13｜Claude Code with Crazyrouter, Part 13: Chapter 10: Solving Problems with a Programming Mindset

13｜Claude Code Integration with Crazyrouter Series 13: Chapter 10: Solving Problems with a Programming Mindset#

This is the 13th article in the Crazyrouter Claude Code series. This article focuses on “Claude Code Integration with Crazyrouter Series 13: Chapter 10: Solving Problems with a Programming Mindset,” covering Chapter 10: Solving Problems with a Programming Mindset, 10.1 What Is a “Programming Mindset,” and a simple way to understand programming thinking.

Unified integration convention: Claude Code / Anthropic native clients should use ANTHROPIC_BASE_URL=https://cn.crazyrouter.com; OpenAI-compatible SDKs, HTTP requests, and frontend/backend applications should use base_url=https://cn.crazyrouter.com/v1.

Guide to This Article#

• Who this is for: developers who are using Claude Code, preparing to connect to domestic models, or hoping to unify their team’s model calls through Crazyrouter.
• What you’ll learn: how to configure environment variables according to the Crazyrouter documentation, organize workflows, and avoid the /v1/v1/... issue caused by an incorrect Base URL.
• Recommended preparation: first create a separate API Token in the Crazyrouter console, then follow the Claude Code integration documentation to complete the basic setup.

Chapter 10: Solving Problems with a Programming Mindset#

10.1 What Is a “Programming Mindset”#

A programming mindset is a way of thinking for solving problems. It applies not only to programming, but also to all kinds of problems in daily work and life. Mastering a programming mindset can help you solve problems more efficiently.

A Simple Way to Understand Programming Thinking#

Core Concepts#

Programming thinking means breaking complex problems down into simple steps, then executing those steps in a logical order to solve the problem.

Simply put, programming thinking includes:

1. Problem decomposition: breaking a large problem into smaller problems
2. Pattern recognition: identifying rules and patterns in the problem
3. Abstraction: extracting general methods from specific problems
4. Algorithm design: designing the steps and process for solving the problem

Programming Thinking in Everyday Life#

In fact, we often use programming thinking in everyday life without realizing it.

Example 1: Cooking

• Problem decomposition: prepare ingredients → process ingredients → cook → plate
• Pattern recognition: cooking follows similar steps each time
• Abstraction: summarize the general cooking process
• Algorithm design: follow the recipe step by step

Example 2: Traveling

• Problem decomposition: choose a destination → check transportation → book tickets → pack → depart
• Pattern recognition: every trip follows similar steps
• Abstraction: summarize the general travel process
• Algorithm design: execute according to the plan

Why Non-Programmers Need It Too#

Improve Work Efficiency#

1. Systematic thinking

• Break complex tasks into simple steps
• Execute them in logical order
• Avoid omissions and confusion

1. Automation

• Identify repetitive tasks
• Design automated workflows
• Save time and effort

1. Workflow optimization

• Analyze existing processes
• Identify areas for improvement
• Design more efficient workflows

Improve Problem-Solving Ability#

1. Structured thinking

• Structure complex problems
• Analyze problems clearly
• Solve problems systematically

1. Logical reasoning

• Apply logical reasoning
• Identify the essence of the problem
• Design effective solutions

1. Innovative thinking

• Think about problems from different angles
• Discover new solutions
• Solve problems creatively

Adapt to the Digital Era#

1. Understand technology

• Better understand technical products
• Use tools more effectively
• Adapt to new technologies faster

1. Collaborate with AI

• Collaborate with AI more effectively
• Use AI tools more efficiently
• Achieve goals faster

1. Data-driven decision-making

• Better understand data
• Analyze data more effectively
• Make decisions more scientifically

Applying Programming Thinking in Daily Work#

Document Processing#

Scenario: You need to process a large number of documents

Applying programming thinking:

1. Problem decomposition:

   • Identify the types of documents to process
   • Determine the processing steps for each document
   • Design a batch-processing workflow

2. Pattern recognition:

   • Identify common characteristics across documents
   • Summarize processing patterns
   • Design a general-purpose method

3. Abstraction:

   • Extract the general workflow for processing documents
   • Design reusable templates
   • Establish standardized processes

4. Algorithm design:

   • Design the processing steps
   • Determine the execution order
   • Implement the processing workflow

Tool: Claude Code can help you automate the processing

Data Analysis#

Scenario: You need to analyze sales data

Applying programming thinking:

1. Problem decomposition:

   • Define the analysis goals
   • Identify the required data
   • Design the analysis steps

2. Pattern recognition:

   • Identify patterns in the data
   • Discover trends and anomalies
   • Summarize analysis patterns

3. Abstraction:

   • Extract analysis methods
   • Design analysis templates
   • Establish an analysis workflow

4. Algorithm design:

   • Design the analysis steps
   • Determine the analysis order
   • Implement the analysis workflow

Tool: Claude Code can help you with data analysis

Content Creation#

Scenario: You need to create a large amount of content

Applying programming thinking:

1. Problem decomposition:

   • Define the content creation goals
   • Identify content types
   • Design the creation steps

2. Pattern recognition:

   • Identify common characteristics across content
   • Summarize creation patterns
   • Design content creation templates

3. Abstraction:

   • Extract creation methods
   • Design reusable templates
   • Establish a content creation workflow

4. Algorithm design:

   • Design the creation steps
   • Determine the creation order
   • Implement the creation workflow

Tool: Claude Code can help you generate content

Case Examples#

Case: Processing Meeting Minutes with a Programming Mindset#

Scenario: You need to prepare meeting minutes every week

Traditional approach:

1. Attend the meeting
2. Record the meeting content
3. Manually organize the meeting minutes
4. Time required: 2–3 hours

Programming-mindset approach:

1. Problem decomposition

• Identify the components of meeting minutes

  • Basic meeting information: time, location, attendees
  • Meeting agenda
  • Meeting content
  • Decisions made
  • Action items
  • Next meeting arrangements

1. Pattern recognition

• Identify the common structure of meeting minutes
• Summarize the writing patterns for meeting minutes
• Design a meeting minutes template

1. Abstraction

• Extract the general workflow for meeting minutes

  • Collect meeting information
  • Organize meeting content
  • Extract decisions made
  • List action items
  • Generate meeting minutes

1. Algorithm design

• Design an automated workflow

  • Use a recording device to record the meeting
  • Transcribe the recording into text
  • Use Claude Code to organize the meeting minutes
  • Review and adjust manually
  • Send the meeting minutes

Results:

• Original time required: 2–3 hours
• Current time required: 30–45 minutes
• Time saved: 70–80%

Case: Generating Weekly Reports with a Programming Mindset#

Scenario: You need to generate a weekly report every week

Traditional approach:

1. Collect work data for the week
2. Manually organize the weekly report
3. Time required: 3–4 hours

Programming-mindset approach:

1. Problem decomposition

• Identify the components of a weekly report

  • Summary of this week’s work
  • Data analysis
  • Issues and suggestions
  • Plan for next week

1. Pattern recognition

• Identify the common structure of weekly reports
• Summarize the writing patterns for weekly reports
• Design a weekly report template

1. Abstraction

• Extract the general workflow for weekly reports

  • Collect work data
  • Analyze data
  • Generate the weekly report
  • Review manually
  • Send the weekly report

1. Algorithm design

• Design an automated workflow

  • Export data from the project management tool
  • Use Claude Code to generate the weekly report
  • Review and adjust manually
  • Send the weekly report

Results:

• Original time required: 3–4 hours
• Current time required: 30–45 minutes
• Time saved: 80–85%

Tips#

1. Start with small problems: practice programming thinking on simple problems first
2. Think and summarize more: regularly think about how to solve problems with a programming mindset
3. Record your experience: document your experience using programming thinking to solve problems
4. Keep learning: continuously learn new methods and techniques
5. Apply it in practice: use programming thinking in real work
6. Share and discuss: share applications of programming thinking with your colleagues

Now, try using a programming mindset to solve your work problems!

10.2 How to Break Down Complex Problems#

Learning how to break down complex problems is one of the core skills of programming thinking. Breaking a large problem into smaller problems makes it easier to solve and easier to manage.

Break Large Problems into Small Steps#

Principles of Problem Decomposition#

1. Independence

• Each small step should be independent
• Minimize dependencies between small steps
• Each small step should be completable on its own

1. Actionability

• Each small step should be actionable
• Each small step should be specific enough
• You should be able to execute each small step directly

1. Verifiability

• The result of each small step should be verifiable
• You should be able to determine whether a small step is complete
• You should be able to evaluate the quality of each small step

Methods for Breaking Down Problems#

Method 1: Top-down

• Start with the overall problem
• Gradually break it down into subproblems
• Continue until each subproblem can be solved directly

Method 2: Bottom-up

• Start with specific tasks
• Gradually combine them into larger tasks
• Continue until the overall problem is complete

Method 3: Hybrid approach

• Combine top-down and bottom-up approaches
• Choose the method based on the actual situation
• Adjust the decomposition strategy flexibly

Example Walkthrough#

Problem: Build a customer management system for the company

Decomposition process:

First-level decomposition:

1. Requirements analysis
2. System design
3. System development
4. Testing and launch

Second-level decomposition (using system development as an example):

1. Requirements analysis

2. System design

3. System development

   • Database design
   • Backend development
   • Frontend development
   • API development

4. Testing and launch

Third-level decomposition (using backend development as an example):

1. Requirements analysis

2. System design

3. System development

   • Database design

   • Backend development

     • User management module
     • Customer management module
     • Order management module
     • Report management module

   • Frontend development

   • API development

4. Testing and launch

Fourth-level decomposition (using the customer management module as an example):

1. Requirements analysis

2. System design

3. System development

   • Database design

   • Backend development

     • User management module

     • Customer management module

       • Enter customer information
       • Query customer information
       • Modify customer information
       • Delete customer information

     • Order management module

     • Report management module

   • Frontend development

   • API development

4. Testing and launch

Identify the Core Elements of a Problem#

Methods for Identifying Elements#

1. 5W1H analysis

• What: What is the problem?
• Why: Why did this problem occur?
• Who: Who is involved in this problem?
• When: When did the problem occur?
• Where: Where did the problem occur?
• How: How can this problem be solved?

1. Fishbone diagram analysis

• Draw a fishbone diagram
• Identify the causes of the problem
• Find the root cause

1. SWOT analysis

• Strengths: The strengths related to the problem
• Weaknesses: The weaknesses related to the problem
• Opportunities: The opportunities related to the problem
• Threats: The threats related to the problem

Example Walkthrough#

Problem: The company's sales have declined for three consecutive months

5W1H analysis:

• What: Sales are declining
• Why: Intensified market competition, insufficient product competitiveness, poor marketing effectiveness
• Who: Sales team, marketing team, product team
• When: The past three months
• Where: Nationwide market
• How: Improve product competitiveness, strengthen marketing, optimize sales strategies

Fishbone diagram analysis:

• Market factors: Intensified competition, changing demand
• Product factors: Insufficient competitiveness, slow updates
• Marketing factors: Poor effectiveness, limited channels
• Sales factors: Insufficient capabilities, insufficient incentives
• Management factors: Improper strategy, insufficient resources

SWOT analysis:

• Strengths: Strong brand recognition, solid customer base
• Weaknesses: Insufficient product competitiveness, poor marketing effectiveness
• Opportunities: Large market potential, application of new technologies
• Threats: Intensified competition, rising costs

Determine the Order for Solving Problems#

Methods for Setting Priorities#

1. Urgent-important matrix

• Urgent and important: Handle immediately
• Urgent but not important: Delegate to others
• Not urgent but important: Schedule for later
• Not urgent and not important: Defer

1. Value assessment method

• Assess the value of each task
• Prioritize high-value tasks
• Allocate resources appropriately

1. Dependency-based method

• Identify dependencies between tasks
• Determine the order based on dependencies
• Ensure tasks can proceed smoothly

Example Walkthrough#

Problem: Complete the launch of a new product

Task list:

1. Product development
2. Market research
3. Marketing planning
4. Sales training
5. Customer testing
6. Product launch

Urgent-important matrix analysis:

• Urgent and important: Product development, customer testing
• Urgent but not important: Sales training
• Not urgent but important: Market research, marketing planning
• Not urgent and not important: Product launch

Value assessment analysis:

• High value: Product development, market research, marketing planning
• Medium value: Customer testing, sales training
• Low value: Product launch

Dependency analysis:

1. Market research (no dependencies)
2. Product development (depends on market research)
3. Customer testing (depends on product development)
4. Marketing planning (depends on market research)
5. Sales training (depends on marketing planning)
6. Product launch (depends on product development, customer testing, marketing planning, and sales training)

Final order:

1. Market research
2. Product development and marketing planning (in parallel)
3. Customer testing and sales training (in parallel)
4. Product launch

Case Examples#

Case: Breaking Down the Problem of "Improving Customer Satisfaction"#

Problem: The company's customer satisfaction has declined, and customer satisfaction needs to be improved

Decomposition process:

First-level decomposition:

1. Analyze the current state of customer satisfaction
2. Identify factors that affect customer satisfaction
3. Develop improvement measures
4. Implement improvement measures
5. Evaluate the improvement results

Second-level decomposition (using factor identification as an example):

1. Analyze the current state of customer satisfaction

2. Identify factors that affect customer satisfaction

   • Product factors
   • Service factors
   • Price factors
   • Communication factors

3. Develop improvement measures

4. Implement improvement measures

5. Evaluate the improvement results

Third-level decomposition (using product factors as an example):

1. Analyze the current state of customer satisfaction

2. Identify factors that affect customer satisfaction

   • Product factors

     • Product quality
     • Product features
     • Product stability
     • Product ease of use

   • Service factors

   • Price factors

   • Communication factors

3. Develop improvement measures

4. Implement improvement measures

5. Evaluate the improvement results

Core element identification:

• Product quality: The factor customers care about most
• Service quality: Affects the customer experience
• Price reasonableness: Affects customer decisions
• Communication efficiency: Affects how customers feel

Solution order:

1. Analyze the current state of customer satisfaction (urgent and important)
2. Identify influencing factors (urgent and important)
3. Develop improvement measures (not urgent but important)
4. Implement improvement measures (urgent and important)
5. Evaluate the improvement results (not urgent but important)

Case: Breaking Down the Problem of "Optimizing Workflows"#

Problem: The department's work efficiency is low, and workflows need to be optimized

Decomposition process:

First-level decomposition:

1. Analyze existing workflows
2. Identify problems in the workflows
3. Design an optimization plan
4. Implement the optimization plan
5. Evaluate the optimization results

Second-level decomposition (using problem identification as an example):

1. Analyze existing workflows

2. Identify problems in the workflows

   • Complex processes
   • Too many repeated steps
   • Cumbersome approvals
   • Poor information flow

3. Design an optimization plan

4. Implement the optimization plan

5. Evaluate the optimization results

Third-level decomposition (using process complexity as an example):

1. Analyze existing workflows

2. Identify problems in the workflows

   • Complex processes

     • Too many steps
     • Too many people involved
     • Complex dependencies

   • Too many repeated steps

   • Cumbersome approvals

   • Poor information flow

3. Design an optimization plan

4. Implement the optimization plan

5. Evaluate the optimization results

Core element identification:

• Process efficiency: Affects overall work efficiency
• Information flow: Affects collaboration efficiency
• Staffing: Affects execution efficiency
• Tool support: Affects operational efficiency

Solution order:

1. Analyze existing workflows (urgent and important)
2. Identify problems in the workflows (urgent and important)
3. Design an optimization plan (not urgent but important)
4. Implement the optimization plan (urgent and important)
5. Evaluate the optimization results (not urgent but important)

Tips#

1. Use diagrams: Use tools such as mind maps and flowcharts to support decomposition
2. Refine gradually: Do not try to break everything down to the finest level in one pass; refine step by step
3. Stay flexible: A decomposition plan is not fixed forever; adjust it based on the actual situation
4. Record the process: Document the decomposition process for future reference
5. Ask for feedback: Discuss the decomposition plan with colleagues and gather feedback
6. Keep optimizing: Continuously improve the decomposition plan based on execution results

Now, try using these methods to break down your own complex problem.

10.3 Design Solutions#

Designing a solution is a key part of problem solving. A good solution should solve the problem effectively while remaining feasible and actionable.

Choose the Right Tools and Methods#

Principles for Choosing Tools#

1. Applicability

• The tool should be suitable for the type of problem
• The tool should meet the needs of the problem
• The tool should match the user's skill level

1. Efficiency

• The tool should improve efficiency
• The tool should save time
• The tool should reduce costs

1. Reliability

• The tool should be stable and reliable
• The tool should have good support
• The tool should be updated continuously

Common Tools and Methods#

1. Claude Code

• Use cases: text processing, data analysis, content generation, and more
• Advantages: intelligent, easy to use, feature-rich
• How to use: interact through conversation, provide requirements, and get results

1. Excel

• Use cases: data processing, data analysis, report generation, and more
• Advantages: widely adopted, powerful, easy to get started with
• How to use: work with spreadsheets and use formulas and functions

1. Professional software

• Use cases: domain-specific professional tasks
• Advantages: highly specialized, comprehensive features, excellent results
• How to use: learn the workflow based on the software's characteristics

1. Automation tools

• Use cases: repetitive tasks, batch processing, and more
• Advantages: highly automated, saves time, reduces errors
• How to use: configure automation workflows and set trigger conditions

Tool Selection Example#

Problem: You need to process a large amount of customer data

Available tools:

1. Excel: suitable for data organization and basic analysis
2. Claude Code: suitable for data analysis and report generation
3. Professional data analysis software: suitable for complex data analysis

Selection advice:

• If you only need simple data organization: choose Excel
• If you need to generate analysis reports: choose Claude Code
• If you need complex data analysis: choose professional data analysis software

Steps for Planning a Solution#

Principles for Step Planning#

1. Logical flow

• Steps should have logical relationships
• The order of steps should be reasonable
• Transitions between steps should feel natural

1. Completeness

• Steps should cover the entire problem
• Steps should leave nothing out
• Steps should form a closed loop

1. Actionability

• Each step should be actionable
• Each step should be specific
• Each step should be verifiable

Methods for Step Planning#

Method 1: Sequential planning

• Plan steps in logical order
• Each step depends on the previous step
• Suitable for linear problems

Method 2: Parallel planning

• Identify steps that can be executed in parallel
• Execute multiple steps at the same time
• Suitable for problems that can be decomposed

Method 3: Iterative planning

• Plan an initial solution
• Execute and evaluate it
• Adjust the solution based on the evaluation results
• Suitable for complex problems

Step Planning Example#

Problem: You need to build a customer feedback system

Step plan:

Phase 1: Requirements analysis

1. Collect user requirements
2. Analyze user requirements
3. Define functional requirements
4. Define non-functional requirements

Phase 2: System design

1. Design the system architecture
2. Design the database
3. Design the interfaces
4. Design the UI

Phase 3: System development

1. Develop the backend
2. Develop the frontend
3. Run integration testing
4. Optimize performance

Phase 4: Testing and launch

1. Functional testing
2. Performance testing
3. User testing
4. Official launch

Phase 5: Operations and optimization

1. Monitor the system
2. Collect feedback
3. Optimize the system
4. Continuously improve

Estimating Potential Problems#

Methods for Estimating Problems#

1. Risk assessment

• Identify possible risks
• Assess the probability of each risk
• Assess the impact of each risk
• Develop mitigation measures

1. Learning from experience

• Refer to experience from solving similar problems
• Learn from others' success stories
• Avoid others' mistakes

1. Expert consultation

• Consult domain experts
• Get professional advice
• Improve the feasibility of the solution

Common Problem Types#

1. Technical issues

• Unfamiliar tools
• High technical difficulty
• Technical limitations

1. Resource issues

• Not enough time
• Not enough people
• Not enough budget

1. Collaboration issues

• Poor communication
• Unclear responsibilities
• Coordination difficulties

1. External issues

• Requirement changes
• Environment changes
• Intensifying competition

Response Strategies#

1. Preventive measures

• Learn the tools in advance
• Allocate resources reasonably
• Establish communication mechanisms
• Create contingency plans

1. Emergency measures

• Respond quickly
• Adjust in time
• Ask for help
• Adapt flexibly

1. Continuous improvement

• Summarize lessons learned
• Optimize the solution
• Improve response capabilities
• Build a knowledge base

Case Examples#

Case: Designing an "Automated Report Generation" Solution#

Problem: A sales report needs to be generated every week, taking 3–4 hours

Tool selection:

• Claude Code: used to generate report content
• Excel: used for data processing and chart generation
• Email: used to send the report

Step plan:

Step 1: Data collection

• Export data from the sales system
• Export customer data from the CRM system
• Export marketing data from the marketing system

Step 2: Data processing

• Use Excel to clean the data
• Use Excel to standardize formats
• Use Excel to calculate metrics

Step 3: Data analysis

• Use Claude Code to analyze the data
• Use Claude Code to generate insights
• Use Claude Code to provide recommendations

Step 4: Report generation

• Use Claude Code to generate the report
• Use Excel to generate charts
• Integrate the report content

Step 5: Report delivery

• Review the report content
• Send the report by email
• Save the report archive

Problem estimation:

1. Data collection may run into system failures
2. Data processing may run into inconsistent formats
3. Data analysis may run into data quality issues
4. Report generation may run into inaccurate content

Response strategies:

1. Test system connections in advance and prepare a backup plan
2. Establish data format standards and unify data sources
3. Establish a data quality check mechanism to detect and fix issues promptly
4. Manually review report content to ensure accuracy

Results:

• Original time spent: 3–4 hours
• Current time spent: 30–45 minutes
• Time saved: 80–85%

Case: Designing a "Customer Service Optimization" Solution#

Problem: Customer service response is slow, and customer satisfaction is low

Tool selection:

• Claude Code: used to generate reply templates
• Customer service system: used to manage customer inquiries
• Knowledge base: used to store answers to frequently asked questions

Step plan:

Step 1: Problem analysis

• Collect customer feedback
• Analyze customer complaints
• Identify service bottlenecks

Step 2: Knowledge base creation

• Organize frequently asked questions
• Write standard answers
• Build the knowledge base

Step 3: Reply template generation

• Use Claude Code to generate reply templates
• Categorize and organize templates
• Optimize template content

Step 4: Process optimization

• Simplify the service process
• Optimize the response mechanism
• Improve processing efficiency

Step 5: Staff training

• Train customer service staff
• Improve service skills
• Strengthen service awareness

Step 6: Results evaluation

• Collect customer feedback
• Analyze service data
• Evaluate the improvement results

Problem estimation:

1. Knowledge base creation may run into incomplete content
2. Reply templates may not be flexible enough
3. Process optimization may meet resistance
4. Staff training may not produce good results

Response strategies:

1. Continuously update the knowledge base and collect new questions and answers
2. Design flexible templates that support personalized adjustments
3. Communicate thoroughly, gain support, and roll out changes gradually
4. Strengthen training, provide guidance, and follow up continuously

Results:

• Response time: reduced from an average of 4 hours to 30 minutes
• Customer satisfaction: increased from 70% to 90%
• Improvement: significant

Tips#

1. Compare multiple options: design several solutions, compare them, and choose the best one
2. Run a small-scale pilot: test the solution in a limited scope first to validate feasibility
3. Keep optimizing: continuously optimize the solution based on execution results
4. Record the process: document the design process for future reference
5. Ask for feedback: discuss the solution with colleagues and gather feedback
6. Adjust flexibly: adapt the solution based on the actual situation

Now, try designing your own solution!

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Further Reading#

• Previous article: Article 12
• Next article: Article 14
• Configuration docs: Connect Claude Code to Crazyrouter
• API endpoint guide: Base URL and /v1 usage
• One-click setup script: Crazyrouter Claude Code One-Click Setup Script

Start Integrating with Crazyrouter#

If you're ready to connect Claude Code, Chinese models, or your own applications to Crazyrouter through a unified entry point, follow this sequence:

1. Go to the Crazyrouter console to create a dedicated API Token, and manage permissions separately by project or team.
2. Claude Code uses the root domain: https://cn.crazyrouter.com; OpenAI-compatible SDKs use: https://cn.crazyrouter.com/v1.
3. When you need to automatically check the environment or quickly write configuration, use the Crazyrouter Claude Code One-Click Setup Script.
4. If debugging fails, check the console logs first, then verify the API Endpoint guide, especially whether the Base URL accidentally includes an extra /v1. When you need to evaluate model costs or choose a different model, first check the Crazyrouter pricing and models page, then add the models you use frequently to the Token whitelist.