Introduction: Why You Should Pay Attention to Claude

This is the third article in the AI Prompt Engineering series. This time, I want to take an in-depth look at Claude, developed by Anthropic. Honestly, I initially thought, "Why bother with another AI when ChatGPT exists?" But after using Claude deeply, I had a completely different experience, and now I alternate between the two AIs depending on the type of task.

Claude has evolved rapidly since its initial release in 2023. The Claude 3 series and Claude 3.5 Sonnet released in 2024 made a big impact in the industry by outperforming competitors in many benchmarks. And Claude 3.5 Opus released in 2025 raised the bar once again. However, it's difficult to explain Claude's value simply through benchmark scores. Claude's unique philosophy and features create a big difference in actual usage experience.

In this article, we'll take a practical look at everything from Claude's core philosophy to each model's characteristics, optimized prompt writing methods, and how to utilize powerful features like Artifacts and Projects.

1. Claude's Core Philosophy: Constitutional AI and Safety

1.1 What is Constitutional AI?

Anthropic was founded as a company with "AI safety" research as its core mission. As a company created by Google AI researchers with the clear goal of "safe AI development," this philosophy is deeply embedded in Claude. The core of this is Constitutional AI.

Constitutional AI is an approach that gives AI models a kind of "principles" or "constitution." Rather than simply prohibiting certain topics, it's a methodology that trains AI to self-review and modify its own responses. For example, Claude generates every response under the principle of "be helpful, but don't cause harm."

You can feel this difference in actual use. Rather than simply refusing with "I can't do that" for dangerous or ethically problematic requests, Claude tries to explain why the request could be problematic and suggest alternatives. Of course, this characteristic can sometimes give the impression of being "too cautious," but in work environments where professional and reliable results are needed, it becomes a significant advantage.

1.2 Practical Benefits of Safety-Focused Design

Claude's safety-centered design provides several practical benefits:

  • Reduced Hallucinations: Claude tends to honestly say "I don't know for certain" or "additional verification is needed" for uncertain information. This is much more useful than plausibly fabricating incorrect information.
  • Consistent Response Quality: With safety principles internalized, it presents balanced perspectives even on complex topics. It doesn't promote biased information or extreme opinions.
  • Enterprise Environment Suitability: When using AI in sensitive fields like law, medicine, and finance, Claude's conservative and cautious approach reduces risks.

2. Claude 3.5 Model Lineup Comparison

2.1 Claude 3.5 Sonnet: Master of Balance

This is currently the most widely used model. Claude 3.5 Sonnet is a model that has found the optimal balance between performance and speed, delivering excellent performance in most everyday tasks.

Based on my personal experience, Sonnet is particularly impressive for coding tasks. It explains complex algorithms while simultaneously writing clean code and explaining why the code was written that way. For writing tasks, it quickly generates results with natural prose and logical structure.

Speed is also satisfactory. Responses to general questions are almost instant, and even long document writing proceeds without noticeable discomfort. Free users can also use a significant amount of messages daily, making accessibility good.

2.2 Claude 3.5 Opus: Premium Maximum Performance

Opus is the most powerful model in the Claude lineup. It shines in complex reasoning, in-depth analysis, and creative work. However, processing speed is slower than Sonnet, and API costs are higher.

When should you choose Opus? I mainly use Opus in situations like:

  • Complex business analysis or strategy development
  • Academic paper-level in-depth research
  • Complex decision-making that requires synthesizing multiple perspectives
  • When unique and in-depth results are needed in creative writing

When reading Opus's responses, there are times when I think "Did AI really write this?" because of the depth and nuance. Of course, not every task needs Opus, but it definitely makes a difference in important projects.

2.3 Claude 3.5 Haiku: King of Speed

Haiku is a model optimized for speed and efficiency. It boasts the fastest response speed and the lowest API cost. It's suitable for simple tasks or when large amounts of data need to be processed quickly.

Situations where Haiku shines:

  • Quick answers to simple questions
  • Repetitive tasks like text classification or summarization
  • Chatbots or customer service automation
  • Applications where real-time response is important

2.4 Model Selection Guide

Task Type Recommended Model Reason
Everyday questions/conversations Sonnet Fast speed and sufficient quality
Code writing/review Sonnet Balance of coding ability and speed
Complex analysis/research Opus Deep reasoning capability
Creative writing Opus Excellent creativity and expressiveness
Large-scale data processing Haiku Fast speed and cost efficiency
Real-time chatbots Haiku Minimum latency

3. Writing Prompts Optimized for Claude

3.1 Understanding Claude's Characteristics

To write effective prompts, you first need to understand Claude's characteristics. Claude has several distinct features:

  • Strong with long instructions: Claude follows complex and detailed instructions well. When other AIs get confused with long prompts, Claude actually produces more accurate results.
  • Context retention ability: Thanks to its massive 200K token context window, it can remember and work with long conversations or entire large documents.
  • Prefers clear structure: It responds particularly well to structured prompts using XML tags or markdown.
  • Honest feedback: It says it doesn't know what it doesn't know, and asks for clarification on unclear requests.

3.2 Structuring with XML Tags

Claude responds very well to prompt structuring using XML tags. This method is also recommended in Anthropic's official documentation. For example:

<context>
You are a senior software engineer with 10 years of experience.
You have expertise in Python and JavaScript.
</context>

<task>
Review the code below and suggest improvements.
</task>

<code>
def calculate_total(items):
    total = 0
    for item in items:
        total = total + item['price']
    return total
</code>

<output_format>
1. Issues with current code
2. Improved code
3. Explanation of improvements
</output_format>

Structuring like this helps Claude clearly understand the role of each section and respond in the requested format.

3.3 Effective Role Assignment Methods

When assigning a role to Claude, it's more effective to provide specific background and perspective rather than simply saying "you are an expert":

You are a marketing director who has worked at both startups and large corporations for 15 years.
You value data-driven decision making, but also understand the value of intuition and creativity.
Recently, you've been deeply researching the possibilities and limitations of AI marketing tools.

From this perspective, please review our company's new product launch marketing strategy.

3.4 Guiding Step-by-Step Thinking

For complex problems, asking Claude to think step-by-step can yield better results:

When analyzing this business problem, please follow these steps:

1. First, identify and define the core of the problem
2. Identify all relevant stakeholders
3. Look at the problem from each stakeholder's perspective
4. Brainstorm possible solutions
5. Analyze the pros and cons of each solution
6. Present your final recommendation and reasoning

Show your thinking process at each step.

3.5 Using Feedback Loops

One of Claude's strengths is that it accepts feedback well. Even if the first result isn't perfect, you can quickly improve it through specific feedback:

"Good start, but please modify these parts:
- The introduction is too stiff. Change it to a friendlier tone
- The example in the third paragraph isn't relevant to our industry. Replace it with a B2B software-related example
- The conclusion is too short. Add 3 actionable next steps"

4. Fully Utilizing the Artifacts Feature

4.1 What are Artifacts?

Artifacts is one of Claude's most innovative features. It's a feature that displays code, documents, diagrams, etc. generated during conversation in a separate panel, allows real-time preview, and lets you download or share directly.

When I first encountered Artifacts, I honestly thought "Wow, this actually works?" For example, if you request "make a simple todo list web app," Claude not only writes the HTML/CSS/JavaScript code but also shows you the running result immediately. You can verify a working app right in the conversation.

4.2 Artifacts Use Cases

Interactive Prototype Creation

Artifacts shines when you want to quickly visualize ideas. Request "make a dashboard UI prototype" and you get a prototype you can actually click and interact with. Very useful when explaining ideas to designers or developers.

Data Visualization

Enter data and say "make a chart from this data," and graphs are generated in real-time. Interactive charts using SVG or Chart.js are also possible.

Document Writing

When writing documents in markdown format, you can immediately see the rendered result. Convenient for writing reports, guides, and manuals.

Code Execution and Debugging

For JavaScript code, you can see actually running results, which is useful for learning algorithms or finding bugs.

4.3 Artifacts Usage Tips

  • Clear requests: Specifying "make it as an Artifact" or "show as executable code" ensures you get results in Artifact form.
  • Iterative improvement: Artifacts can be continuously modified during conversation. Say "change the button color to blue" and it's reflected immediately.
  • Version control: Claude remembers previous versions of Artifacts, so you can go back to earlier versions if needed.
  • Export utilization: Completed Artifacts can be downloaded or shared via link. Very useful for collaboration.

5. Maintaining Context with Projects Feature

5.1 Core Value of Projects

Projects is a feature that allows you to maintain consistent context across multiple conversations. Upload documents, code, guidelines, etc. related to a specific project, and you can reference that information in all conversations within that project.

Let me give an example of how useful this feature is in actual work. I've uploaded technical documents, coding conventions, and API specifications from my ongoing development project to a Project. Then, even when I start a new conversation, Claude already understands the project's context, so I don't need to explain the background every time. Just saying "I want to add a new endpoint to this API" gets suggestions that match the existing API structure.

5.2 Effective Project Organization Methods

Writing Project Descriptions

Writing detailed descriptions when creating a Project helps Claude understand the context better:

Project Name: EcoShop E-commerce Platform Development

Overview: This is a development project for an eco-friendly product specialized e-commerce platform.

Tech Stack:
- Frontend: React 18, TypeScript, Tailwind CSS
- Backend: Node.js, Express, PostgreSQL
- Infrastructure: AWS (EC2, RDS, S3)

Coding Conventions:
- Use ESLint + Prettier
- Use functional components and hooks
- Korean comments allowed, variable names in English

Current Stage: MVP development (February 2026 launch target)

Document Organization

Organizing uploaded documents systematically helps Claude reference them more accurately:

  • Technical specifications and architecture documents
  • Coding style guide
  • API documentation
  • Meeting notes and decision records
  • Frequently occurring problems and solutions

5.3 Projects Use Cases

  • Software Development: Upload codebase, documentation, issue tracker information for consistent development support
  • Content Creation: Reference brand guidelines, tone and manner, previous content for consistent content generation
  • Research Projects: Gather papers, references, research notes for literature review or analysis
  • Business Analysis: Strategy development based on financial statements, market reports, competitor analysis materials

6. Utilizing the 200K Token Context Window

6.1 Why Context Size Matters

Claude's 200,000 token context window is equivalent to about 150,000 words, or 300-500 pages of a book. To understand what this actually means:

  • You can analyze an entire average-length novel at once
  • You can review the entire codebase of a medium-sized software project
  • You can conduct comprehensive analysis while simultaneously referencing dozens of documents

Previously, long documents had to be processed in multiple pieces, with context loss during the process. But now you can process entire documents at once, yielding much more accurate and consistent results.

6.2 Large Context Utilization Strategies

Full Document Analysis

For summarization, key point extraction, or structural analysis of long documents, inputting the entire document yields much more accurate results than partial analysis.

The following is the full text of our company's 2025 annual report. [200-page report]

Analyze this report and organize:
1. 5 major achievements
2. 3 risk factors
3. Suggestions for 2026 strategic direction

Multi-Document Comparison

You can input multiple documents simultaneously for comparative analysis:

The following are product introduction materials from three competitors:

[Company A product document]
[Company B product document]
[Company C product document]

Compare and analyze the features, pricing, and target customers of all three products,
and find differentiation points for our product.

Code Review

You can review code spanning multiple files at once:

The following are the main files from our project:

[File 1: src/components/Dashboard.tsx]
[File 2: src/hooks/useData.ts]
[File 3: src/services/api.ts]
[File 4: src/utils/helpers.ts]

Review overall code quality, architecture, and potential bugs.

6.3 Efficient Token Usage Tips

Even though 200K tokens seems like a lot, it can be quickly exhausted in complex tasks. Tips for efficient use:

  • Remove irrelevant content: When inputting documents, exclude parts not needed for analysis (headers, footers, legal notices, etc.).
  • Summary then detailed analysis: First request an overall summary, then request detailed analysis only for necessary parts.
  • Utilize Projects: Upload repeatedly referenced documents to Projects so you don't need to input them each time.

7. ChatGPT vs Claude: Selection Guide by Use Case

7.1 Objective Comparison

Both AIs are excellent tools, and it's difficult to definitively say "which is better." Each has pros and cons, and the more suitable choice varies by situation.

Category ChatGPT (GPT-4) Claude 3.5
Context Window 128K tokens 200K tokens
Plugins/Integrations Various plugins, internet search Limited (Projects, Artifacts focused)
Image Generation DALL-E integration Not supported
Code Execution Code Interpreter Artifacts (web technologies)
Writing Style Diverse and flexible More natural and human-like
Safety Standard More conservative

7.2 Recommendations by Situation

When ChatGPT is more suitable:

  • Search-based tasks requiring latest information
  • When image generation is needed
  • Python code execution and data analysis
  • When various external service integrations are needed

When Claude is more suitable:

  • Very long document analysis (150K+ tokens)
  • Tasks where natural writing is important
  • Balanced analysis on sensitive topics
  • Code explanation and educational purposes
  • Long-term project management (using Projects)
  • Interactive web prototype creation

7.3 Practical Combined Usage

I use both AIs complementarily. For example:

  1. Search latest trends or specific information with ChatGPT
  2. Synthesize collected information and write analysis reports with Claude
  3. Process data with ChatGPT's Code Interpreter
  4. Create result visualization and presentation materials with Claude's Artifacts

Rather than being dependent on either one, understanding each tool's strengths and using them appropriately is the wisest approach.

Conclusion: Growing Together with Claude

Claude goes beyond being a simple AI chatbot to become a tool that can be a true AI collaboration partner. The philosophical foundation of Constitutional AI, excellent context understanding, and innovative features like Artifacts and Projects combine to provide a unique user experience.

Of course, no tool is perfect. Claude can sometimes be too cautious, or fall behind competitors in certain tasks. What's important is understanding these characteristics and using them according to your needs.

In the next part, we'll cover advanced prompt techniques like Chain of Thought and Few-shot Learning, introducing expert-level techniques that can be applied not just to Claude but to various AI models. Let's move forward together to the next stage of our AI prompt engineering journey.

If you have questions or comments, please leave them in the comments. Sharing your actual usage experiences would be greatly appreciated.