The Building Blocks of an AI Agent
What an agent needs
Core components
Most agentic systems have a few common parts: a goal, a policy or decision process, a memory, tools, and a feedback loop. The goal says what success looks like. The decision process chooses actions. Memory helps the agent keep track of context. Tools let it interact with the outside world. Feedback tells it whether the action helped.
Core terms
How the loop works
A typical loop is: observe → think/plan → act → observe results → update. This cycle can repeat many times until the goal is reached or the system stops for some reason.
A simple agent loop
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Step 1: Read the current task and context.
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Step 2: Decide the next best action.
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Step 3: Use a tool or produce output.
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Step 4: Check the result and continue if needed.
Important idea
An agent does not need to be perfect. It needs to be able to keep working across multiple steps.
Which component helps an agent remember earlier context?
Memory stores information the agent can reuse later.
Correct answer: Memory
Name one external capability that can count as a tool for an AI agent.
Many answers are valid, such as search, calculator, browser, database, or API access.
Correct answer: Search engine
INSIDE THE AGENT
Four core building blocks every agent needs
Perception
Reading the world: text, files, APIs, sensor data
Memory
Short-term (context window) and long-term (vector DBs)
Reasoning
The LLM core: planning, deciding, generating steps
Action
Executing: calling tools, writing output, triggering APIs
Agent Architecture Flow
Files · APIs · Web · Databases
Parses and formats observations
ReAct / CoT / Plan-then-Execute
Runs code, searches web, sends requests