A large-scale frontend modernisation initiative was undertaken to migrate a legacy application built on Angular 1.5 to a more modern, scalable framework using Next.js. Given the sheer size and complexity of the application, the team chose an AI-assisted approach to help streamline the process, keep things moving efficiently, and ensure the end result met current development standards.

Challenges Identified:

• Outdated Frontend Technology: The application had been running on Angular 1.5 for some time, and the limitations were beginning to show — from constrained scalability and performance bottlenecks to growing incompatibility with the way modern development teams work.
• High Migration Complexity: With an application of this size, going the manual route wasn’t really a viable option. It would have been slow, and the risk of ending up with an inconsistent codebase was very real.
• Risk of Functional Gaps: Rewriting large chunks of the frontend always carries the danger of something slipping through the cracks — whether that’s a piece of business logic or a subtle UI behaviour that users rely on.
• Standardisation Challenges: Keeping coding standards and architecture decisions consistent across a migration of this scale is genuinely hard to do by hand. Without guardrails, things tend to drift.

Solution Features:

The team put in place an AI-assisted development workflow to support a structured and efficient migration:

• AI-Assisted Code Migration: Tools like GitHub Copilot and Claude were brought in to help analyse and refactor the legacy AngularJS code into modern Next.js components. This took a significant amount of repetitive work off the team’s plate and kept development moving at a good pace.
• Complementary Use of Copilot and Claude: Rather than treating these tools as interchangeable, the team used them in ways that played to their respective strengths. Copilot handled in-editor suggestions and helped accelerate repetitive patterns, while Claude was used for working through more complex logic, thinking through architecture decisions, and translating nuanced Angular constructs into idiomatic React and Next.js.
• Framework Transition to Next.js: Moving to Next.js opened up server-side rendering, noticeably better performance, and a frontend architecture that could actually grow with the product.
• Code Refactoring and Optimisation: Legacy patterns and outdated structures were reworked into modular, reusable components — the kind that are easier to maintain and build on top of.
• Consistency and Standards Enforcement: AI-assisted suggestions acted as a useful check, helping the team maintain uniform coding standards throughout and keeping the codebase readable and coherent.
• Incremental Migration Strategy: Rather than attempting a big-bang cutover, the migration was broken into phases. This gave the team the ability to validate functionality continuously and catch issues early, without destabilising what was already working.

Advantages:

• Faster Migration Execution: Having AI support in the loop made a meaningful difference to the pace of migration, particularly across a codebase of this complexity.
• Improved Code Quality: The refactored components came out cleaner and more aligned with modern practices, making the application easier to maintain going forward.
• Reduced Risk of Errors: AI assistance acted as an extra layer of validation, reducing the likelihood of logic being missed or inconsistencies creeping in during the transition.
• Enhanced Performance and Scalability: The move to Next.js delivered real performance gains and left the application in a much better position for future development.

Conclusion: 

This project is a good example of what’s possible when AI-assisted tools are used thoughtfully in a large-scale modernisation effort. By moving from Angular 1.5 to Next.js with the support of GitHub Copilot and Claude, the team was able to modernise the application without sacrificing functional integrity — and came out the other side with a codebase that performs better and is built to last. It’s an approach worth considering for any organisation looking to tackle legacy frontend transformation in a structured and scalable way.