AI Agent Architecture: Intelligent System Built in 4 Layers
KoKyat2 min read·Just now--
In the future AI Governance system, AI Agents will not only be data collectors but also autonomous entities that can make their own decisions. According to KoKyat Logic, a robust and systematic AI Agent should be built in the following (4) layers.
- Logic Layer
This is the DNA or policy of an Agent.
Action: The core logic that defines what the Agent should and should not do.
Importance: If the Logic Layer is not robust, the Agent can go astray, so it is built as the “constitution” of the system first.
2. Reasoning Layer
This is the thinking process of the Agent.
Action: The received data is compared with the Logic Layer and the “why” and “how” should be considered.
Importance: In this layer, AI decides on an action only after performing multi-step reasoning.
3. Action Layer
This is the execution layer of the agent.
Action: Use external APIs or tools to implement the results of the analysis.
Importance: This layer is responsible for not only thinking but also having an impact.
4. On-chain Layer (Recording and Verification)
This is the accountability layer of the agent.
Action: Every action and result of the agent is recorded on the Blockchain.
Importance: This layer makes the agent’s decisions verifiable and transparent.
Conclusion
When these four layers are combined, an AI agent will have the following characteristics: Logic, Reasoning, Action, and On-chain. This is the systematic AI agent design guided by KoKyat Logic.
