Resource Hub
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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91 resources
A Substack newsletter on hiring trends and job market conditions written from inside recruiting, with posts on how employers screen and select candidates. Free posts are available to read and subscribe to by email.
A KDnuggets guide by Vinod Chugani that goes round by round through current data science hiring processes, including AI-assisted coding rounds and generative AI evaluation questions, and lists ways candidates can prepare.
Reviews research on wage growth and onboarding performance among workers who change employers. Discusses why hiring teams may assess accomplishments, reasons for moves and adaptability rather than treating short tenure as an automatic warning sign.
ManpowerGroup's quarterly hiring outlook for tech and IT services, based on responses from 4,258 employers in 42 countries collected in July 2026. Available as an online viewer and PDF.
The Guardian’s October 23, 2026 article examines Anthropic’s account of how AI agents have changed its workforce and hiring. Researchers question the report’s methods and whether its company-specific findings establish wider labor-market effects. Anthropic did not respond to the Guardian’s request for comment.
Resume Now's report comparing Bureau of Labor Statistics projected employment growth for 2025–2035 across 70 U.S. occupational groups with employee reviewers' outlook on their employers' futures.
Korn Ferry's Talent Trends 2027 outlook on skills-shifting in the workforce.
Nikhyl Singhal examines changing job-search advice through three leaders’ moves to Runway, Eli Lilly, and Google Search. The publicly readable article discusses hands-on AI experience, leadership skills, and evaluating opportunities at startups and established companies.
Western Governors University's second annual Workforce Decoded survey of more than 3,100 U.S. hiring professionals, examining how AI is changing the skills employers need and how they verify that candidates actually have them.
Anthropic analyzes internal employment, hiring, AI-use, output and survey data alongside employee interviews. Reports changing junior technical hiring and productivity patterns as agent use expands, with human attention becoming a bottleneck; this employer case study is not representative of the whole labor market.
Essay (October 15, 2026) on falling demand for frontend and junior developer roles, citing Djinni job-board data and Indeed Hiring Lab software-posting figures.
Quarterly roundup from TechServe Alliance, the IT and engineering staffing trade association, on the five labor-market signals from Q3 2026 that matter most for tech hiring and staffing.
TestGorilla's 2026 survey of more than 1,000 talent professionals on how recruiting has changed, finding that sourcing candidates is easier while judging who can do the job is harder.
Ratio Institute Working Paper No. 388 (Lodefalk, Löthman, Koch, Engberg) on how generative AI relates to hiring across age groups. Free PDF.
A web tool from Performance-based Hiring ("Moneyball for HR") that estimates the odds a candidate will exceed a job's performance objectives at the one-year mark, using evidence of past performance instead of interview impressions. Includes a sample report.
Free online courses from recruiting-software company Ashby on hiring analytics, recruiting practices and talent trends. A free account is required; much of the material is written for Ashby users.
Article on the added regulatory scrutiny US employers face when hiring foreign workers following layoffs.
Generation USA describes how its training-and-placement model aims to reduce hiring risk and improve efficiency for employers, arguing the global hiring system leaves capable adults overlooked.
eFinancialCareers interview in which Jane Street's CTO explains what the trading firm looks for in engineers.
Why I recommend it: One elite firm's view — its bar is unusually high, so don't treat it as typical.
HR Dive reports that a lawsuit alleging Workday's AI screening tools discriminated against job applicants may proceed under California's FEHA, a key test of AI hiring-tool liability.
Why I recommend it: HR Dive blocked our automated check, so confirm the article opens for you; the case is ongoing, so treat outcomes as unsettled. If you use AI screening in hiring, this case matters.
angld.ai analysis of 20,973 posts on Reddit's r/recruitinghell finding that being ghosted after applying now rivals rejection as job seekers' top complaint.
Why I recommend it: Written by angld.ai, which sells a paid tool for reaching hiring managers directly — the answer to ghosting it points to is its own product. Reddit complaints also skew toward the most frustrated job seekers.
Peter Kuhn and Trevor Osaki survey people on which kinds of hiring and pay discrimination they consider unfair, and why.
Why I recommend it: A working paper based on survey attitudes — it tells you what people think is fair, not what the law allows.
How common fake or dormant job listings are, the survey data behind the estimates, and where proposed ghost-job laws stood as of September 2026.
Why I recommend it: Written for employers, but useful for job seekers: it explains why a listing may never be filled so you can spend your applications wisely.
A duty-by-duty walkthrough of California's automated decisionmaking technology rules — approved 23 September 2025, in effect from 1 January 2026, with ADMT obligations from 1 January 2027 — and where each duty can actually be enforced in a system. Covers pre-use notice, opt-out, human review, appeals and per-decision record keeping. The rules apply when computation replaces human judgment on a significant decision about work, money, housing, education or health.
Why I recommend it: The clearest free explanation I have found of what these rules require, and the section on significant decisions is directly relevant if an employer screens you by machine — you get notice, an opt-out and a route to a human. Read it knowing DeepInspect sells the kind of control it describes, so the framing pushes toward buying a product; the legal dates and duties are checkable against the state agency's own page, which it links.
