Career Flux
Career Flux
Find your AI career readiness score — and a 90-day plan to close the gap.
Date: 2026-06-11 Form factor: Web app (single-page, mobile-friendly) Status: Prototype
What it is
Career Flux is a two-minute personal skills assessment that tells workers exactly how AI is reshaping their role, which skills are commanding the biggest salary premiums in their field, and gives them a prioritized 90-day reskilling roadmap. Users select their industry and role, check off the skills they already have, and instantly see an AI Impact Score (0–100), a demand-growth bar chart for every trending skill, and a three-phase learning plan pointing to free and paid resources.
Who it serves
Knowledge workers in software, finance, marketing, operations, healthcare, and design who sense their role is changing but don't know where to start. Specifically: mid-career professionals (5–15 years in) who have solid domain expertise but feel behind on AI tooling, and who don't have time to sift through dozens of LinkedIn Learning courses to figure out what actually moves the needle on salary and job security.
Why it could be profitable
Monetization model: Freemium — free one-time scan, $8/month Premium for a weekly AI Skills Pulse digest (trending skills by role, salary benchmark shifts, new resource drops) plus a resume gap analyzer.
Demand rationale: Workers in AI fluency-required occupations grew 7× in two years (from ~1M in 2023 to ~7M in 2025), and AI-skilled workers now command a 56% wage premium over peers without those skills. Meanwhile 80% of the engineering workforce needs upskilling by 2027 (Gartner), but only 40% of organizations offer hands-on training — leaving individuals to self-direct. There is no dominant consumer brand in the personal AI skills gap space: existing tools like LinkedIn Learning, Coursera, and SkyHive target enterprises and HR buyers, not the individual trying to self-assess on a Sunday afternoon. Career Flux owns that specific moment of anxiety — "am I falling behind?" — and converts it into a clear, actionable plan.
Form factor & scope
A single-page web app (HTML/CSS/JS, no build step). The prototype demonstrates the complete three-step flow — role selection → skills self-assessment → results dashboard — across six industries and thirteen roles, with a 36-skill catalog covering demand growth data and learning resources.
How to run it
- Serve the folder with a local HTTP server — e.g.
npx serve .orpython3 -m http.server 8080— becausescript.jsusesfetchto loadsample-data.json. - Open
http://localhost:8080(or whichever port) in any modern browser. - Select an industry, then a role, click Start My Assessment, check off your skills, and click See My Results.
Note: The app will display an error if opened directly as a
file://URL due to browser CORS restrictions on localfetchcalls.
What's in this prototype
- Welcome screen with three live market-data stat chips and an industry/role selector
- Skills checklist showing all trending and durable skills for the chosen role, sorted by demand-growth percentage, with a live checkbox to mark what you already have
- AI Impact Score gauge — animated semicircular dial (0–100) color-coded green/amber/red with a role-specific narrative
- Skills Gap Analysis — horizontal demand-growth bars for every trending skill, green-checked if you have it, blue if it's a gap
- Readiness Summary — three progress bars: AI/Trending Skills, Durable/Safe Skills, Overall Readiness
- 90-Day Reskilling Plan — top three skill gaps mapped to 30-day phases with linked free and paid learning resources
- Restart flow and Premium upsell CTA
Roadmap
- Resume upload + automated gap detection against a target job description
- Weekly email digest: AI Skills Pulse (trending skills, salary data, new resources)
- Salary impact simulator: "adding Skill X could raise your market rate by ~$Y"
- Team readiness dashboard for managers (B2B tier)
- Skill decay alerts: notify users when a skill they claimed drops in market demand
Sources
- https://gloat.com/blog/ai-skills-demand/ — AI fluency worker growth (7×), wage premium (56%), adoption data
- https://www.digitalapplied.com/blog/ai-upskilling-workforce-guide-stay-relevant-2026 — 80% workforce upskilling need by 2027; 40% org training gap
Requirements
Career Flux — Requirements
Goals
- Give any knowledge worker a clear, quantified picture of how AI is transforming their specific role within two minutes.
- Surface the skills commanding the highest demand growth in their field so they know exactly what to learn next.
- Produce a concrete, time-boxed (90-day) learning plan rather than an abstract list of recommendations.
- Monetize the daily anxiety around AI-driven career displacement with a low-friction freemium entry point.
Primary user
Mid-career knowledge worker (5–15 years experience) in software, finance, marketing, operations, healthcare, or design. Uses the app on a weekday evening or weekend morning when career anxiety peaks. Job-to-be-done: "Tell me honestly where I stand and give me a specific plan I can start this week."
Functional requirements
- FR1: User selects their industry from a predefined list of at least 6 industries.
- FR2: Upon industry selection, a role dropdown populates with relevant roles for that industry.
- FR3: After selecting a role, user proceeds to a skills self-assessment checklist showing all trending and durable skills for that role.
- FR4: Each skill in the checklist displays its label, category, and demand-growth percentage.
- FR5: User checks skills they currently possess; the UI provides visual confirmation (checked state, color change) for each selected item.
- FR6: Results page displays an AI Impact Score (0–100) as an animated gauge with a role-specific narrative explaining the score.
- FR7: Results page shows a skills gap analysis: all trending skills for the role listed by demand growth, with visual bars and a checkmark/growth indicator showing which skills the user has vs. needs.
- FR8: Results page shows a readiness summary with three progress bars: AI/Trending Skills coverage, Durable/Safe Skills coverage, and Overall Readiness.
- FR9: Results page generates a 90-day reskilling plan: the top three skills the user is missing, each assigned to a 30-day phase with a description and two linked learning resources.
- FR10: User can navigate back from any step without losing their selections.
- FR11: User can restart the full assessment from the results page.
- FR12: Prototype runs without a build step; all data loaded from a local JSON file via fetch.
- FR13: All third-party content (if any) is loaded over HTTPS from public CDNs or linked to external URLs in resource cards.
User stories
- As a software engineer, I want to see which AI skills are trending in my field so that I can prioritize what to learn without spending hours researching job boards.
- As a mid-career marketer, I want an honest score for how much AI is disrupting my role so that I can have an informed conversation with my manager about upskilling.
- As a finance professional, I want a 30-60-90 day learning plan for my top skill gaps so that I can act on the assessment immediately rather than file it away.
- As a healthcare administrator, I want to understand which of my existing skills are "durable" (AI-safe) so that I can lean into them while building new ones.
- As a non-technical user, I want clear labels and plain-language descriptions for each skill so that I don't feel lost by jargon.
- As a returning user, I want to re-run the assessment for a different role so that I can explore a potential career pivot.
- As a product manager, I want to see the demand-growth percentage for each skill so that I can justify my learning investment with data.
Non-functional requirements
- Performance: App must be fully interactive within 1 second of page load on a standard broadband connection.
- Accessibility: All interactive controls must be keyboard-navigable; color is not the sole visual indicator (icons + labels used alongside color).
- Mobile-friendliness: Layout must be fully functional on screens ≥ 360px wide using responsive flex/grid.
- Privacy: No user data is collected, stored, or transmitted. All computation happens client-side.
- Self-containment: No API keys, authentication tokens, or environment variables required. No server-side code.
- Browser support: Works in any Chromium, Firefox, or WebKit browser released after 2023.
Out of scope (for the prototype)
- User accounts, authentication, or saved assessments
- Real-time job market API integration (BLS, LinkedIn, Indeed)
- Resume upload and automated skill extraction
- Email capture or actual subscription flow
- Salary data or compensation benchmarks
- Manager / team dashboard
- Mobile app or PWA shell
Open questions
- Should the AI Impact Score be framed as "automation risk" (threat-first) or "opportunity score" (growth-first)? Prototype uses opportunity framing; test which drives more conversions.
- How often should skill demand data be refreshed? Weekly pull from job postings APIs seems right for production.
- Is the 90-day plan length right, or should users be able to choose 30-day vs. 6-month horizons?
- What is the optimal free-to-paid conversion moment — end of assessment, or first time a user returns to re-check their score?
