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3505 hand-picked resources for students, job seekers, career changers, founders, and AI learners — 100% free to browse with no account required.
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57 resources
CNBC Make It examines New York City's technology employment and its appeal to workers, reporting that the city now has more tech workers than San Francisco. The November 9 feature provides regional labor-market context rather than a list of currently open jobs.
CNBC analysis of Bureau of Labor Statistics data finds average monthly long-term unemployment above 1.8 million in 2026, up about 45% from 2019 and 55% from 2023. The article examines financial, emotional and family effects that can continue after people return to work.
Why I recommend it: Long-term unemployment means joblessness lasting at least 27 weeks. The figures are CNBC's analysis of BLS data published June 4, 2026.
Challenger reports 43,994 announced U.S. job cuts in October 2026 and 470,400 seasonal hiring plans through October, a 26% increase from the prior-year period. The release breaks down announced cuts by industry, geography and stated reason, including employer-cited AI.
Why I recommend it: Counts are employer-announced job cuts and hiring plans, not realized employment changes. AI attribution reflects employers' stated reasons.
Stanford's August 2026 Canaries update describes an employment shortfall among young workers in highly AI-exposed occupations, primarily through reduced hiring. The authors stress these are descriptive patterns, not proof that AI caused the gap.
New York Fed economists Elizabeth B. Li, Giorgio Topa and Jacob P. Weber compare three new LinkedIn measures of how hard it is for employers to find workers against government job-openings data, and test how well they track wage growth.
CNBC reports that initial U.S. unemployment claims were 194,000 for the week ending October 17, 2026. The October 22 article describes low layoffs alongside weak hiring and discusses what these indicators do and do not show about the labor market.
Article by Laetitia Vitaud in Fast Company examining the push for more "masculine energy" in corporate culture, drawing on Women in the Workplace report data, 2025 labor market statistics, and the team-supporting work that goes unrewarded. Published October 7, 2026.
ICIMS Insights September 2026 Workforce Report, drawing on data from more than 3.1 million users and 691 million candidate profiles, finding job openings outpacing hires for a third straight month and a widening gap between employer-desired AI skills and how job seekers are acquiring them.
Partnership for New York City report (October 2, 2026) on how AI is changing the city's economy: AI companies leased more than 2.2 million square feet of office space in the first half of 2026, NYC AI startups raised a record $16.7 billion in venture capital last year, yet entry-level hiring is declining in the white-collar industries most exposed to AI, and the report warns that the city's AI strategy does not yet address eroding entry-level pathways in finance, information and professional services.
The Bureau of Labor Statistics page listing Current Employment Statistics news releases, including the monthly Employment Situation report on U.S. nonfarm payroll jobs, hours and earnings. (Described from the page title; the page blocks automated reading.)
AARP's Longevity Economy Outlook series measures how Americans 50 and older contribute to the U.S. economy, including their spending, jobs supported, tax payments, and unpaid caregiving and charitable contributions. The reports include projections through 2060 and key findings for employers and policymakers.
Why I recommend it: Useful for seeing the scale of older workers and consumers in the labor market — a counterweight to coverage that treats workers over 50 as an afterthought.
An HR guide to planning for skills gaps and talent shortages before they hit, covering whether to build, buy, or borrow talent. It cites ManpowerGroup data that 72% of employers still struggle to fill roles, and contrasts industries with shortages against job seekers sending hundreds of applications. A guest contribution from Global Verification Network, updated April 7, 2026.
Why I recommend it: A practical employer-side view of the skills-gap problem — pairs well with resources written for job seekers navigating the same market.
McKinsey Global Institute report (September 2026) on how AI, automation and structural trends are reshaping US jobs, examining which skills are growing or declining in demand and the pathways workers take into future jobs.
Stanford Digital Economy Lab paper using payroll data to track employment changes for early-career workers in jobs most exposed to AI.
Stanford Digital Economy Lab follow-up examining whether interest rates and timing, rather than AI, explain employment shifts among young workers.
U.S. Bureau of Labor Statistics monthly data on job openings, hires, quits and layoffs. The BLS site blocked the automated check, so this description is based on the page title.
Quartz report on the white-collar pay correction: employers stopped raising pay years ago, and economists trace the freeze to the pandemic hiring boom companies are now correcting.
Joseph Politano examines U.S. job losses across media, film and the arts and asks how much of the change can be attributed to generative AI. Free to read.
NYCEDC's monthly data briefing on the city's economy as of September 24, 2026: private-sector employment down 12,900 in August, unemployment at 4.8% after six straight monthly declines, labor force participation at 62.1%, median asking rent near $4,000, plus office visitation, tourism, and transit numbers.
Why I recommend it: The one-page-per-topic format makes this the fastest way to sound current on the NYC economy in an interview or a client meeting. Read the jobs and small-business pages; skip the real-estate detail unless it touches your field. It is a city agency's own read of its own economy, so pair it with the raw BLS numbers if you need the unspun version.
Dewey Data review of mixed research on AI and jobs; job-posting data suggests firms are changing what they hire for more than how much.
Why I recommend it: Written by a data vendor that sells datasets used in this research. Check the original studies.
A roundup of 2026 hiring data — job openings, applications per role, skills-based hiring and time-to-hire — with the sources behind each figure.
Why I recommend it: Published by a university that sells degrees, so read the education-related claims with that in mind; check the linked original sources before quoting a number.
Stanford Digital Economy Lab working paper by Bharat Chandar and Bouke Klein Teeselink, separating what happens to jobs after a firm adopts generative AI into a company-wide productivity effect and changes in what specific kinds of workers are asked to do.
Why I recommend it: Free, with the full PDF on the page. It is a working paper dated 21 September 2026, meaning it has not been through peer review yet, so read it as early evidence. Useful because it does not answer 'will AI take jobs' — it asks which workers get asked to do more and which get asked to do less.
Hosseinioun and colleagues use US survey and resume data to show skills sit in a nested order — some can only be learned once others are in place — and link that structure to wage gaps and long-term wage penalties after job loss.
Why I recommend it: Open access, so the full paper is free — no library login needed. The useful takeaway for career work: skill order matters. Learning a foundation skill first opens more later moves than stacking another surface skill, and the paper shows why some people recover from a layoff faster than others.
Market analysis of education technology and the higher-education business: online program managers, learning platforms, enrollment trends, microcredentials, and the labor-market outcomes of degrees. Written by Phil Hill, a long-standing independent analyst of the sector.
Why I recommend it: Freemium: a good share of posts are free to read and there is a paid tier for the deeper market analysis. Useful if you are weighing whether a bootcamp, online degree or microcredential is worth the money — this is one of the few places that reports on the finances behind those programs rather than their marketing.
