Resource Hub
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91 resources
USA Today reports experts saying the traditional career path is fading as workers embrace AI and portfolio careers for more stability.
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.
SHRM's annual look at the challenges employers and HR teams expect in 2026, including workload pressure, skills gaps and shifting employee expectations.
Allwork.Space article on how artificial intelligence is changing corporate real estate planning and flexible workspace decisions. Free to read.
A Dreamforce 2026 conversation in which Salesforce Chief Platform & Engineering Officer Rohan Kumar sits down with Social Capital founder Chamath Palihapitiya on the future of tech, the true ROI of enterprise AI, and scaling the AI era. Free to stream on Salesforce+ with a free account.
Owl Labs' tenth annual survey report on how US employees work across office, hybrid, and remote arrangements, including attitudes toward return-to-office policies and workplace technology. Owl Labs sells video-conferencing hardware, so it has a commercial interest in hybrid work.
An Amazon company-news post in which CEO Andy Jassy outlines how Amazon is using generative AI across its businesses and what he expects it to mean for the company's workforce. Published by Amazon about its own plans.
JFF's explainer on three-year bachelor's degree programs: how schools are redesigning degrees around fewer credits and clearer career outcomes, which accreditors have approved them, and what the model could mean for cost and time-to-degree.
Why I recommend it: Worth reading before you or someone you advise commits to a four-year price tag. JFF is a workforce nonprofit with its own agenda around shorter pathways, so treat the optimism as advocacy — but the accreditation facts and school examples check out.
A Forbes Business Development Council column (Sept 15, 2026) arguing that the habit of continuous learning matters more for AI-era careers than any single technical skill.
Why I recommend it: Forbes Councils columns are written by paying council members, not Forbes journalists, so treat this as one practitioner's opinion. Forbes may limit free articles per month.
Allwork.Space roundup of business leaders predicting AI will shorten the workweek.
Why I recommend it: Predictions, not plans. None of these companies has announced a three-day week.
Pew Research Center short read, 18 August 2026, on a survey of US adults conducted 22-28 June 2026. 52% now say they are more concerned than excited about AI in daily life, up from 37% in 2021. Among adults aged 18-29, 55% are more concerned than excited and 11% more excited than concerned, and 73% think AI will mean fewer US jobs over the next 20 years, up from 61% in 2024.
Why I recommend it: Useful when a client says the worry is just in their head — it is not, and the numbers are free to download as a spreadsheet. Read it as what people expect, not as what has happened to employment: it measures opinion, not job counts.
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.
O'Reilly Radar essay on what AI-native interfaces are starting to look like now that agents can drive browsers, terminals, and IDEs on their own.
Why I recommend it: Free to read. Good context if you are trying to picture what "AI in your workflow" actually means beyond a chat box.
Chapter 3 of Pew's April 2025 report comparing US adults with AI experts on what AI will do over the next two decades. 56% of the experts surveyed expect AI's impact on the US to be positive, against 17% of the public; 35% of adults expect a negative impact, against 15% of experts. The gap is widest on work and money: 73% of experts think AI will positively affect how people do their jobs versus 23% of the public, and 69% versus 21% on the economy, with a 40-point gap on medical care (84% versus 44%). Experts and the public broadly agree on the risks to democracy and journalism: only 11% of experts and 9% of the public expect AI to help elections, while 61% of experts and 50% of the public expect harm. Gender splits are large among experts — 63% of male experts predict a positive impact versus 36% of female experts. Free to read, with methodology and appendix tables.
Why I recommend it: Use this when someone tells you 'the experts say AI will be fine at work' — the numbers show experts and the public are describing two different futures, and the widest gap of all is about jobs. Read it with two limits in mind: the fieldwork was in 2024 and published 3 April 2025, so it predates a lot of what has happened since, and Pew's 'AI experts' are people who published or presented at AI conferences, many of them employed by companies building AI, which is exactly the group the optimism gap belongs to.
Allwork.Space's write-up of a four-day Reuters/Ipsos poll that closed on Sunday 20 September 2026: 73% of Americans worry AI companies have not gone far enough to prevent serious harm, 55% favour slowing AI development, 39% say AI is having a negative effect on society (up from 36% the month before, the highest since Reuters/Ipsos began asking in March), and only 11% call it positive. Most respondents said federal officials, not the companies, should set safety standards. Free to read, no paywall.
Why I recommend it: Useful when you need a number for how the public actually feels about AI at work rather than how vendors say it feels. Two honest limits: this is Allwork.Space reporting a Reuters/Ipsos poll, so read the original poll before quoting a figure in writing, and a poll measures opinion, not job losses — it tells you nothing about how many roles AI has actually replaced.
Darrell M. West argues that AI agents and robots in the workplace will reshape jobs, HR functions and the social contract with workers. Free to read.
From the site: Darrell M. West explains how AI agents and robots are reshaping jobs, HR departments, and society's social contract with workers.
Why I recommend it: A useful piece for thinking about how AI changes the job itself, not just whether the job exists. It is an argument, not data.
A free daily publication covering the future of work: hybrid and remote policy, return-to-office mandates, flexible workspace and coworking, workplace technology and AI, and the employment law and labour trends behind them. Articles read in full with no subscription and no paywall.
Why I recommend it: Read this when you want to know what employers are actually doing about remote and hybrid work before you negotiate for it, or when you are weighing an offer that calls itself flexible. It is written for the workspace industry, so some coverage is trade news about office operators rather than advice for you; take the policy reporting and skip the property pieces.
Interdisciplinary Stanford research institute studying how digital technology and AI change work, productivity and shared prosperity, with public papers and data.
From the site: The Stanford Digital Economy Lab is an interdisciplinary research institute shaping a future where technology drives human well-being and shared prosperity.
Why I recommend it: Free to read. Useful when you want measured research on AI and jobs instead of headline claims — check the publication date on each paper, the field is moving fast.
IEEE Spectrum article on how AI is shifting entry-level engineering work toward higher-order thinking, review and collaboration skills, and what recent graduates can do about it.
From the site: How can recent grads navigate a job market transformed by AI? Learn how to make AI work for you, not against you.
Why I recommend it: Free to read on IEEE Spectrum. Practical if you are early-career: it describes what junior work is turning into rather than predicting job counts.
A DAIR Institute project for unions, labor organizations and worker-organizers dealing with AI and automation at work: case studies, primers and a resource library on worker-led oversight of new technology.
From the site: Research and case studies.
Why I recommend it: Free. Written from an explicitly pro-worker position, which it states openly — useful if you want the labor perspective on workplace AI rather than the vendor one.
TED talks from the author of AI Superpowers on how AI changes work and how China and the United States differ in building it.
From the site: Kai-Fu Lee has spent more than three decades at the cutting edge of artificial intelligence research, development and investment both in the US and China.
Why I recommend it: Free to watch, no account. His point about which jobs AI takes first is more specific than most, which makes it easier to test against your own work.
MIT research group studying how digital technology and AI change work, wages and productivity, with published papers and reports.
From the site: The MIT Initiative on the Digital Economy (IDE) explores how people and businesses will work, interact, and prosper in the digital era.
Why I recommend it: This is measurement rather than prediction, which is rare in this subject. Go here when you want numbers on automation instead of opinions about it.
Free library of articles, reports and recordings from Singularity on emerging technology and business change.
From the site: Explore our comprehensive resources, including insightful videos, articles, guides and reports designed to foster an innovation mindset and leverage exponential technology in your organization. Dive into Singularity insights today to drive growth and thrive in the future.
Why I recommend it: The free resources are free to read; the courses behind them are not. Stick to this page unless you want to be sold a program.
Site of the XPRIZE and Singularity founder: newsletters, podcasts and talks on exponential technology and longevity.
From the site: Founder of XPRIZE and pioneer in exponential technologies. Building a world of Abundance through innovation, longevity, and breakthrough ventures.
Why I recommend it: Relentlessly optimistic by design — he is selling a worldview as well as describing one. Read for the trends he spots, discount the certainty.
Free global research on jobs, skills and technology — including the Future of Jobs reports that most workforce coverage is based on.
Why I recommend it: Go to the source. The Future of Jobs report is free and is what half the "jobs of the future" headlines are quoting.
Free public documentation explaining how an autonomous AI software engineer plans, runs and reviews coding work, including its limits and where human review is required.
From the site: Devin is the AI software engineer, built to help ambitious engineering teams crush their backlogs.
Why I recommend it: The product costs money but the docs are free — read them to understand what "AI engineer" tools actually do and do not do before anyone tells you your job is gone.
Ed Elson's Simply Put essay on how AI, cost and weakening returns on a degree are reshaping education and the entry-level job market.
Why I recommend it: Useful context if you are deciding whether more school is the answer. It argues the credential is worth less than the proof of work.
A free newsletter briefing on AI developments from a pro-human standpoint, covering labor, safety, policy and the campaigns pushing back on automation-first decisions.
Why I recommend it: A steady weekly read if you want the human-impact side of AI news rather than product launches.
Noema Magazine essay on how generative AI is reshaping creative work and value — what an abundance of output does to originality, pay and the meaning of being a creative professional.
Why I recommend it: If you work in a creative field, read this before you decide how to position AI in your own pitch.
The Argument essay arguing that much of the current AI debate misreads the problem: delegating decisions is the intended feature, not an accident, and that reframing should change how we govern it.
Why I recommend it: Read this alongside the optimistic AI takes — holding both views is what makes you sound credible on the topic.
A free twenty-hour introduction to artificial intelligence for high school students, no coding experience required, taught through hands-on projects in areas students already care about.
Why I recommend it: free and built for students who were never handed AI access. If you know a high schooler, send them the application list.
Job market data drawn from employer career sites since 2007 — 350+ million postings used for hiring-trend research, competitive analysis, and investment research.
Why I recommend it: Not a job board — it is where the hiring trend numbers come from. Handy when you want evidence about a field instead of vibes.
Executive Speakers Bureau on choosing a speaker for an exhausted team facing constant change — what actually lands with fatigued audiences and what makes burnout worse.
Why I recommend it: Useful from both sides — if you book speakers, and if you speak. The read on what a tired room can actually absorb applies to any presentation you give.
Partnership on AI's open library of guidance, frameworks, and case studies on responsible AI: synthetic media, labor and the economy, AI safety, fairness, and inclusive AI development.
Why I recommend it: When you need a credible source instead of a hot take, cite these. The labor and economy work is the most useful set for career conversations about automation.
Application to join UC Berkeley CITRIS's Tech Policy Working Group: research lab-style weekly meetings, lightning talks, skill-building workshops, and an end-of-semester showcase for students working on a technology policy problem. Applications close 11:59 PM Friday, September 18, 2026.
Why I recommend it: No policy coursework required, and the deadline is September 18. Built for Berkeley students, but they invite others to email — worth one message if you want real policy research on your resume.
Free ebook on building, monitoring, and troubleshooting AI agents in production: what to instrument, where agents fail, and the practices teams use to keep them reliable.
Why I recommend it: Useful even if you never build an agent yourself — it shows what serious teams actually worry about, which is good language to have in an interview about AI work.
Anthropic's free learning hub for Claude: structured courses with video lessons and quizzes covering Claude.ai, Claude Code, Cowork, the API, and MCP, with completion badges.
Why I recommend it: A free, name-brand AI credential path. The Claude 101 course alone gives you something concrete to put under "skills" instead of vaguely claiming AI experience.
A two-page printable worksheet from Pilyoung Kim, Ph.D. for setting deliberate terms with AI: comparing warm, sycophantic, and machine-like responses, setting your own tone dials, turning them into a reusable custom-instructions prompt, deciding what goes to AI versus a person, and guarding your judgment against flattery.
Why I recommend it: Print it and actually fill it in. Section 5 — writing your own view down before you ask AI — is the single habit that keeps these tools from quietly making your decisions for you.
Created by Pilyoung Kim, Ph.D.
An open-source personal AI assistant, run on your own device, that connects to chat apps like WhatsApp, Telegram, Slack, and Teams to handle email, calendars, and everyday tasks.
Why I recommend it: Appealing if you want an assistant that runs on your own machine instead of a vendor's cloud. It is developer-flavored to install, so budget an hour and read the security notes first.
A Liberty Street Economics post from the New York Fed arguing that, so far, AI adoption is being used to change how work is done rather than to reduce headcount, based on regional business survey data.
Why I recommend it: A useful counterweight to AI job-loss headlines; helpful for understanding how employers are actually deploying the technology right now.
A Center for an Urban Future report on how AI is reshaping entry-level tech hiring in New York City and what city leaders, educators, and employers can do to rebuild on-ramps for low-income New Yorkers.
Why I recommend it: Valuable context if you are entering tech in NYC or advising students and early-career talent on which pathways still lead to good first jobs.
A September 2026 working paper by Brian Jabarian (Carnegie Mellon) and Luca Henkel (Erasmus Rotterdam) reporting a field experiment with 70,000 real applicants randomly assigned to be interviewed by a human recruiter or an AI voice agent. Applicants interviewed by AI were 12% more likely to receive an offer, with higher job starts and retention and no drop in on-the-job productivity. Transcript analysis traces the gain to more structured, consistent interviews that still adapt to each applicant.
Why I recommend it: If you have been told AI interviews are stacked against you, this is the largest piece of real evidence so far and it points the other way: consistent, structured questions helped candidates more than a tired recruiter on their eleventh call did. Prepare for them like any structured interview, with clear, specific answers.
Created by Brian Jabarian and Luca Henkel
Neurodiversity employment network that matches autistic, ADHD, and dyslexic candidates with employers seeking neurodivergent talent in software, UX, and data roles.
Why I recommend it: Built by neurodivergent founders. The matching process is designed around strengths rather than interview performance.
Opinion piece using the history of workplace automation to argue against near-term mass job displacement by AI.
Why I recommend it: Useful counterweight if the headlines have you panicking. Read it alongside the more pessimistic forecasts.
Economic policy organization researching corporate power, prices, and worker outcomes.
Why I recommend it: Their work on corporate power explains a lot about the labor market job seekers are facing.
Think tank publishing research on economic policy, labor markets, and corporate power.
A free calculator estimating the true cost of hiring an employee in a given country, including taxes, benefits and statutory contributions.
Why I recommend it: Useful in both directions: founders get a real number before their first hire, and candidates get a sense of what an employer actually pays beyond salary.
A vendor resource explaining the "software factory" idea — how engineering teams are restructuring workflows around AI coding agents, and what changes in review, testing, and ownership.
Why I recommend it: Read it knowing it comes from a company selling the tooling. Still worth your time if you write code for a living, because the workflow shifts it describes are already showing up in job descriptions.
An essay weighing the argument that AI adoption could push unemployment into double digits, against the labor data we actually have so far.
Why I recommend it: I collect both the alarmed and the skeptical takes on AI and jobs on purpose. Read this next to the Census and Brookings data in this collection and form your own view rather than borrowing a headline.
A Brookings analysis of how traditional labor market data is being challenged and reshaped by the frontier economy.
Why I recommend it: Labor market data is shifting fast. This Brookings piece helps you understand what is really happening beneath the headlines.
A research paper describing a software library whose repository holds almost no code: plain-language design documents are the durable artifact, and AI coding agents regenerate the implementation from those docs on every update.
Why I recommend it: The takeaway for non-engineers is bigger than the paper: clear written thinking is becoming the valuable skill, and the code is what gets generated from it.
Research exploring possible economic futures as AI capability advances, including labor market effects and policy questions.
Why I recommend it: Scenario planning is a career skill, not just a policy exercise. Read it and ask which future your current job depends on.
Survey data on how US workers are using AI, what they fear about it, and how confidence differs across roles and generations.
Why I recommend it: I use survey data like this to sanity check my own assumptions. If you feel behind on AI, the numbers may reassure you that most people are too.
Curated open library mapping the organizations, data systems, and policies connecting education, credentials, and employment.
Why I recommend it: This is the map behind the map: who funds and shapes hiring pipelines. Useful if you work in workforce development or want to.
An essay on how AI exposes the cultural debt embedded in org charts, leadership habits, and unexamined processes.
Why I recommend it: This piece nails why AI adoption is less a technology problem and more a culture-and-power problem. Essential reading for anyone leading a team through change.
A nonprofit research institute that translates labor-market data into insights about skills, mobility, and the future of work.
Why I recommend it: Burning Glass turns labor-market data into actionable insight about which skills are in demand and who is getting left behind. I cite their research often.
Economist Noah Smith's newsletter covering labor markets, technology, industrial policy, and the economics behind AI hype cycles.
Why I recommend it: One of the few writers I trust to check the numbers before drawing a conclusion. Worth a standing subscription if you follow the economy at all.
Noah Smith's data-driven argument that AI adoption has not yet produced the labor-market displacement the headlines promise, with a look at what the employment numbers actually show.
Why I recommend it: Read this before you panic about your field disappearing. It is the most level-headed counterweight I have found to the "AI took the jobs" narrative.
A federal, downloadable PDF negotiation guide developed for the DOL's Transition Employment Assistance for Military Spouses (TEAMS) program, broadly applicable beyond its original military-spouse audience.
Why I recommend it: Written for military spouses, but the scripts and framing work for anyone re-entering the workforce or switching careers. Download it before your next offer conversation.
Not-for-profit social enterprise empowering men of all ages and backgrounds to improve employment outcomes through image presentation and career support.
Why I recommend it: The male equivalent of Dress for Success. Great referral for men re-entering the workforce or preparing for interviews without a professional wardrobe.
Harvard Ash Center essay arguing that generative AI adoption has been driven more by vendor hype and institutional pressure than measured results, with a look at what happens as expectations reset.
Why I recommend it: Useful counterweight when your employer says AI will replace your role next quarter. Ask what evidence they are working from.
OpenAI's announcement of GPT-6 Astra, its most capable model, with reported results on computer use, browsing, software engineering, cybersecurity, and professional work.
Why I recommend it: Read the capability list as a job-task list. Whatever a model does well this year reshapes entry-level work the next.
New York City's citywide racial equity plan, laying out agency commitments, hiring and contracting goals, and measurable targets for closing economic and employment gaps.
Why I recommend it: Read the workforce and procurement sections. City equity plans often name specific programs and set-asides you can apply to directly.
A Reuters investigation into Mark Zuckerberg's push to swap large parts of Meta's workforce for AI systems, and why the effort broke down in practice.
Why I recommend it: Read this before you panic about AI taking your job. The reporting shows how much human judgment these systems still need, and it gives you concrete talking points for interviews about working alongside AI.
The state labor department's full library of free New Jersey labor market publications: economic outlooks, employment and industry reports, emerging occupations, business employment dynamics, and monthly labor market updates.
Why I recommend it: Details: Free, current, and specific to New Jersey and the surrounding region. Use it to name real industries and wage ranges in interviews and business plans instead of guessing.
NCDA on how government relations connects frontline practitioner experience to policy on education, employment, and workforce access.
Why I recommend it: Details: if you do this work, your day-to-day observations are policy evidence — this explains where to send them.
Glassdoor research on worker attitudes toward AI in 2026 — covering adoption, concerns, and what employees expect from employers.
Why I recommend it: A useful snapshot of public sentiment around AI at work. Helpful for coaching conversations about which skills matter and how to talk about AI on the job.
Official NJ Department of Labor data hub: industry and occupational employment projections, wages, and county-level labor statistics.
Why I recommend it: Before you commit to a training program, check the projections and wage data for that occupation in your state. This is the free source that tells you if the demand is real.
Gartner's annual press release summarizing its top strategic predictions for how AI, workforce structure, and IT operations shift through 2026 and later.
Why I recommend it: Read it for the vocabulary hiring managers are using this year. Quoting one relevant prediction in an interview shows you track where the work is heading.
One hub linking every location-based finder: workforce development boards, community colleges, unemployment benefits, apprenticeship offices, Job Corps centers, reentry programs, older worker programs, Native American programs, refugee assistance, farmworker jobs, and youth programs.
Why I recommend it: If you are not sure which program fits your situation, start here — nearly every population-specific finder lives on this one page.
Workforce programs addressing job displacement in low-income and Black communities, including reentry-focused employment partnerships delivered through local Urban League affiliates.
Why I recommend it: Find your local affiliate — programming and hiring partners differ a lot city to city.
New York City Employment and Training Coalition open letter urging the Economic Development Corporation to invest in workforce development alongside job creation.
Why I recommend it: Read this if you want to understand how workforce funding decisions actually get made — and who is arguing for job seekers at the table.
Free employment support, training, and job placement services for adults receiving Social Security disability benefits.
Why I recommend it: Free services and protections that let you try work without immediately losing benefits. Pair it with your state vocational rehabilitation agency.
VA program providing training, education, and employment support for veterans with service-connected disabilities.
Why I recommend it: Chapter 31 can fund a full retraining plan. Worth an eligibility check even if you think you will not qualify.
Career counseling, retraining, and employment support for veterans and service members.
Why I recommend it: Start here if you are a veteran or transitioning service member. It connects you to funded retraining, not just advice.
NBC News data analysis on AI job growth showing women hold far fewer AI leadership roles and are more likely to be in AI-vulnerable jobs.
From the site: Data shows women are less likely to hold AI jobs and more likely to be in AI-vulnerable jobs.
Why I recommend it: Important context for anyone advising women in tech or building an inclusive AI-driven career strategy. Use the data to advocate for equitable training and access.
Futurist and author of six books on employee experience and the future of work; publishes "The Future Of Work" newsletter.
Why I recommend it: Bridges the gap between "AI is coming" panic content and what it actually means for how you are managed day to day.
Future of work and AI architect, former Head of Remote at GitLab, writing and consulting on distributed and remote-first work.
Why I recommend it: He built GitLab's entire remote playbook from scratch — anyone managing or negotiating remote work should read his stuff first.
Future of work advisor and founder of HRTechRadar, connecting HR technology, pay and workforce strategy from the Netherlands.
Why I recommend it: A rare voice that treats HR tech and compensation as one connected system instead of separate topics.
The underlying working paper by Jeremy Yang and co-authors, using Perplexity data to model tasks as discrete steps and compare fixed vs. marginal costs of chatbots versus autonomous agents.
Why I recommend it: If the HBS summary hooks you, go to the source. Skim the task-cost framework and use it to audit your own week: which tasks are high-step and repeatable? Those are the ones to hand to an agent first.
Harvard Business School AI Institute breakdown of new research on agentic AI: how autonomy and context integration shift the cost structure of knowledge work, expanding both productivity and the scope of what workers take on.
Why I recommend it: Read this before you assume AI just speeds up your current tasks. The useful takeaway for job seekers: agents lower the cost per step, so the valuable human skills become specifying goals clearly and verifying output. Practice describing outcomes, not keystrokes, and put "agent workflow design" language in your resume bullets.
Leading employment and contract network across the Middle East and North Africa.
Why I recommend it: Useful if you are open to relocation or remote work with MENA employers.
Experis/ManpowerGroup research summary on how employers and employees are actually using AI at work, plus a five-step action plan for building AI career durability.
In plain terms: A research write-up from staffing firm Experis showing most employers now use AI in hiring and are fine with candidates using it too, while very few companies have AI fully rolled out. It argues AI mostly augments jobs rather than replacing them, and lists five practical steps — build durable skills, learn your company's AI tools, research use cases for your role, take free training, and propose a small pilot.
From the site: Exploring the key findings of our new report: Building and Sustaining a Meaningful Career in the AI Age.
Why I recommend it: The headline stat matters for job seekers: 85% of employers say it is fine for candidates to use AI during hiring, and 53% already use AI in hiring and onboarding. Use the five-step durability plan as a checklist — learn what AI your employer is deploying, find use cases for your role, take free training, then pitch one small pilot you can measure. That pilot becomes a resume bullet.
Labor market research institute studying degree requirements, skills-based hiring trends, and economic mobility using real job posting data.
In plain terms: This research institute analyzes employment data and hiring trends across the country. You can read free reports to learn which job skills are in demand, explore labor market forecasts, and find which credentials lead to higher pay.
Why I recommend it: Their reports tell you which employers actually dropped degree requirements versus which just said they did.
Disability Advocate, Speaker. Advocate with cerebral palsy addressing hiring discrimination, workplace tokenism, and the disability unemployment gap.
In plain terms: This is the LinkedIn profile of a disability advocate and speaker. Follow him to learn about navigating job accommodations, fighting hiring discrimination, and advocating for disability inclusion at work.
Why I recommend it: Honest about what hiring actually feels like with a visible disability.
Nonprofit providing free tech training, apprenticeships, and job placement to bridge the gap between learning to code and employment.
In plain terms: This nonprofit offers free tech training and job placement services. You can learn software development or artificial intelligence skills and get matched with hiring employers.
Why I recommend it: Free training plus actual placement — one of the strongest career-change paths into tech.
The Ludwig Institute's alternative unemployment measure that counts people who are jobless, underemployed, or earning below a living wage.
In plain terms: A research institute publishes a "true rate of unemployment" that counts anyone jobless, stuck in part-time work, or earning under a living wage. The number is usually far higher than the official rate, which explains why a "strong" job market can still feel impossible.
From the site: LISEP’s mission is to help achieve shared economic prosperity for all Americans, particularly for middle- and low-income families. Our focus is fact-based economic and policy research.
Why I recommend it: When headlines say the job market is strong and your search still feels brutal, this number explains the gap. Useful language for interviews and for your own sanity.
Practical first steps after losing a job — severance and paperwork, unemployment benefits, health coverage, references, and how to sequence your search in the first 30 days.
In plain terms: This guide outlines steps to handle the emotional and personal impact of losing a job. You can use it to establish healthy daily routines, find support, and prepare yourself before starting a new search.
Why I recommend it: Do the benefits and paperwork items in week one. Filing late for unemployment costs real money you can't get back.
Created by Phyl Terry — Never Search Alone
World Economic Forum podcast episode on the skills-first shift: which capabilities are growing fastest, how employers are restructuring roles, and what workers should invest their learning time in.
Why I recommend it: Listen on a commute. The point that sticks: skills expire faster than degrees, so a learning habit beats a credential.
A step-by-step guide to forming an LLC (name search, registered agent, state filing, operating agreement, free EIN, business banking) and electing S-corp tax status, with filing fees and direct portal links for NY, NJ, GA, and CA, plus a section on 1099 contractor and consulting taxes.
In plain terms: This guide explains how to set up an LLC or elect S-corp tax status for freelance and consulting work. You can use it to register your business, get a free tax ID, and understand your self-employment taxes.
Why I recommend it: Most consultants should start as a plain LLC and only add the S-corp election once net profit is consistently past roughly $50-80K. Get the free EIN yourself — never pay for it.
Created by Justin Smith — Launchpad Library
Brookings fellow writing on AI, workers, and the future of good jobs.
In plain terms: This newsletter features writing from a Brookings fellow about artificial intelligence, workers, and the future of jobs. You can read it to stay informed about how technology impacts the modern workplace.
From the site: Click to read Molly Kinder on Substack. Launched 15 days ago.
Why I recommend it: Her worker-first framing is exactly how to talk about AI in a job interview.
