THIS IS A SAMPLE DASHBOARD
Premium dashboard Where you stand, Maya. Junior at Northlight University, Psychology major, aiming at UX Researcher. Everything below moves when you add one more real accomplishment.
Sample dashboard. Every name and number here is invented so you can see how it works.
Coverage The proof you are building The share of the durable work of a UX Researcher you can already evidence with something you actually did.
Up 12 this term What AI already does
Moderate. So aim your energy at the half it cannot touch.
Built only from O*NET, Eloundou, and METR*
Readiness
Coverage after one private clean-up flag you set. Nobody else sees this number.
Clean-up never touches the AI-exposure number.
Where to aim
The durable core of the role, and the parts AI already handles Lean in AI cannot do this Interview real users and hear the need under the ask
Strong evidence on file.
Move a room that disagrees toward a decision
Partial evidence so far.
Frame a fuzzy problem into the right questions
Highest value here. One more example would settle it.
Own the call when the data is incomplete
Nothing on file yet. The gap worth closing first.
Let AI carry it Already automated Drafting survey questions and screeners
Use AI here and say so. Employers now expect it.
Summarizing transcripts and notes
Fast with AI. Show that you direct it.
First-pass personas and report drafts
A starting point, never the judgment.
Usability heuristic checklists
Commodity work.
Open the dashboard
Nine areas that need some work, and what each one is holding right now Evidence
Answer a prompt, watch coverage move, get a resume bullet and a LinkedIn line from the same record.
6 on file 5 open
Portfolio
Store the work itself. Case studies, reports, prototypes, and decks that back up a claim.
4 saved 2 slots
Resume
One profile, kept current. Edit a win once and the resume rewrites itself.
Updated 3 days ago
LinkedIn
Headline, About, and experience bullets written to paste straight in. Preview before you do.
In step Copy ready
Network
The loose ties you already have, ranked, with the exact message to send each one.
2 to send 1 to find
Interview
The answer to the question every hiring manager is quietly asking about this role.
Drafted From 6 wins
Careers
Pay and growth beside AI exposure, adjusted for where you live and how you would work.
4 compared Context only
Roadmap
Three terms to graduation, sequenced so the biggest gaps close first.
7 steps 3 this term
Clean-up
The private tidy-up path. Nothing stored, nothing described, never sent to any model.
1 flag Private
Do these three next The shortest route from 68 to 74 Add one example of owning a call with incomplete data +4
Upload the onboarding case study to your portfolio +2
Send the message waiting for Priya Nadar Network
Method and sources O*NET OnLine, occupational task data Eloundou et al. (2024), Science 384:1306-1308 METR, long-run time-horizon trend * The published AI-exposure number is built only from O*NET task data, Eloundou et al., and METR*
* This projection uses METR's established long-run time-horizon trend, not the faster 2026 estimates. Those newer figures come from a task suite near saturation, carry very wide confidence intervals, and measure software tasks specifically, so extrapolating them across all occupations is not yet reliable. See MIT Technology Review, "This is the most misunderstood graph in AI," February 5, 2026, https://www.technologyreview.com/2026/02/05/1132254/this-is-the-most-misunderstood-graph-in-ai/
This dashboard is a sample. Maya Rivera, Northlight University, Northbeam, Lumen, and Verdi Labs are invented, and every figure on this page is sample data, not a real result.
