🚀 Resume Feedback Is Easy — Until You Try Making It Context-Aware
While building my AI Career Advisor, I initially assumed resume feedback would be one of the simplest features. Upload resume → analyze → give suggestions. There are already dozens of tools doing t...

Source: DEV Community
While building my AI Career Advisor, I initially assumed resume feedback would be one of the simplest features. Upload resume → analyze → give suggestions. There are already dozens of tools doing this, so it seemed straightforward. But once I introduced memory and user context, things became much more complex. 🧠 What the system actually needs to do At a basic level, the system should: Parse a resume Extract skills and projects Compare them with target roles Suggest improvements Simple enough — but in practice, this wasn’t sufficient. Because a resume is only a "snapshot", not the full story. ⚠️ The real problem: resumes are incomplete Users often: Forget to include recent work Undersell their projects Omit important details If the system only analyzes the uploaded resume, it misses critical context. So the real challenge became: 👉 'How do we combine resume data with stored user memory?' ❌ First attempt: treat resume as the source of truth const parsedResume = parseResume(file); const