The Architecture of a Modern AI Agent

The Five Core Components

Component	Role
Orchestrator	The “operating system” of the AI agent. It receives the user’s request, creates and manages the execution plan, maintains workflow state, schedules tasks, handles retries, coordinates tool usage, and determines when the objective has been completed.
Large Language Model (LLM)	The reasoning engine. It interprets the current task, decides which tool to use next, analyzes results, writes content, generates code, and helps refine the execution plan when needed.
Tools	External capabilities available to the agent, including browsers, terminals, file systems, code execution environments, APIs, databases, email, calendars, and enterprise applications.
Instructions	Product-specific guidance that defines the agent’s behavior, including system prompts, best practices, safety policies, coding standards, and domain expertise.
Memory & Context	The working memory of the agent, including conversation history, intermediate results, project files, user preferences, and long-term context that enables complex, multi-step tasks.

How an AI Agent Works

Unlike a traditional chatbot that generates a single response, an AI agent continuously cycles through reasoning and action until the task is complete.

A simplified execution loop looks like this:

1. The user submits a high-level objective.
2. The orchestrator creates an execution plan and initializes the workflow.
3. The orchestrator sends the current task to the LLM.
4. The LLM decides whether to reason further or invoke a tool.
5. The selected tool executes and returns its results.
6. The orchestrator updates the workflow state and determines the next step.
7. If new information changes the situation, the orchestrator asks the LLM to revise the plan.
8. The cycle repeats until the orchestrator determines that the objective has been successfully completed.

This continuous Plan → Reason → Act → Observe → Re-plan loop is what differentiates an AI agent from a traditional conversational chatbot.

Different Products Are Different Configurations

Most leading AI products share the same architectural foundation but specialize by exposing different tools, instructions, and workflows.

Product	Primary User	Specialized Tools	Primary Optimization
ChatGPT	General users	Search, documents, images	Conversational AI and knowledge work
ChatGPT Work	Knowledge workers	Browser, office documents, presentations, coding tools	End-to-end business workflows
Codex	Software developers	Terminal, Git, IDE, testing, repositories	Software engineering
Claude	General users	Search, documents	Conversation and analysis
Claude Cowork	Knowledge workers	Browser, files, spreadsheets, office workflows	Autonomous office productivity
Claude Code	Software developers	Terminal, Git, IDE, shell, debugging	End-to-end software development
Gemini	General users	Google Workspace	Productivity and search
Gemini Code Assist	Software developers	IDE, repositories, Google Cloud	Enterprise software development
GitHub Copilot	Software developers	IDE integration, repositories	Developer productivity