Resume, LinkedIn, portfolio or graph?
What is each one for.
They are not really competitors. Each answers a different question. The gap in most careers is the one none of them fills well: the context and evidence behind the work.
Four things, four different jobs
Compare them by the question each one answers, not by which is best.
- The question it answers
- ResumeShould we interview this person?
- LinkedIn profileWho is this, and who do they know?
- PortfolioWhat have they made?
- graphWhat did they actually do, and why did it matter?
- Who reads it
- ResumeRecruiters and hiring managers, deciding quickly
- LinkedIn profileRecruiters, peers and your network
- PortfolioAnyone who wants to inspect the work
- graphYou first, then anyone you choose to share it with
- Strongest at
- ResumeA short summary that can be scanned in seconds
- LinkedIn profileReach, connections and recommendations from people who worked with you
- PortfolioShowing real output you can point to
- graphThe specifics: decisions, scale, trade-offs and outcomes, with your GitHub, portfolio and publications in one place
- Weak spot
- ResumeLittle room for evidence, so claims stay vague
- LinkedIn profileMostly self-written claims with little supporting detail
- PortfolioHard to build when your work is confidential or is not code
- graphNot a social network, so it does not replace LinkedIn's reach
- When it changes
- ResumeWhen you apply for something
- LinkedIn profileNow and then
- PortfolioWhen a project is finished
- graphAs your work happens
| Aspect | Resume | LinkedIn profile | Portfolio | graph |
|---|---|---|---|---|
| The question it answers | Should we interview this person? | Who is this, and who do they know? | What have they made? | What did they actually do, and why did it matter? |
| Who reads it | Recruiters and hiring managers, deciding quickly | Recruiters, peers and your network | Anyone who wants to inspect the work | You first, then anyone you choose to share it with |
| Strongest at | A short summary that can be scanned in seconds | Reach, connections and recommendations from people who worked with you | Showing real output you can point to | The specifics: decisions, scale, trade-offs and outcomes, with your GitHub, portfolio and publications in one place |
| Weak spot | Little room for evidence, so claims stay vague | Mostly self-written claims with little supporting detail | Hard to build when your work is confidential or is not code | Not a social network, so it does not replace LinkedIn's reach |
| When it changes | When you apply for something | Now and then | When a project is finished | As your work happens |
What each is good for, and where it falls short
You will probably keep using all of them. Here is what to use each for.
Resume
Use it forThe document that goes with an application. Short, scannable, tailored to one role.
Watch out forA page leaves no room for reasoning, so lines turn vague. In our analysis of Data Engineer resumes, over 8 in 10 of the improvements quoted were round figures like 30% or 40%, which read as estimates.
See where resumes lose outBeing found by recruiters, staying in touch, and collecting recommendations from people who worked with you.
Watch out forMost of it is self-written, and there is little space for the long version of a project: what went wrong, what you decided, what changed.
Portfolio
Use it forA personal site, GitHub, notebooks or Kaggle. Finished work that anyone can open and inspect.
Watch out forA lot of the best work is private, under an NDA or not code at all. Fewer than 1 in 10 of the Data Engineer resumes we read linked a GitHub profile.
A general chatbot
Use it forTools like ChatGPT and Claude. Good for fixing wording, brainstorming and tidying your resume.
Watch out forIt only knows what you type in. If a line is vague, it makes it sound nicer but not more specific. It will not stop and ask, “how much faster, and compared with what?” the way an interviewer will.
It sits underneath the rest
graph does not replace any of these. It is where the evidence lives, so the rest can be written from it instead of from memory.
You ship a pipeline, fix an incident, make an architecture call. The detail is real, and it is fresh.
You add a quick note. graph asks the follow-up questions a hiring panel would, and keeps your answers next to the moment they belong to.
- A resume tailored to a job description
- An interview prep sheet built from your stories
- One profile that brings your GitHub, portfolio and publications together, public only if you choose
Where it is not the right tool
- graph is not a social network, so it will not replace LinkedIn's reach.
- It is built for Data, AI and Analytics roles and asks domain-specific questions. It is not a general career tool.
- It works best when you add notes as the work happens. It cannot invent detail you never gave it.
See the four steps or where resumes lose out.
Start from your situation
Most people need more than one. Here is what to reach for first.
- You are applying for a job this week
- A resume tailored to that role. graph can generate one from what you have captured.
- You want recruiters to find you
- LinkedIn. Keep it current and keep it honest.
- You have public work to show
- Keep it where it lives, on GitHub or a portfolio. Then bring it all together in one place on your graph profile: GitHub, portfolio, articles, Kaggle and publications, each with the story behind it.
- Your best work is under an NDA
- graph, to keep the story and the reasoning without the confidential detail, then a resume built from it.
- You have an interview coming and cannot recall the details of a project
- graph's interview prep, built from the stories you captured while they were fresh.
- A review, promotion case or job change is coming
- graph, so the evidence is already written down instead of reconstructed from memory.
Make your work impossible to overlook.
Start with your resume. graph shows you what it understood and what is missing.