← Agent Development15 · Agent Development
How Are AI Agents Built?
An AI agent is not one model or one tool. It is a system that combines model intelligence with instructions, tools, state, and an execution loop.
Main architecture
From a user goal to a result
User goal
↓
Agent System
ModelInstructionsPlanningState / MemoryAgent Loop
↓
TOOLS / MCP / APIsApproved actions the system can call
↓
EXTERNAL SYSTEMSBrowser · Database · Files · Business Apps
↓
Result
HUMAN APPROVALReview or confirm sensitive actions.
CONTROLPermissions, limits, logs, and stop conditions.
The core building blocks
Six pieces working together
THINK
Model
Generates or reasons about the next useful step.
DIRECT
Instructions / System Prompt
Sets the role, rules, context, and boundaries.
ACT
Tools
Lets the system take approved actions in the world.
REMEMBER
State / Memory
Keeps task context, history, and useful information.
CONNECT
API / MCP
Provides a structured bridge to external capabilities.
CONTROL
Permissions / Human Approval
Defines what can happen automatically and what needs review.
The agent loop
Action happens in a cycle
GOAL
→
OBSERVE
→
PLAN / DECIDE
→
ACT
→
OBSERVE RESULT
→
UPDATE STATE ↺
Goal completedBlockedApproval requiredFailure / stop condition
The loop continues until one of these conditions is reached.
One simple example
“Check order 123 and draft an update email.”
01User Goal
→
02Agent reads order ID
→
03Tool call: get_order("123")
→
04System returns status
→
05Agent updates state
→
06Agent drafts email
→
07Human reviews → send if approved
Common agent patterns
Four common shapes
SINGLE AGENT + TOOLS
One agent uses a set of tools to complete a task.
AGENT + RAG
An agent retrieves relevant knowledge before acting.
AGENT + HUMAN APPROVAL
The agent proposes actions while a person controls sensitive steps.
MULTI-AGENT
Several specialized agents coordinate on one larger task.
Where frameworks fit
Frameworks assemble the pieces
BUILDING BLOCKSModel · tools · state · loop
→
FRAMEWORKOrchestration and reusable patterns
→
APPLICATIONA useful experience for people
Frameworks help developers assemble and manage these pieces. Explore Agent Frameworks →
Agent vs model
Capability vs system
MODEL
Generates and reasons.
+
AGENT SYSTEM
Uses model capability inside an action loop.
Model + Tools + State + Loop = Agent System
Agent vs workflow
Dynamic vs predefined
AGENT
Can dynamically decide the next steps.
↔
WORKFLOW
Often follows predefined steps.
Real systems can combine both.
Remember this
An agent is a system
An AI agent is built by combining a model with instructions, tools, state, and a loop that lets it act toward a goal.
Acceptance check
HOW AGENTS ARE BUILT PAGE PASS / FAIL
PASS when you can explain what an Agent is made of, Model vs Agent, the Agent Loop, Tools / State / MCP, and Agent vs Workflow.