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The Universal Adapter: How the Model Context Protocol (MCP) Connects AI to the Physical World
Over the past few weeks, we’ve systematically broken down the architecture of modern enterprise AI. We established the foundational blueprint in Deconstructing AI, zoomed into the core matrix-math in Deconstructing the Brain, explored how static intelligence becomes autonomous in The Agentic Control Loop, and mapped out multi-agent collaboration in Deconstructing the Swarm. But despite all this advanced architecture, there is still one massive, glaring hole. An autonomous age

Sathish Kumar
Jun 265 min read


Deconstructing the Swarm: How the Agent-to-Agent (A2A) Protocol Drives AI Collaboration
Over the past few weeks, we have been building a complete mental model of modern AI architectures. In Part 1, Deconstructing AI, we laid out the high-level orchestration of Large Language Models, Agents, and MCP servers. In Part 2, Deconstructing the Brain, we zoomed all the way in to reveal the frozen matrix-math that makes up an LLM. Then, in Part 3, The Agentic Control Loop, we evolved that passive brain into a dynamic entity, wrapping it in a continuous Sense-Think-Act lo

Sathish Kumar
Jun 205 min read


The Agentic Control Loop: How AI Agents Execute Autonomous Actions
In my foundational piece, Deconstructing AI, I laid out the high-level architecture of how Large Language Models, Agents, and MCP servers interact. Then, last week in Deconstructing the Brain, we zoomed all the way in. We cracked open the LLM itself to reveal its structural reality: a frozen file of billions of numerical parameters processing data via pure matrix math. We saw how an LLM acts as an incredible static reasoning engine, taking a prompt and outputting a highly pre

Sathish Kumar
Jun 145 min read
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