Transforming Digital Experience Velocity
How AI-First Development Delivered 50-60% Faster Time-to-Market
for a Global Entertainment, Travel & Hospitality Leader
A global entertainment, media, travel and hospitality powerhouse faced a critical challenge: legacy digital properties accumulated over the years were creating technical debt, slowing innovation, and struggling to handle millions of users during peak events. Traditional development approaches would take months to modernize their digital ecosystem—time they couldn't afford in a competitive market, making a repeatable migration framework essential.
Travel & Hospitality
Employee Count
9000+
Myridius Service Offering
Quality Engineering, Test
Automation & DevOps Integration
By pioneering an AI-first development methodology combining Adobe Edge Delivery Services with intelligent development acceleration, Myridius helped the client achieve what typically takes months in a matter of weeks with generative AI workflows, reducing component development effort by 50-60% and cutting defect resolution time by 70-80%— all while improving quality, consistency, and scalability through AI-accelerated development and automated component scaffolding.
The Business Challenge
Speed, Scale, & Technical Debt
During the early analysis of the client’s requirements, our team was able to understand three core challenges where the business was struggling, and it needed a web modernization strategy to address them.
The Stakes
For an entertainment, travel and hospitality giant serving millions of global visitors, digital properties aren't just websites—they're revenue engines. Event-driven campaigns, product launches, and seasonal peaks drive massive traffic surges that directly impact customer engagement and sales conversions.
However, their legacy infrastructure was becoming a liability and slowing down enterprise modernization during high-traffic cycles demanding more digital ecosystem modernization. These were the critical pain points
Years of accumulated complexity made even minor updates risky and time-consuming
Page load times suffered during high-traffic events, directly impacting user experience and conversion rates
Traffic spikes caused system slowdowns despite significant infrastructure investment
Creating new features or components takes days per element. This throttled their marketing agility, limiting the ability to maintain reusable components and slowing parallel development
Meeting modern compliance standards required extensive rework across legacy code.
Technical Debt Paralysis
Years of accumulated complexity made even minor updates risky and time-consuming
Performance Degradation
Page load times suffered during high-traffic events, directly impacting user experience and conversion rates
Scalability Ceiling
Traffic spikes caused system slowdowns despite significant infrastructure investment
Development Bottleneck
Creating new features or components takes days per element. This throttled their marketing agility, limiting the ability to maintain reusable components and slowing parallel development
Accessibility Gaps
Creating new features or components takes days per element. This throttled their marketing agility, limiting the ability to maintain reusable components and slowing parallel development
Business Impact
Due to these critical challenges, the business was impacted
1
Slower time-to-market for campaigns and promotions
2
User experience deterioration during critical revenue moments
3
Increasing maintenance costs consuming innovation budget
4
Competitive disadvantage in an experience-driven market
These issues led to slow time-to-market, higher operational risk, rising maintenance costs, and a widening competitive gap. This accelerated the need for digital ecosystem modernization and a scalable migration strategy.
The Strategic Response
Modernization Meets AI-First Innovation
The Vision
Rather than a conventional "lift and shift" migration, Myridius developed a legacy-to-EDS transition leveraging edge-first architecture and prompt-driven engineering. This strategy combines AI-augmented development with automated validation workflows, creating an accelerated innovation engine for scalable, high-quality delivery.
The Architecture
Adobe Edge Delivery Services (EDS) Foundation
| Edge-first block-based architecture for maximum performance | Serverless middleware (AWS Lambda, API Gateway) | Intelligent caching layer (AWS CloudFront, S3 preloading) | Multi-environment deployment (Latest, Stage, Production) | Enterprise-grade security (AWS Secrets Manager integration) |
Edge-first block-based architecture for maximum performance
Serverless middleware (AWS Lambda, API Gateway)
Intelligent caching layer (AWS CloudFront, S3 preloading)
Multi-environment deployment (Latest, Stage, Production)
Enterprise-grade security (AWS Secrets Manager integration)
The AI-First Differentiator
Cursor AI Development Assistant integrated into developer workflows enabled component generation with automated documentation
Natural language-driven component generation by prompt-driven engineering
Intelligent code scaffolding aligned to organizational standards
Automated testing and documentation generation along with continuous quality enforcement and pattern consistency
1
Cursor AI Development Assistant integrated into developer workflows enabled component generation with automated documentation
2
Natural language-driven component generation by prompt-driven engineering
3
Intelligent code scaffolding aligned to organizational standards
4
Automated testing and documentation generation along with continuous quality enforcement and pattern consistency
This created a scalable migration strategy enabling teams to build faster with fewer dependencies.
How AI-First Delivered Business Outcomes
Velocity Transformation: From Days to Hours
TRADITIONAL APPROACH
Creating a single reusable component (e.g., a promotional teaser with CTA) required
| Manual HTML/CSS/JavaScript development |
| Accessibility compliance verification |
| Responsive design testing |
| Unit test creation |
| Documentation writing |
| Code review iterations |
AI-FIRST APPROACH
Using natural language prompts, developers specified requirements -
"Create an EDS block named Teaser with title, CTA button, following accessibility guidelines, responsive design, and unit tests." Cursor generated production-ready code in minutes, enabling teams to maintain standardized templates across all components
| teaser.js with DOM rendering and interaction logic |
| teaser.css with responsive, brand-compliant styling |
| teaser.test.js with comprehensive unit tests |
| Inline documentation and comments |
Timeline:
2-3 Days for a complex or
large component
Timeline:
Hours from concept to deployment-ready driven by AI-enabled front-end development
Business Impact
1
2
3
Quality at Scale
Consistency Without Compromise
The Challenge
Multiple teams, repositories & websites required absolute consistency in code patterns, accessibility compliance, and architectural standards—typically enforced through extensive code reviews and documentation.
The AI-First Solution
Cursor was trained with organisational standards, coding conventions, and EDS best practices. Every generated component automatically adhered to the following elements, designed for multi-site migration.
| Enterprise coding standards | Responsive design patterns | Security best practices | Testing frameworks |
Enterprise coding standards
Responsive design patterns
Security best practices
Testing frameworks
Business Impact
Our intelligent development workflows and digital platform transformation helped the business drive the following benefits
1
70-80% reduction in defect resolution effort
2
Fewer regression issues in production
3
Accelerated QA cycles with standardized EDS development templates
4
Reduced code review overhead & Consistent user experience across all properties
1
70-80% reduction in defect resolution effort
2
Fewer regression issues in production
3
Accelerated QA cycles with standardized EDS development templates
4
Reduced code review overhead & Consistent user experience across all properties
Middleware Acceleration
Complex Integration, Simplified
The Challenge
Backend business logic — AWS Lambda functions, API integrations, third-party service connections — traditionally requires significant boilerplate code, security configurations, and integration testing. However, we streamlined it using AI-powered scaffolding.
The AI-First Solution
Cursor assisted developers in generating the following elements while ensuring they aligned with a repeatable migration framework.
| Lambda function scaffolding with proper error handling | AWS Secrets Manager integration for credential management | API Gateway routing configurations | Cron job setups for cache pre-warming |
Edge compute functions for personalization |
Lambda function scaffolding with proper error handling
AWS Secrets Manager integration for credential management
API Gateway routing configurations
Cron job setups for cache pre-warming
Edge compute functions for personalization
Business Impact
Our intelligent development workflows and digital platform transformation helped the business drive the following benefits
1
2
3
4
Developer Experience
From Repetition to Innovation
The Cultural Shift
Rather than replacing developers, AI augmentation freed teams from repetitive, boilerplate work to focus on
| Custom business logic & user experience optimization |
Architectural decisions & system design | Complex problem-solving & innovation | Strategic feature development |
Custom business logic & user experience optimization
Architectural decisions & system design
Complex problem-solving & innovation
Strategic feature development
Business Impact
Our intelligent development workflows and digital platform transformation helped the business drive the following benefits
1
2
3
4
Results
Measurable Business Transformation
|
Performance Outcomes |
Development Efficiency |
Quality & Consistency |
Business Agility |
| Lighthouse performance scores improved across all digital properties |
50-60% faster component & middleware development |
Standardized code patterns across all repositories | Faster response to marketing campaign requirements |
| Page load times are significantly reduced, especially during peak traffic | 70-80% reduction in defect resolution time | Improved accessibility compliance | Ability to test and iterate features rapidly |
| Scalability enables seamless handling of event-driven traffic surges | Accelerated migration velocity enabling faster ROI realization as part of a legacy-to-EDS migration | Reduced technical debt accumulation |
Parallel development across multiple teams |
| Uptime shows enhanced reliability during critical business moments |
Reduced overall project costs through efficiency gains | Enhanced maintainability and documentation | Competitive advantage through speed-to-market |
The Technology Stack
FRONT- END
-
Adobe Edge Delivery Services (EDS)
-
Block-based component architecture
- Semantic HTL, CSS, JavaScrip
DEVELOPMENT&
DEPLOYMENT
-
GitHub (version control)
- Harness (CI/CD pipelines & CI/CD automation)
- Cursor AI (development acceleration)
EDGE COMPUTING
-
Akamai Edge Workers
- Block-based component architecture
- AWS Lambda@Edge
MIDDLEWARE & BACKEND
-
AWS Lambda (serverless compute)
- AWS API Gateway (routing)
- AWS Secrets Manager (security)
- AWS CloudFront (CDN)
- AWS S3 (cashing layer)
OPTIMIZATION
-
Cron Lambdas (cache pre-warming)
- EventBridge (automated scheduling)
- Multi-layer caching stretegy
| Performance Outcomes Lighthouse performance scores improved across all digital properties Page load times are significantly reduced, especially during peak traffic Scalability enables seamless handling of event-driven traffic surges Uptime shows enhanced reliability during critical business moments |
| Development Efficiency 50-60% faster component and middleware development 70-80% reduction in defect resolution time Accelerated migration velocity enabling faster ROI realization as part of a legacy-to-EDS migration Reduced overall project costs through efficiency gains |
| Quality & Consistency Standardized code patterns across all repositories Improved accessibility compliance Reduced technical debt accumulation Enhanced maintainability and documentation |
| Business Agility Faster response to marketing campaign requirements Ability to test and iterate features rapidly Parallel development across multiple teams Competitive advantage through speed-to-market |
Prompt-Driven Development
Developers describe requirements in natural language, receiving production-ready code aligned to standards.
Intelligent Scaffolding
AI generates complete component structures—logic, styling, tests, documentation—in minutes using AI-powered scaffolding while supporting reusable components for future development.
Continuous Quality Enforcement
Real-time linting, accessibility checks, and pattern validation during development.
The AI-First Methodology
How It Works
Automated Testing
Unit tests, integration tests, and mocks generated alongside functional code.
Documentation as Code
Inline comments, README files, and technical documentation auto-generated.
Human-AI Collaboration
Developers validate, customize, and enhance AI-generated code, maintaining architectural control.
Key Success Factors
Standards-First Approach
Training AI with organizational standards ensured consistency without manual enforcement backed by automated validation workflows and strengthened enterprise modernization efforts.
Iterative Refinement
Continuous feedback loops improved AI output quality over time.
Measurable Outcomes
Clear metrics tracked efficiency gains and business impact across high-traffic digital platforms supported by generative AI workflows.
Hybrid Expertise
Human architects guided strategy while AI accelerated execution.
Strategic AI Integration
AI wasn't bolted on—it was architected into the development workflow from day one.
Key Success Factors
| Standards-First Approach |
| Training AI with organizational standards ensured consistency without manual enforcement backed by automated validation workflows and strengthened enterprise modernization efforts. |
| Iterative Refinement |
| Continuous feedback loops improved AI output quality over time. |
| Measurable Outcomes |
| Clear metrics tracked efficiency gains and business impact across high-traffic digital platforms supported by generative AI workflows. |
| Hybrid Expertise |
| Human architects guided strategy while AI accelerated execution. |
| Strategic AI Integration |
| AI wasn't bolted on—it was architected into the development workflow from day one. |
Looking Forward
The Competitive Advantage
This transformation wasn't just about migrating technology—it was about establishing a new operating model where
- Speed becomes a strategic weapon
- Quality scales automatically
- Innovation capacity multiplies
- Technical debt stops accumulating
- Developer talent focuses on differentiation
As AI-assisted development matures, the efficiency gains compound, creating widening competitive moats for organizations that embrace this methodology early.
Looking Forward
The Competitive Advantage
This transformation wasn't just about migrating technology—it was about establishing a new operating model where -
| Speed becomes a strategic weapon |
| Quality scales automatically |
| Innovation capacity multiplies |
| Technical debt stops accumulating |
| Developer talent focuses on differentiation |
As AI-assisted development matures, the efficiency gains compound, creating widening competitive moats for organizations that embrace this methodology early.
Conclusion
The Future is AI-First
In an era where digital experience directly drives business outcomes, velocity and quality can no longer be trade-offs. This case study demonstrates how an AI-first development approach delivers both—50-60% faster development, 70-80% fewer defects, and measurably better business outcomes driven by AI-powered development workflows and repeatable migration frameworks
For organizations facing similar challenges—legacy modernization, scalability demands, development bottlenecks—the question isn't whether to adopt AI-augmented development, but how quickly you can integrate it into your delivery model.
The future belongs to teams that combine human strategic thinking with AI execution velocity. The results speak for themselves.
50-60%
Faster Development
70-80%
Fewer Defects
BETTER
Business Outcomes
Ready to transform your digital delivery velocity? Download a copy of full case study to explore how AI-first development can accelerate your modernization initiatives.
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