Claude Code | FedEx x Anthropic

Developer Productivity Breakthrough

Real metrics from enterprise engineering teams using Claude Code

40%

Faster Feature Development

60%

Reduced Debugging Time

3x

Faster Onboarding

85%

Code Review Pass Rate

What is Claude Code?

Claude Code is an AI-powered development assistant that works alongside your FedEx engineering teams. It understands context across your entire codebase, suggests improvements, catches bugs, and helps modernize legacy systems.

Multi-file editing: Refactor across dozens of files simultaneously
Legacy modernization: Migrate COBOL, mainframe code to modern stacks
Natural language queries: "Find all API calls that don't have error handling"
Test generation: Automatically create comprehensive unit tests
Code review assistance: Identify security issues, performance bottlenecks

Start Using Claude Code →

claude-code.sh

$ claude-code > Find all database queries in our shipping module that could cause N+1 problems Analyzing codebase... Found 12 potential N+1 query issues: 1. ShipmentRepository.java:156 // Loading addresses in a loop for (Shipment s : shipments) { s.getAddress(); // N+1! } 💡 Suggestion: Use JOIN FETCH > Apply all fixes ✓ Fixed 12 files, added eager loading ✓ Estimated 85% query performance improvement ✓ Generated integration tests

Powerful Features for FedEx Engineering

Built specifically for enterprise software development at scale

🔍

Intelligent Code Search

Search across millions of lines of code using natural language. Find patterns, dependencies, and potential issues instantly.

// Natural language query:
"Show me all API endpoints that
 access customer PII without
 encryption"
                        

🔧

Multi-File Refactoring

Refactor entire features across multiple files, services, and repositories while maintaining consistency.

// One command, 47 files updated:
"Rename ShippingService to
 LogisticsService across all
 repos, update tests"
                        

🏗️

Legacy System Modernization

Migrate legacy COBOL, mainframe, or monolithic code to modern microservices architecture.

// Modernization assistant:
"Convert this COBOL module to
 Java Spring Boot microservice
 with REST APIs"
                        

🧪

Automated Test Generation

Generate comprehensive unit, integration, and E2E tests with edge cases and mocking.

// Test generation:
"Write unit tests for
 RateCalculator class with
 100% coverage"
                        

🔒

Security & Compliance

Identify security vulnerabilities, ensure compliance with FedEx coding standards, and enforce best practices.

// Security audit:
"Scan for SQL injection,
 XSS vulnerabilities, and
 insecure dependencies"
                        

📚

Documentation Generation

Automatically generate API docs, README files, inline comments, and architecture diagrams.

// Documentation:
"Generate OpenAPI spec and
 developer guide for this
 REST API"
                        

Interactive Demo

See Claude Code in action on real FedEx use cases

Use Case: Modernize Legacy Shipment Tracking System

Convert a 30-year-old COBOL tracking system to a modern Java microservice

Before: COBOL Legacy Code

SHIPTRACK.COB

IDENTIFICATION DIVISION. PROGRAM-ID. SHIPTRACK. DATA DIVISION. WORKING-STORAGE SECTION. 01 TRACKING-NUMBER PIC X(15). 01 SHIP-STATUS PIC X(20). 01 SHIP-LOCATION PIC X(50). PROCEDURE DIVISION. ACCEPT TRACKING-NUMBER. PERFORM QUERY-DATABASE. DISPLAY SHIP-STATUS. DISPLAY SHIP-LOCATION. STOP RUN. QUERY-DATABASE. EXEC SQL SELECT STATUS, LOCATION INTO :SHIP-STATUS, :SHIP-LOCATION FROM SHIPMENTS WHERE TRACK_NUM = :TRACKING-NUMBER END-EXEC.

After: Modern Java Microservice

TrackingService.java

@RestController @RequestMapping("/api/v1/tracking") public class TrackingService { @Autowired private ShipmentRepository repo; @GetMapping("/{trackingNumber}") public ShipmentDTO getTracking( @PathVariable String trackingNumber ) { return repo.findByTrackingNumber( trackingNumber ).map(this::toDTO) .orElseThrow(() -> new ShipmentNotFoundException() ); } }

Claude Code converted this in 12 minutes vs. 2 weeks manual rewrite

Use Case: Debug Production Issue

Identify and fix a critical performance issue causing timeout errors

$ claude-code debug

> Analyze why our shipping calculator times out for bulk orders

🔍 Analyzing call stack and performance profiles...

❌ Issue Found: RateCalculator.java:234

// Current implementation:
for (Order order : bulkOrders) {
  for (Item item : order.getItems()) {
    rate += calculateShipping(item); // API call per item!
  }
}

💡 Root Cause: N+1 API calls (avg 847 calls for bulk orders)
💡 Solution: Batch API calls, use caching layer

> Apply fix

✓ Refactored to batch API calls (1 call per 100 items)
✓ Added Redis caching for rate lookups
✓ Performance: 12.3s → 0.8s (94% improvement)
✓ Generated load tests to prevent regression
                    

Use Case: Build New REST API

Create a complete REST API for international customs documentation

$ claude-code create-api

> Create REST API for customs document generation with endpoints for:
   - Upload invoice PDF
   - Generate commercial invoice, packing list, certificate of origin
   - Return HS codes and duty calculations

🏗️  Generating API structure...

✓ Created CustomsController.java (5 endpoints)
✓ Created CustomsService.java (business logic)
✓ Created DocumentRepository.java (data layer)
✓ Generated DTOs and validation rules
✓ Added error handling and logging
✓ Created OpenAPI/Swagger documentation
✓ Generated Postman collection

📚 API Documentation: http://localhost:8080/swagger-ui
                    

Use Case: Generate Comprehensive Tests

Create unit and integration tests for critical shipping logic

$ claude-code generate-tests ShippingCalculator.java

🧪 Analyzing ShippingCalculator class...

✓ Generated 47 unit tests (100% coverage)
✓ Created 12 integration tests
✓ Added edge case tests:
  - Null/empty inputs
  - Boundary values (0, MAX_INT)
  - International shipping edge cases
  - Concurrent calculation scenarios

✓ Created mock data fixtures
✓ Added performance benchmarks

Running tests...
✓ 47/47 passed in 2.3s
                    

Developer Productivity ROI

Real cost savings for FedEx engineering teams

Time Savings Per Developer

12 hrs

Saved per week

30%

Productivity increase

4 hrs/week on code reviews and debugging
3 hrs/week on writing boilerplate code
2 hrs/week on documentation
2 hrs/week on test writing
1 hr/week on code search and navigation

Cost Savings for FedEx

$8.2M

Annual savings (500 developers)

$16,400 saved per developer per year
Features delivered 3x faster
60% reduction in production bugs
Legacy modernization costs cut by 80%
Faster onboarding: 3 months → 3 weeks

Break-Even Analysis

2 weeks

Time to ROI

1,250%

3-Year ROI

$24.6M

3-Year Total Savings

Two Ways to Deploy Claude Code

Choose the integration path that works best for your infrastructure

🚀

Direct Access

Use Claude Code CLI or API directly from Anthropic. Fastest setup, perfect for pilot programs.

Setup time: 30 minutes
CLI tool + VS Code extension
REST API integration

Direct Setup Guide →

🔷

Google Vertex AI

Integrate with Google Cloud infrastructure. Perfect for GCP-native FedEx services.

Setup time: 2-4 hours
GCP-native deployment
Cloud Logging integration

Vertex Setup Guide →

Ready to 3x Your Team's Velocity?

Start with a 2-week pilot program with your FedEx engineering team. See measurable productivity gains from day one.

Get Started Now Schedule Demo

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