Can AI replace Careerflow?

Build a personal replacement for Careerflow in an empty repository.
Use Next.js 15, TypeScript, SQLite, Drizzle ORM, and an optional OpenAI API; do not offer alternative stacks.
The core loop is: organize job applications, create evidence-grounded resume and LinkedIn improvement checklists, tailor user-authored materials against a supplied role, and keep every claim traceable to the user's own evidence.
Make the first run work locally with one documented command.
Store all user data locally by default and make export straightforward.
Put secrets in .env, ship .env.example, and never commit credentials.
Create a structured evidence bank for roles, projects, skills, dates, metrics, and source notes.
Import a job description and highlight requirements without inventing missing experience.
Generate a tailored resume variant only from approved evidence and show the source for each bullet.
Add application stages, contacts, tasks, dates, notes, documents, and a follow-up view.
Provide interview-question practice with answer notes and a self-review rubric, not deceptive live assistance.
Export resume data as JSON and PDF plus the application tracker as CSV.
Include clear empty, loading, success, and recoverable error states.
Add input validation, safe filenames, and graceful handling of unavailable APIs.
Write focused tests for the core transformation and one end-to-end happy path.
Create a README with setup, architecture, permissions, data location, and backup steps.
Do not add accounts, billing, telemetry, analytics, or a hosted control plane.
Deliberately leave out automatic mass application.
Deliberately leave out fabricated qualifications or deceptive interview assistance.
Deliberately leave out proprietary recruiter databases and guaranteed job outcomes.
Finish by running the tests and listing the exact commands used.