional tool.
What role does the AI Model play in the AI Tech Stack?
The AI Model provides the underlying intelligence and reasoning capabilities. Models such as GPT, Claude, Gemini, and Grok can understand information, reason through problems, create content, analyze data, write code, and perform other cognitive tasks.
What role does the AI Harness play?
The AI Harness provides the environment through which a person interacts with and uses an AI model. Depending on the harness, it may provide interfaces, tools, files, memory, browsers, terminals, permissions, and other capabilities.
What role does MCP play in the AI Tech Stack?
Model Context Protocol provides a standardized way for compatible AI applications to connect with external tools, data, and systems. In the five-layer framework, MCP represents the connection layer.
What role does Context as a Service play?
Context as a Service provides specialized data, methodologies, tools, and domain knowledge that help general-purpose AI perform work within a particular industry or organization. In the AI Tech Stack, it represents the domain expertise layer.
Why is the human part of the AI Tech Stack?
The human provides judgment, accountability, experience, and decision-making. AI can perform increasingly complex research, analysis, and production work, but the professional remains responsible for reviewing outputs and making consequential decisions.
How does the AI Tech Stack apply to commercial real estate?
In commercial real estate, an AI model can provide intelligence, an AI Harness can provide the working environment, MCP can connect that environment to external capabilities, a Context as a Service platform such as CRE Agents can provide specialized CRE methodologies and data, and the CRE professional can apply judgment to the resulting analysis and decisions.
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