AI can migrate a technology stack, including frameworks, languages, build tools, databases, and cloud services, when the migration is staged and backed by tests. It should not be treated as a one-prompt conversion.
Start by documenting the current system, target stack, compatibility requirements, unsupported dependencies, and rollback strategy. Build a representative proof of concept before committing the whole project. Add characterization tests for existing behavior and compare performance, security, and operational costs.
Choose an incremental pattern when possible: move one route, package, service, or UI area at a time behind stable interfaces. Parallel agents can migrate independent modules, while one owner controls shared types, schemas, and infrastructure. Generated replacements must be reviewed for semantic differences; APIs with similar names may behave differently around transactions, concurrency, errors, or lifecycle.
Verdent can plan the migration, dispatch bounded tasks, isolate work in git worktrees, and review changes. Use its model and worker controls to separate research, implementation, and verification. Require build and test evidence at every checkpoint. AI reduces mechanical conversion work, but humans should approve architecture, data migration, security, licensing, and production cutover.
