CairnCareers vs CareerWing.
CareerWing and CairnCareers both hand you a plan. The difference is who the plan is for and what the clock is. CareerWing counts in days from today. CairnCareers counts in academic terms, because that is the calendar a student actually lives on.
| Feature | CareerWing | CairnCareers |
|---|---|---|
| Built for | Professionals navigating uncertainty, discovering what is next, and staying accountable to a plan, according to its homepage.4 | College students and recent graduates choosing a first path. |
| The plan | A 30/90/365-day plan generated automatically once your matches are ready, with daily missions, XP, badges, and a Career Health Score.4 | A term-by-term roadmap. Each term closes the biggest evidence gap first, sequenced so the earliest work makes the later work easier. See the sample roadmap.3 |
| The coach | Ava, a chat coach available around the clock.4 | A coach that asks one question at a time to turn what you did into a record with a number in it, and never writes the number for you. |
| Where the matches come from | Your profile: strengths, motivations, work style, goals and constraints.4 We did not find a public page naming outside data sources. | O*NET occupational task data, the Eloundou et al. (2024) exposure framework in Science, and METR's* capability trend, every source linked on the methodology page.1 |
| AI exposure | Described as helping you discover future-proof careers.4 We did not find a published method for how that is measured. | A task-weighted 0 to 100 exposure score per path, with pay and growth data kept separate from it so you can see what moved the result.1 |
| One record, many outputs | Missions and progress tracking.4 | One answered prompt raises your coverage, writes a resume bullet, and writes a LinkedIn line at the same time. |
| Price | See careerwing.ai for current plans.4 | Free tier. Pro at US$6 a month. Premium at US$11 a month.2 |
When CareerWing is the better fit
- You are already working and want to change roles on a day-counted timeline rather than a term-counted one.
- Daily missions, points, and a coach you can message at any hour are what keep you moving.
When CairnCareers is the better fit
- You are in school or just out, and your year runs on terms, not on days from today.
- You want to know where a number came from before you put it on a resume or repeat it to a recruiter.
- You want the AI-exposure score built from published, linkable sources rather than a profile match.
Is CareerWing built for college students?
Not primarily. Its homepage describes it as built for professionals navigating uncertainty, discovering what is next, and staying accountable to a plan, and its plan counts in days from today: 30, 90, and 365.4
A student's year does not run on days from today. A 90-day plan started on October 1 ends in late December, over winter break, while the sample roadmap starts internship applications in January.3 A term-by-term plan puts each step in the term it fits: the course at registration, applications when they open, case studies after the summer.
How is the AI-exposure score calculated?
It averages how exposed each task in an occupation is to current AI, weighted by how much of the work each task takes up, and puts the result on a 0 to 100 scale.1 The tasks come from O*NET. Each one gets an exposure value from the Eloundou et al. (2024) framework: 0 if today's AI cannot meaningfully do it, 0.5 if AI can do it with the right tools, and 1.0 if AI can do it on its own.1
A worked example: half of an occupation's work is a task AI can do on its own, a quarter is a task AI can do with tools, and a quarter is a task AI cannot touch. That gives (0.5 x 1.0) + (0.25 x 0.5) + (0.25 x 0) = 0.625, or about 63 out of 100.1
What does a term-by-term plan look like?
Three terms of four months each, with the breaks between them doing their own jobs.3 In the sample roadmap, fall term starts Research Methods to close the largest evidence gap and ships a first case study by December. Spring term applies for an internship in January, presents at a design showcase in March, and accepts an offer in April.3
Summer is the internship itself. Senior fall publishes two case studies from it, asks for referrals, sends applications in November, and interviews in December.3 Every name in the sample is invented; the order is the part that carries over to your plan.
How does CairnCareers match you to a career?
It starts from the career paths you are weighing and matches each one to a standardized occupation in O*NET, the U.S. Department of Labor's occupational database.1 AI does not replace job titles. It changes the tasks inside a job, and standardized occupations are how those tasks are defined.
You see the plain occupation name and how close the match is, while the federal occupation codes stay behind the scenes.1 CareerWing describes its matches as built from your profile: strengths, motivations, work style, goals and constraints.4 The two answer different questions. A profile match asks which work suits you. A task match asks which parts of a given job current AI can already do, which is why two paths with similar titles can score very differently.1
What if you have already graduated?
The sequence works the same. On the sample roadmap, month one starts the day you decide instead of at registration, an online course or workshop stands in for the class pick, and the breaks between terms become catch-up weeks.3
This is where a day-counted plan and a term-counted one come closest, because a graduate's calendar no longer follows a school year. What stays different is the input. CairnCareers still builds the order from the evidence gaps for a target role, so a recent graduate's first month goes to whichever gap is largest for the job they want, and each later month leans on the one before it.3
How does CairnCareers track progress without points or badges?
With coverage: how much of the durable work of your target role you can already back up with something you actually did, out of 100. Finishing a course or a case study does not move it on its own. The evidence page asks for the details first, such as the audience size at a showcase talk, and coverage moves once the prompt is answered.3
Each answered prompt is one record, and that record writes a resume bullet and a LinkedIn line at the same time. In the sample, December ends with a check against a coverage target of 85 out of 100 for the role, and anything still open moves into spring.3 CareerWing uses daily missions, XP, badges, and a Career Health Score.4 If streaks and points are what keep you going, that is a fair reason to pick it.
Why plan by term instead of by day?
Because a student's deadlines are set by terms, not by the date you sign up. Course registration, internship application windows, and recruiting season arrive on the academic calendar whether or not a plan counted toward them.
A term-based plan puts each step where the calendar allows it. On the sample roadmap, Research Methods slots into registration as it comes, internship applications go out in January, summer is the internship, and senior fall is recruiting.3 A day-counted plan can reach the same steps, but it has to be adjusted by hand every time a deadline falls somewhere the count did not expect.
Sources
- CairnCareers methodology page: the three sources behind the score (O*NET, Eloundou et al. 2024 in Science, METR) and the 0 to 100 scale.*
- CairnCareers pricing: Free, Pro at US$6 a month, Premium at US$11 a month, on the pricing section of the homepage.
- CairnCareers sample roadmap: the term-by-term plan, one evidence gap per term.
- CareerWing homepage: Ava, the 30/90/365-day plan, daily missions, XP, badges, and the Career Health Score, as described there on the date checked.
Statements about CareerWing describe its public pages on the date checked and may have changed since, so if something here is out of date, tell us and we will correct it.
* 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/