Artificial intelligence has revolutionized the way we interact with technology, and ChatGPT stands at the forefroArtificial Intelligence (AI) is reshaping how we interact with technology, and OpenAI’s ChatGPT is at the forefront of this transformation. As AI grows more advanced, ChatGPT has introduced three specialized agents—Codex, Operator, and Deep Research—each with distinct capabilities designed to enhance productivity, streamline tasks, and deepen analysis.
In this comprehensive article, we explore the unique roles and capabilities of Codex, Operator, and Deep Research, how they differ from the base ChatGPT model, and how you can utilize them effectively in your workflows.
What Are ChatGPT AI Agents?
AI agents are specialized tools within the ChatGPT ecosystem designed to carry out specific types of tasks more effectively than the base model. While the main ChatGPT model is a general-purpose assistant, these agents are trained or configured to excel in particular areas:
- Codex is tailored for code generation and software development.
- Operator manages API calls and structured data workflows.
- Deep Research is designed for conducting in-depth investigations, summarization, and source-backed answers.
Let’s take a detailed look at each of these powerful agents and understand what makes them unique.
1. Codex: The Code Generation Expert
What Is Codex?
Codex is an AI agent trained on a vast corpus of code and natural language documentation. It powers features in tools like GitHub Copilot and is optimized for writing, understanding, and debugging code.
Key Capabilities of Codex
a. Code Generation in Multiple Languages
Codex can write code in Python, JavaScript, PHP, Java, C++, HTML/CSS, and many other languages. It understands user prompts and can generate functionally accurate code, including:
- Web development (HTML/CSS/JS)
- Backend development (Node.js, Python, PHP)
- API integration
- Data structures and algorithms
- Database queries (SQL, MongoDB)
b. Bug Detection and Debugging
Codex helps developers identify and fix bugs. You can paste your broken code, and it will analyze and suggest corrections, often with explanations.
c. Code Explanation
It’s an excellent tool for learning, as it can break down complex code into understandable English. This is helpful for beginners or anyone reviewing unfamiliar code.
d. Converting Code Between Languages
Codex can convert a snippet of code from one programming language to another, helping developers migrate codebases or understand syntax differences.
e. Writing Tests
Whether you need unit tests or integration tests, Codex can auto-generate them, speeding up development cycles.
Example Use Case
A software developer working on a Laravel project can ask Codex to create a new controller or API route, saving hours of manual effort and reducing syntax errors.
2. Operator: The Task Manager and Workflow Automator
What Is Operator?
Operator is ChatGPT’s built-in agent for interacting with APIs, tools, and structured data. Think of it as a virtual assistant that automates business logic, data retrieval, and real-time interactions using external services.
Key Capabilities of Operator
a. Tool and Plugin Integration
Operator can call functions, APIs, and third-party tools. For instance, if a business needs to fetch inventory data or initiate a task via a scheduling API, Operator handles it.
b. Automated Data Workflows
You can use Operator to parse and manipulate spreadsheets, generate reports, manage calendars, or extract details from structured documents.
c. Natural Language to API Calls
You don’t need to write complex syntax. Just say “Get me today’s weather in Valsad” or “Add a task to my to-do list,” and Operator translates that into an API call in the background.
d. CRM and ERP Support
Operator can connect to customer databases, update records, pull sales data, or interact with CMS systems.
e. Real-Time Responses
Thanks to live API connectivity, Operator provides real-time answers, unlike Codex or Deep Research which rely on static or pretrained data.
Example Use Case
An e-commerce manager can use Operator to automatically generate a report on daily sales by region, integrate it with Google Sheets, and email it to the team—all triggered by a single natural-language prompt.
3. Deep Research: The Analytical Brain
What Is Deep Research?
Deep Research is designed to go beyond surface-level queries. It is optimized for:
- Long-form content generation
- Source-backed research
- Summarizing complex topics
- Extracting insights from large documents
This makes it ideal for journalists, researchers, analysts, students, and educators.
Key Capabilities of Deep Research
a. Multi-Source Analysis
Deep Research can simulate reading across multiple sources and synthesizing insights. While it may not access the live web unless connected to browsing tools, it mimics deep analytical reading and comparison.
b. Contextual Summarization
Give it a long PDF, research paper, or even a policy document, and it will return a concise, structured summary with key points, pros and cons, and implications.
c. Citations and Source Attribution
In research modes that include browsing capabilities, Deep Research can provide links and citations, which is crucial for academic or factual writing.
d. In-Depth Content Creation
Deep Research can generate whitepapers, detailed blog posts, reports, and essays with a logical structure and insightful analysis.
e. Q&A from Large Documents
You can paste entire sections of documents or long articles, and Deep Research can answer questions like, “What’s the main argument in section 4?” or “What data supports this conclusion?”
Example Use Case
A content strategist working on a 2000-word blog post about climate change can use Deep Research to summarize IPCC reports, generate sections with bullet points, and even suggest sources for further reading.
Codex vs Operator vs Deep Research: Key Differences
| Feature | Codex | Operator | Deep Research |
|---|---|---|---|
| Purpose | Coding and development | Task automation & API handling | Research, analysis, summarization |
| Internet Access | No | Yes (via APIs) | Limited (unless browsing enabled) |
| Programming Languages | All major ones | Minimal | Not applicable |
| Output Type | Code, logic, syntax | Actions, data, integrations | Text, summaries, insights |
| Best For | Developers | Business users, analysts | Writers, researchers, students |
How to Access These Agents in ChatGPT
To access Codex, Operator, and Deep Research in ChatGPT:
- Subscribe to ChatGPT Plus: These agents are available in the Pro plan which uses GPT-4-turbo.
- Navigate to the Agent Selector: When starting a new chat, choose an agent from the dropdown (if available).
- Switch Context as Needed: Depending on your task—coding, automation, or research—you can switch between agents mid-conversation or start new threads.
Practical Use Cases for Each Agent
For Developers
- Use Codex to scaffold projects, generate APIs, and debug code.
- Use Operator to test API integrations.
- Use Deep Research to find best practices or explain complex concepts.
For Businesses
- Use Operator for inventory automation, CRM updates, and reporting.
- Use Deep Research for market analysis or document summarization.
For Content Creators
- Use Deep Research to generate outlines, compare sources, and write long-form articles.
- Use Codex to embed custom scripts or tracking code on websites.
For Students & Educators
- Use Codex for computer science tasks.
- Use Deep Research for writing essays or summarizing books.
- Use Operator to interact with academic databases or calendars.
Future of AI Agents in ChatGPT
OpenAI’s move to introduce modular agents points toward a broader vision—creating an AI workspace where tasks are handled by specialists rather than a generalist assistant. Over time, these agents will likely:
- Learn to collaborate with each other
- Personalize themselves based on your usage
- Expand into more domains (e.g., finance, design, healthcare)
The agent-based architecture represents a significant leap forward, not just in AI capability but in usability. Users no longer need to know how to perform a task—they just need to ask the right agent.
Conclusion
ChatGPT’s three core agents—Codex, Operator, and Deep Research—bring domain-specific intelligence to your fingertips. Whether you’re a coder, a business professional, or a researcher, these agents can transform the way you work.
By understanding their unique strengths and capabilities, you can make the most of ChatGPT’s full potential. As OpenAI continues to refine and expand these agents, the line between human expertise and AI assistance will continue to blur, unlocking new levels of efficiency and creativity.