A portfolio website is a personal website that showcases your skills, work, experience, achievements, and professional background. It acts like an online version of your resume, but with much more space to show what you can actually do.
Instead of simply telling people that you are a designer, developer, photographer, writer, or freelancer, a portfolio website allows you to show examples of your work.
For example, a graphic designer can display their logo designs, a photographer can showcase their photographs, and a web developer can present websites and applications they have created.
A portfolio website can also help potential clients, employers, or customers learn more about you and contact you directly.
What Should You Include in a Portfolio Website?
A good portfolio website should be simple, professional, and easy to navigate. You don’t need to include every detail about your career. Instead, focus on information that helps visitors understand who you are, what you do, and what you can offer.
Here are some important sections you can include.
1. About Me
The About Me section introduces you to visitors.
You can briefly explain who you are, what you do, your experience, and what type of work you specialize in.
For example:
“Hi, I’m Rahul, a freelance web designer who creates fast, modern, and mobile-friendly websites for small businesses.”
Keep this section short and easy to read.
2. Your Best Work
This is usually the most important part of a portfolio website.
Showcase some of your best and most relevant projects rather than adding everything you have ever worked on.
For each project, you can include:
Project name
Short description
Your role
Tools or technologies used
Images or screenshots
Link to the live project, if available
Results or achievements, if relevant
For example, a web designer could display screenshots of websites they have designed along with a short explanation of the project.
3. Skills and Services
Tell visitors what you can do.
For example, a web developer might list:
WordPress development
Website design
HTML and CSS
JavaScript
Website maintenance
A photographer might list:
Wedding photography
Product photography
Portrait photography
Event photography
This section helps visitors quickly understand whether your skills match their needs.
4. Resume or Experience
You can include your professional experience, education, certifications, or important achievements.
You don’t necessarily need to upload your complete resume. A short timeline or summary can make the information easier to read.
You can also provide a Download Resume button if you want employers to have a detailed version.
5. Testimonials
If you have worked with clients or companies, consider adding a few genuine testimonials.
A testimonial can show potential clients what it is like to work with you.
For example:
“Rahul created our company website and made the entire process simple and easy. The new website is much faster and easier for our customers to use.”
Always use real testimonials and get permission before publishing someone’s name, photograph, or company information.
6. Contact Information
Make it easy for people to contact you.
Your portfolio website can include:
Email address
Contact form
Phone number, if appropriate
Social media profiles
LinkedIn profile
Location or service area, if relevant
A clear Contact Me or Hire Me button can also make it easier for visitors to take the next step.
Examples of Portfolio Websites for Different Professions
A portfolio website can be useful for many different types of professionals. However, the content and presentation should be adapted to the profession.
1. Graphic Designer
A graphic designer’s portfolio should focus heavily on visual work.
For example, a graphic designer could showcase:
Logo designs
Brand identity projects
Social media designs
Posters
Packaging designs
Illustrations
UI designs
Instead of simply listing “Graphic Design” as a skill, the designer can show actual projects and explain how they approached each one.
Example:
A designer creates a brand identity for a new coffee shop. Their portfolio project could show the logo, color palette, packaging, menu design, and social media graphics.
This gives potential clients a much better idea of the designer’s capabilities.
2. Web Developer
A web developer can use a portfolio website to demonstrate their technical and problem-solving skills.
Their portfolio could include:
Websites they have built
Web applications
WordPress projects
E-commerce websites
Landing pages
Custom software projects
Each project can include information about the technologies used, such as HTML, CSS, JavaScript, PHP, React, WordPress, or other tools.
For example:
Project: Restaurant Website Role: Web Developer Technology: WordPress, HTML, CSS, JavaScript Work: Designed and developed a responsive website with an online menu and contact form.
A developer can also link directly to the live website or a GitHub repository when appropriate.
3. Photographer
For a photographer, the portfolio itself is often the most important part of the website.
A photographer can organize their work into categories such as:
Weddings
Portraits
Fashion
Products
Events
Travel
Food photography
High-quality images should be displayed prominently, while unnecessary text should be kept to a minimum.
The website can also include information about photography packages, availability, client testimonials, and contact details.
Which Professionals Should Have a Portfolio Website?
A portfolio website can be useful for almost anyone who needs to show their work or demonstrate their skills.
It is particularly valuable for:
Graphic designers
Web designers
Web developers
UI/UX designers
Photographers
Videographers
Illustrators
Architects
Interior designers
Artists
Writers and content creators
Copywriters
Freelancers
Digital marketers
SEO professionals
Animators
Software developers
Consultants
For creative professionals, a portfolio can be especially important because your work can demonstrate your abilities more effectively than a list of qualifications alone.
Even students and people starting their careers can create a portfolio website. You don’t need dozens of professional projects. You can include personal projects, college projects, practice work, case studies, or projects created specifically to demonstrate your skills.
Do You Need a Portfolio Website?
Not every professional necessarily needs a portfolio website.
For example, someone whose work is primarily administrative or internal may get more value from a traditional resume and professional profile.
However, if your work involves creating something that can be shown, demonstrated, or presented, a portfolio website can be a valuable way to build your professional presence online.
Think of it this way:
Your resume tells people what you have done. Your portfolio can show them what you can do.
Keep Your Portfolio Website Simple
A portfolio website doesn’t need to be complicated.
In fact, a simple website with your introduction, best projects, skills, experience, testimonials, and contact information can be more effective than a website filled with unnecessary animations and information.
Make sure your portfolio is also mobile-friendly, loads quickly, uses clear navigation, and makes it easy for visitors to view your work.
Most importantly, regularly update your portfolio as you complete new projects and gain new skills.
Want a Portfolio Website?
If you are a freelancer, designer, developer, photographer, creator, or professional looking to build a strong online presence, having your own website can make it easier for people to discover your work and contact you.
Need a professional portfolio website? Contact Lakshya Kaushik at lakshyakaushik.in to discuss your website requirements and create a portfolio website that showcases your work professionally.
A cookie is a small piece of data that a website saves in your web browser when you visit it. Cookies help websites remember information about you and make your browsing experience easier and more personalized.
For example, when you log in to a website and select “Remember me,” a cookie may help the website remember that you are logged in when you come back later.
How Do Website Cookies Work?
When you visit a website, the website can send a small cookie to your browser. Your browser stores it and sends it back to the website when you visit again.
Cookies can store information such as:
Login or session information
Language preferences
Items added to a shopping cart
Website settings
Pages or products you have viewed
A Simple Example
Imagine you visit an online shopping website and add a pair of shoes to your cart. You leave the website and come back later. If the website uses cookies, it may remember the shoes you added to your cart.
Without cookies, many websites would have difficulty remembering your actions between different pages or visits.
Are Cookies Safe?
Cookies themselves are generally not harmful. They are simply small pieces of stored information. However, some cookies can be used to track your activity across websites for analytics or advertising purposes.
This is why many websites show a cookie consent banner asking whether you want to accept certain types of cookies.
Types of Cookies
There are several common types of cookies:
1. Session cookies These are temporary cookies that usually disappear when you close your browser.
2. Persistent cookies These remain in your browser for a specific period and can remember information when you return to a website.
3. First-party cookies These are created by the website you are directly visiting.
4. Third-party cookies These are created by services or companies other than the website you are visiting and may be used for advertising, analytics, or other features.
In Simple Words
Think of a cookie like a small reminder note that a website gives to your browser. It helps the website remember things such as your preferences, login session, or shopping cart.
Cookies are an important part of how modern websites provide convenient and personalized experiences.
Artificial intelligence has moved far beyond the simple idea of asking a chatbot a question and receiving an answer.
Today, AI assistants can write articles, analyze documents, create presentations, generate code, research the internet, work with images, analyze data, build websites, interact with applications, and in some cases even operate a computer on a user’s behalf.
Three of the most important platforms in this space are ChatGPT, Claude, and Gemini.
All three are powerful, but they are not identical.
They have different ecosystems, strengths, workflows, interfaces and approaches to getting work done. Choosing between them is therefore less about asking, “Which AI is the smartest?” and more about asking:
“Which AI is best suited to the type of work I need to accomplish?”
This article explains the differences between ChatGPT, Claude and Gemini, their major capabilities, where each fits, and how their scopes of work compare.
1. What Are ChatGPT, Claude and Gemini?
Before comparing them, it is useful to understand who makes each platform.
It started primarily as a conversational AI assistant, but it has evolved into a much broader platform covering writing, reasoning, coding, research, data analysis, image-related tasks, document creation and agentic workflows.
OpenAI’s current direction is increasingly focused on making ChatGPT capable of completing multi-step work rather than merely answering questions.
OpenAI describes its newer Work capability as an agent that can work across apps and files, break larger goals into smaller tasks, and produce finished outputs such as documents, spreadsheets, presentations and web applications.
ChatGPT also includes Deep Research, which can conduct multi-step research across web sources and produce structured reports with citations.
Claude
Claude is developed by Anthropic.
Claude has developed a particularly strong identity around:
Writing
Coding
Reasoning
Long documents
Large codebases
Artifacts
Knowledge work
Agentic computer interaction
Anthropic’s Claude Opus 4.6, for example, introduced a 1-million-token context window in beta and improvements aimed at longer coding and agentic tasks.
Claude’s Artifacts system is another major part of its ecosystem. It allows Claude to create standalone documents, code, diagrams, websites, dashboards and interactive experiences that can be edited and shared separately from the conversation.
Anthropic has also expanded Claude into document and presentation creation through Claude Docs and Claude Slides.
Its biggest differentiating factor is its connection to Google’s ecosystem.
Gemini is closely connected with Google’s information and productivity environment, including Google Search and, depending on the user’s plan and configuration, services such as Gmail, Drive and Google Docs.
Gemini Deep Research can use Google Search as a source and can also incorporate sources such as Gmail, Drive, uploaded files and NotebookLM notebooks.
Google has also developed Gemini Canvas, where users can create documents, web pages, apps, games, quizzes, infographics and other interactive projects.
So, in simple terms:
ChatGPT = general-purpose AI work platform
Claude = reasoning, writing, coding and artifact-oriented work platform
Gemini = AI deeply connected to Google’s information and productivity ecosystem
That is an oversimplification, but it provides a useful starting point.
2. The Biggest Difference: Ecosystem
One of the most important differences between these platforms is not necessarily the underlying AI model.
It is the ecosystem around the model.
Think of the three platforms this way.
Platform
Major ecosystem orientation
ChatGPT
AI assistant + agents + files + research + creation
Claude
AI assistant + coding + artifacts + knowledge work
Gemini
Google Search + Google ecosystem + multimodal AI
The boundaries are becoming increasingly blurred.
For example, Claude now has documents and presentations, Gemini can create applications, and ChatGPT can work with documents and presentations.
Therefore, the question is increasingly:
How does each platform organize these capabilities around the user’s workflow?
3. ChatGPT: The General-Purpose AI Workbench
ChatGPT can be thought of as an AI workbench.
It is designed to handle many different categories of work inside one environment.
A user might start with a simple question and then move into:
Research
Analysis
Writing
Coding
Data analysis
File processing
Presentation creation
Website creation
Automation
without necessarily changing platforms.
OpenAI’s current Work direction reflects this shift from “chatbot” toward “AI worker.” OpenAI says Work can work across apps and files, operate on complex projects for extended periods, and create finished materials.
What can ChatGPT be used for?
Writing
ChatGPT can help create:
Blog posts
Articles
Emails
Business proposals
Social media posts
Product descriptions
Scripts
Documentation
Reports
Marketing copy
SEO content
Website copy
It can also rewrite existing material according to a particular tone.
For example:
“Rewrite this landing page to sound more premium and professional.”
or:
“Turn these rough notes into a 2,000-word article.”
4. ChatGPT for Research
Research is one of the areas where modern AI assistants have changed substantially.
Instead of asking an AI:
“What is SEO?”
you can ask:
“Research the current SEO landscape for small businesses in India, identify changes in search behavior, compare major strategies and provide sources.”
ChatGPT’s Deep Research capability is designed for this type of task.
OpenAI describes it as a multi-step research capability that searches, analyzes and synthesizes information, with citations or source links.
This is different from ordinary conversational answering.
The AI can break the question into smaller research problems, gather information and construct a report.
That makes this type of AI useful for:
Market research
Competitor research
Product research
Industry research
Academic research
Business analysis
Technology research
Content research
5. ChatGPT for Coding
ChatGPT can be used for a wide range of programming tasks.
For example:
Beginner coding
You can ask:
“Teach me HTML and CSS by building a portfolio website.”
Debugging
You can provide code and ask:
“Why isn’t this JavaScript function working?”
Development
You can ask:
“Build a responsive dashboard using HTML, CSS and JavaScript.”
Architecture
You can ask:
“Design the database architecture for a SaaS application.”
Existing projects
You can provide project files and ask the AI to:
Understand the existing code
Find bugs
Add features
Refactor code
Improve performance
Explain unfamiliar code
Create documentation
ChatGPT’s broader agentic direction also means coding can increasingly become part of a larger workflow rather than an isolated conversation.
6. ChatGPT for Data Analysis
ChatGPT can also be used as an analytical assistant.
For example, a business owner can provide:
CSV files
Excel spreadsheets
Sales data
Marketing reports
Financial data
Survey results
and ask questions such as:
“Which products generated the most revenue?”
or:
“Identify unusual changes in sales.”
or:
“Create a monthly performance report.”
The important shift is that the user doesn’t necessarily need to know how to write Python or SQL before asking the question.
The AI can help bridge the gap between:
raw data → analysis → explanation → report
7. ChatGPT for Business Work
ChatGPT can be particularly useful as a general business assistant.
Potential tasks include:
Creating proposals
Writing emails
Preparing meeting documents
Creating marketing strategies
Researching competitors
Analyzing spreadsheets
Writing SOPs
Creating presentations
Developing website content
Creating reports
Brainstorming products
Developing business processes
For businesses, the important concept is not “AI writes text.”
It is:
AI can participate in the workflow surrounding the text.
8. Claude: The Knowledge-Work and Coding Specialist
Claude has developed a strong reputation around long-form reasoning, writing, coding and handling complex projects.
Anthropic’s current Claude ecosystem goes significantly beyond a traditional chatbot.
Claude’s Artifacts can produce standalone:
Documents
Websites
Dashboards
Diagrams
Interactive components
Tools
Presentations
Designs
and allow users to continue editing and sharing them.
This makes Claude interesting for people who want the AI to create something that exists as an actual working artifact rather than just text inside a conversation.
9. Claude for Writing
Claude is particularly useful for long-form writing workflows.
For example:
“Here are 30 pages of research. Turn this into a structured report.”
or:
“Rewrite this 10,000-word document while preserving the important information.”
or:
“Analyze this company’s documentation and create an internal knowledge guide.”
Claude’s long-context capabilities are particularly relevant when working with large amounts of information.
Anthropic says Claude Opus 4.6 introduced a 1-million-token context window in beta, alongside improvements for large codebases and extended agentic tasks.
Context size isn’t the only factor determining quality, but it becomes important when a task involves a very large amount of material.
10. Claude for Coding
Coding is another major Claude use case.
Claude can work with:
HTML
CSS
JavaScript
Python
PHP
React
Node.js
SQL
APIs
Larger software projects
It can help with:
Generating code
Debugging
Refactoring
Code review
Architecture
Documentation
Understanding existing codebases
Anthropic has also developed Claude Code, which is designed around software development workflows.
Anthropic says Opus 4.6 was specifically improved for longer coding tasks, code review, debugging and working more reliably across larger codebases.
Claude can also produce artifacts directly from coding sessions.
For example, a coding session can produce a live dashboard or interactive web page that can be viewed separately from the conversation.
11. Claude Artifacts
Artifacts are one of the easiest ways to understand Claude’s product philosophy.
Suppose you say:
“Create a dashboard showing website traffic.”
Instead of merely returning HTML code in the chat, Claude can create a standalone artifact.
That artifact can be:
Viewed
Modified
Iterated
Shared
Claude’s documentation describes artifacts as substantial standalone content such as documents, code, websites, SVG graphics, diagrams and interactive React components.
This makes Claude particularly interesting for workflows where the output itself matters.
Instead of:
AI → answer
the workflow becomes:
AI → working object
12. Claude and Computer Use
Claude has also moved toward agentic computer interaction.
Anthropic introduced computer-use capabilities in Claude Cowork and Claude Code, allowing Claude to open files, use development tools, navigate interfaces and interact with a computer through point-and-click actions.
This represents a major change in how AI assistants can operate.
Traditional AI:
User asks → AI responds.
Agentic AI:
User gives objective → AI performs multiple steps.
For example, an AI agent might eventually be asked to:
“Organize these files and prepare a report.”
Instead of merely explaining how to do it, the agent can potentially perform parts of the workflow itself, subject to the available permissions and tools.
13. Gemini: Google’s AI Ecosystem
Gemini is different because Google has something the other companies do not have at the same scale:
Google’s enormous ecosystem of information and productivity products.
Gemini can be connected to Google’s services and information sources depending on the user’s configuration and plan.
This makes Gemini particularly relevant for people already working heavily inside Google’s ecosystem.
For example:
Gmail
Google Drive
Google Docs
Google Search
NotebookLM
Google Workspace
Gemini Deep Research can use Google Search and can incorporate sources such as Gmail, Drive, uploaded files and NotebookLM notebooks.
14. Gemini for Research
Research is one of Gemini’s major capabilities.
Gemini Deep Research can break a question into multiple research areas, investigate websites and create multi-page reports.
Google describes it as a research assistant capable of conducting in-depth, real-time research and producing comprehensive reports.
This makes Gemini useful for questions such as:
“Research the Indian fitness market.”
or:
“Analyze the competitors in this industry.”
or:
“Research this topic and prepare a report that I can continue editing.”
The ability to connect research with Google’s ecosystem can be useful when the user’s information is already stored there.
15. Gemini Canvas
Gemini Canvas is another major part of the Gemini experience.
Google describes Canvas as a space where users can write, code and create.
It can be used for:
Documents
Web pages
Apps
Games
Quizzes
Infographics
Interactive experiences
Google also describes workflows where a Deep Research report can be transformed into a web page, infographic, quiz or other interactive creation.
This is an important development because Gemini is no longer simply:
Google Search + chatbot
It is increasingly:
Research + creation + productivity + coding
16. ChatGPT vs Claude vs Gemini: Writing
All three can write.
The difference is more about workflow and ecosystem than whether one can “write” and another cannot.
ChatGPT
Useful for:
Marketing content
Business communication
SEO content
Structured writing
Brainstorming
Editing
Reports
General-purpose writing
Claude
Useful for:
Long documents
Detailed rewriting
Large-context editing
Complex documentation
Long-form knowledge work
Gemini
Useful for:
Writing within Google’s ecosystem
Research-backed content
Google Docs workflows
Content derived from Google-based information sources
There is significant overlap.
The best choice can depend heavily on the specific document and workflow.
17. ChatGPT vs Claude vs Gemini: Coding
All three platforms can help programmers.
Coding task
ChatGPT
Claude
Gemini
HTML/CSS
Strong
Strong
Strong
JavaScript
Strong
Strong
Strong
Python
Strong
Strong
Strong
React
Strong
Strong
Strong
Debugging
Strong
Strong
Strong
Code explanation
Strong
Strong
Strong
Large codebase work
Strong
Strong
Strong
Interactive prototypes
Strong
Strong
Strong
Agentic coding
Strong
Strong
Strong
Google ecosystem development
Strong
Strong
Particularly relevant
The important point is that there is no useful permanent ranking here.
Models change.
Their coding tools change.
Their context limits change.
Their agent capabilities change.
A model that performs differently today may perform differently after its next major update.
18. ChatGPT vs Claude vs Gemini: Research
Research can be divided into several types.
General web research
All three can participate.
Deep research
All three increasingly offer dedicated research workflows.
ChatGPT Deep Research is designed around multi-step investigation and synthesis.
Gemini Deep Research uses Google Search by default and can incorporate additional sources such as Gmail, Drive and NotebookLM.
Research involving your Google ecosystem
Gemini has a natural advantage in workflow integration because of its connection to Google services.
Research involving files and broader work
ChatGPT and Claude can also be highly useful, particularly when the research must turn into documents, code, analysis or other outputs.
19. ChatGPT vs Claude vs Gemini: Image and Multimodal Work
Modern AI assistants are multimodal.
That means they can work with more than text.
Depending on the available model and product configuration, this can include:
Images
Screenshots
Documents
PDFs
Tables
Code
Audio
Video
The important concept is that multimodal AI doesn’t simply “look at an image.”
It can combine different forms of information.
For example:
Upload a screenshot + provide a website URL + provide your code + ask the AI to identify the problem.
That becomes much more powerful than traditional text-only assistance.
20. AI Agents: The Next Major Difference
One of the biggest developments in AI is the transition from chatbots to agents.
A chatbot primarily responds.
An agent can perform a sequence of actions.
Consider this task:
“Research 20 competitors, collect their pricing, organize the information into a spreadsheet, identify patterns and create a presentation.”
A traditional chatbot might answer with instructions.
An agentic AI system can potentially:
Search for competitors
Collect information
Analyze the data
Create a spreadsheet
Generate charts
Prepare a presentation
Produce a final report
This is where ChatGPT, Claude and Gemini are increasingly converging.
OpenAI’s Work capability is explicitly designed around multi-step work across apps and files.
Claude has been expanding its agentic computer and coding capabilities.
Gemini is combining research with creation through Deep Research and Canvas.
21. AI for Website Development
For web developers, all three can be useful.
Imagine asking:
“Build a responsive website for a real estate company.”
The AI can potentially help create:
HTML
CSS
JavaScript
React
Forms
UI components
Animations
Responsive layouts
SEO structure
Schema markup
You can then iterate:
“Make the cards more premium.”
“Add a filter.”
“Make it mobile responsive.”
“Add dark mode.”
“Fix the navigation.”
This conversational development workflow is becoming one of the most important applications of generative AI.
22. AI for Designers
AI is also becoming useful for designers.
Potential applications include:
UI concepts
Layout ideas
Design systems
Wireframes
Website structures
SVGs
Visual assets
Presentations
Infographics
Prototypes
Claude’s Artifacts and Design capabilities are particularly focused on creating visual and interactive outputs.
Gemini Canvas similarly allows users to transform ideas into visual and interactive projects.
ChatGPT can also be used as a broader design and creation assistant.
23. AI for SEO and Digital Marketing
For digital marketers, all three can be useful.
An AI assistant can help with:
Keyword research
Generate keyword ideas based on:
Location
Search intent
Industry
Buyer stage
Product category
Content planning
Create:
Topic clusters
Pillar pages
Supporting articles
FAQs
Internal linking plans
Content production
Create:
Blog articles
Meta titles
Meta descriptions
Landing pages
Product descriptions
Social media content
Competitor research
Analyze:
Competitor websites
Content structures
Topics
Offers
Positioning
Search opportunities
The major limitation is that AI-generated SEO content should not simply be published without human review.
Search engines evaluate the usefulness and quality of content, and factual accuracy still matters.
AI should therefore be treated as a research and production accelerator, not an automatic substitute for editorial judgment.
24. AI for Business Owners
A business owner can use these platforms as a virtual team of specialists.
For example:
Marketing assistant
“Create a 30-day social media plan.”
SEO assistant
“Find content opportunities for my website.”
Sales assistant
“Write a proposal for this client.”
Research assistant
“Analyze these competitors.”
Financial assistant
“Analyze this spreadsheet.”
Technical assistant
“Explain this website error.”
Product assistant
“Turn this idea into a product specification.”
Operations assistant
“Create an SOP for onboarding a new client.”
The interesting part is that the same AI can move between these roles.
25. AI for Students
Students can use these systems for:
Explaining difficult concepts
Creating study notes
Generating quizzes
Summarizing material
Brainstorming projects
Practicing languages
Explaining programming
Creating revision plans
Gemini Canvas, for example, can turn study material into interactive quizzes and other learning experiences.
The best educational use is generally not:
“Give me the answer.”
It is:
“Explain why this answer is correct.”
That changes AI from an answer generator into a learning assistant.
26. AI for Developers
Developers can use AI throughout the entire software-development lifecycle.
Planning
“Turn this idea into technical requirements.”
Architecture
“Design the database.”
Development
“Build the API.”
Debugging
“Find the bug.”
Testing
“Create test cases.”
Documentation
“Document this API.”
Refactoring
“Improve this code without changing its behavior.”
Deployment
“Explain how to deploy this application.”
The emergence of agentic coding tools makes the workflow increasingly collaborative.
Instead of writing every line manually, the developer becomes more like:
architect + reviewer + decision maker + AI operator
27. Context Window: Why It Matters
One technical term you will hear frequently is:
Context window.
A context window is essentially the amount of information an AI model can work with within a particular interaction.
Imagine giving an AI:
A 500-word document
versus:
A 500-page collection of documents.
The second task requires substantially more context.
Large context windows can therefore be useful for:
Large codebases
Books
Legal documents
Research papers
Business documentation
Large datasets
Long conversations
Claude has emphasized large-context workflows, with Anthropic stating that Opus 4.6 has a 1-million-token context window in beta.
But context window size should not be treated as a simple quality score.
A larger window does not automatically mean better reasoning.
This combination can be more important than the model alone.
For example:
AI without web access:
“I can explain this.”
AI with web research:
“I can investigate this.”
AI with files:
“I can analyze your documents.”
AI with code execution:
“I can analyze the data.”
AI with computer access:
“I can perform actions.”
AI with all of these:
“I can potentially take the project from research to execution.”
That is the direction in which the industry is moving.
29. Why You Should Not Think of One AI as “The Best”
AI models are constantly changing.
A comparison published six months ago can become outdated.
A model may receive:
A new reasoning system
Better coding
Larger context
New tools
Better browsing
New integrations
Better image capabilities
New agent features
This means that instead of asking:
“Which AI is the best?”
a better question is:
“Which AI fits this particular task and workflow?”
30. A Practical Comparison
Here is a more useful way to think about the three.
Area
ChatGPT
Claude
Gemini
General assistance
Broad
Broad
Broad
Writing
Strong
Strong
Strong
Long documents
Strong
Strong
Strong
Coding
Strong
Strong
Strong
Research
Strong
Strong
Strong
Web research
Strong
Strong
Strong
Data analysis
Strong
Strong
Strong
Agents
Strong
Strong
Strong
Artifacts/prototypes
Strong
Strong
Strong
Google integration
Good
Limited compared with Gemini
Very strong
Large-context workflows
Strong
Strong
Strong
Google Search ecosystem
Indirect
Indirect
Native ecosystem advantage
Computer interaction
Available in relevant workflows
Available in relevant workflows
Evolving
Business workflows
Strong
Strong
Strong
Documents
Strong
Strong
Strong
Presentations
Strong
Strong
Strong
Web/app creation
Strong
Strong
Strong
This table should not be interpreted as a permanent ranking. The platforms are changing rapidly and capabilities vary by model, plan, region and enabled tools.
31. When ChatGPT Makes Sense
ChatGPT can make sense when you want a broad AI workspace capable of moving between different types of work.
It is particularly useful when your work doesn’t fit neatly into one category.
A business owner might use it for marketing in the morning, coding in the afternoon and research in the evening.
That breadth is an important part of the ChatGPT proposition.
32. When Claude Makes Sense
Claude can be particularly useful when the work involves:
Large documents
Complex writing
Programming
Large codebases
Technical reasoning
Documentation
Interactive artifacts
Agentic computer work
Its Artifacts system also makes it interesting when the output needs to become a reusable object rather than remain a chat response.
33. When Gemini Makes Sense
Gemini becomes especially relevant when your workflow revolves around Google’s ecosystem.
For example, imagine your information is already stored across:
Gmail
Google Drive
Google Docs
Google Search
NotebookLM
Gemini’s ability to work with those sources can make the workflow more integrated. Google’s documentation specifically describes Deep Research using Search and allowing additional sources such as Gmail, Drive, uploaded files and NotebookLM notebooks.
Gemini Canvas adds another layer by connecting research, writing, coding and interactive creation.
34. Using More Than One AI
There is no requirement to use only one AI platform.
In fact, a multi-AI workflow can be very powerful.
For example:
Step 1 — Research
Use a research-oriented workflow to collect information.
Step 2 — Analysis
Use another model to challenge assumptions and identify gaps.
Step 3 — Writing
Use an AI that matches your preferred writing style.
Step 4 — Coding
Use an AI coding workflow to implement the technical solution.
Step 5 — Review
Give the final output to another model for criticism and error detection.
This creates something similar to a virtual team.
35. Example: Building a Website Using AI
Imagine you want to create a website for a school.
You could use AI for the entire process.
Stage 1: Strategy
Ask:
“Create the website structure for a modern international school.”
Stage 2: Content
Generate:
Homepage copy
About page
Admissions page
Facilities
Academics
Contact page
Stage 3: Design
Generate:
Color palette
Typography
Component structure
Hero section
Cards
Navigation
Stage 4: Development
Generate:
HTML
CSS
JavaScript
React components
Stage 5: Testing
Upload screenshots and ask:
“Identify UI problems.”
Stage 6: SEO
Ask:
“Create metadata and structured content for each page.”
Stage 7: Launch
Use the AI to create:
Deployment instructions
Analytics setup
SEO checklist
Maintenance checklist
The AI is no longer simply writing.
It is participating in the entire project.
36. Example: Building a Business With AI
Consider someone starting an online business.
AI can assist with:
Idea
→ market research
→ competitor analysis
→ customer persona
→ product development
→ branding
→ website
→ SEO
→ advertising
→ social media
→ analytics
→ customer support
→ automation
The human remains responsible for business decisions.
AI becomes the execution and research layer.
37. The Biggest Limitation of All Three
Despite their capabilities, none of these systems should be treated as infallible.
AI can:
Make factual mistakes
Misinterpret instructions
Produce incorrect code
Invent information
Misread documents
Make calculation errors
Misunderstand business requirements
Produce outdated information
This is why the most powerful workflow is often:
AI generation → human verification → AI refinement → final human decision
rather than:
AI generation → publish immediately
38. AI Does Not Eliminate Expertise
A common misunderstanding is:
“If AI can do something, I don’t need to know how it works.”
The opposite can often be true.
The more capable AI becomes, the more valuable it can be to have enough expertise to evaluate its output.
A developer who understands programming can recognize bad code.
An SEO professional can identify weak SEO recommendations.
A designer can identify poor UX.
A business owner can recognize an unrealistic strategy.
AI increases the speed of execution.
Human expertise provides direction and judgment.
39. The Future of AI Assistants
The most important transition is from:
Question → Answer
to:
Goal → Plan → Execute → Review → Deliver
This is the foundation of agentic AI.
Imagine saying:
“I need a competitor analysis by tomorrow.”
Instead of manually:
Searching Google
Opening websites
Copying information
Creating spreadsheets
Analyzing the data
Creating charts
Writing a report
you increasingly delegate the workflow to an AI system.
ChatGPT, Claude and Gemini are all moving in this direction, although their implementations and ecosystems differ.
40. Final Perspective
ChatGPT, Claude and Gemini should not simply be viewed as three chatbots competing to answer questions.
They represent three major AI ecosystems that are rapidly evolving into broader work platforms.
ChatGPT is developing toward a broad AI work environment combining conversation, research, files, coding, analysis, creation and agents.
Claude has developed strongly around reasoning, coding, long-context knowledge work, artifacts and increasingly autonomous computer-based workflows.
Gemini benefits from Google’s enormous ecosystem and is increasingly combining Search, research, productivity tools, multimodal capabilities and interactive creation.
The important lesson is that the AI landscape is moving away from:
“Which chatbot gives the best answer?”
and toward:
“Which AI can help me complete the entire job?”
That distinction is extremely important.
The next generation of AI users will not necessarily use AI merely to generate text. They will use AI to research, analyze, build, automate, review and execute.
The person who understands how to combine these capabilities into a workflow may gain substantially more value than someone who simply knows how to write prompts.
And ultimately, the most effective approach may not be choosing one AI forever.
It may be learning when to use ChatGPT, when to use Claude, when to use Gemini, and when to combine them.
Quick Mental Model
If you want a simple way to remember the differences:
ChatGPT → Think of it as a broad AI workbench.
Claude → Think of it as a powerful reasoning, coding and artifact workspace.
Gemini → Think of it as an AI layer across Google’s information and productivity ecosystem.
But these boundaries are increasingly overlapping, so the practical differences should always be checked against the current capabilities of the specific models and plans you have access to.
