The Agentic Shift in Legacy Migration

I just used VS Code + GitHub Copilot + Claude 4.6 Sonnet to migrate a legacy PHP Kohana CMS to Next.js/TypeScript in 1 week — a task estimated at 3–4 weeks. This is the Agentic Shift in action.

I just used VS Code + GitHub Copilot + Claude 4.6 Sonnet to migrate a legacy codebase that, frankly, I would have considered quitting over if I had to do it manually.

The task: Migrating a massive CMS from PHP Kohana to a modern Next.js/TypeScript stack.

Standard estimate: 3-4 weeks.
Actual time with this setup: 1 week.

This isn't just another AI integration; it's the Agentic Shift in action. We are moving beyond "autocomplete" into the era of autonomous engineering partners.

The Agentic Workflow: Architecture over Execution

The secret was building a robust Instruction Framework (via .github/copilot-instructions.md) that governed every move:

Stack Definition: TailwindCSS + shadcn/ui. Key constraint: No commercial libraries for zero-dependency overhead.
Mobile-First & Model-First: UI refactors were mobile-first by default. All TypeScript interfaces were derived from business logic models before any components were built.
DB Non-Changes: I enforced a strict policy to keep the legacy database intact, requiring the AI to build custom mapping layers to bridge old schemas with new models.

The Reality Check: It's not all "magic"

We hit a major roadblock with ORM library conflicts. Instead of me debugging for hours, I used the Copilot + Sonnet combo to analyze the conflict. It mapped out the dependency tree, refactored the mapping layer, and resolved the architectural bottleneck autonomously.

The Result: aloka.tech (Technical Review)

The outcome of this 1-week sprint is now live at https://aloka.tech

Performance: Near-perfect Lighthouse scores. By moving from Kohana's traditional rendering to Next.js SSR, we've drastically reduced LCP and improved TBT.
UI/UX: A unified design system using shadcn/ui - modular, accessible, and high-performance.
SEO & Metadata: Semantic HTML and automated metadata generation have significantly improved our indexing potential compared to the legacy system.
Admin Scalability: A full-featured admin dashboard built on a Component-driven architecture, ready for rapid feature expansion.

The Architect's Perspective

I spent 80% of my week acting as a System Architect, reviewing structural decisions rather than losing hours to syntax boilerplate. Agentic workflows won't replace engineers, but they will make "manual refactoring" look as obsolete as punch cards.

Want to replicate this 1-week migration success?

I've opened a FREE Study Mode course on using AI Agents specifically for this workflow. Learn how to architect, prompt, and deploy like an Agentic Engineer.

I'll leave the link to the free study mode in the first comment!

How are you handling your legacy technical debt? Are you leading the Agentic shift, or watching from the sidelines?