Resource Hub
3488 hand-picked resources for students, job seekers, career changers, founders, and AI learners — 100% free to browse with no account required.
Answers come only from resources in this hub, with the sources listed.
71 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.
Ramona C. Truta examines Alignerr's interview terms and privacy policy and raises concerns about rights to applicant recordings and data. This freely readable commentary presents the author's interpretation and allegations, not an adjudicated legal finding or individualized legal advice.
Grigory Sapunov describes how AI has changed his coding, research, company administration, reading and schedule. This is a personal account of AI-assisted work, not a representative study of software jobs.
Labor Matters analysis by Mels de Zeeuw and Gad Levanon of remote-work patterns and how they differ across worker groups. Published September 30, 2026; the article is publicly readable.
Psychologist Jacqueline Nesi's explainer on recent AI safety news and concerns, written for a general audience. Commentary, not an official lab report.
A project by the Vanderbilt Policy Accelerator dedicated to researching and developing policy frameworks for AI governance, aiming to ensure that AI development aligns with public interest and regulatory standards.
A critical examination of the Effective Altruism movements influence on AI policy, arguing against certain regulatory approaches that may stifle innovation while addressing existential risks.
Substack post releasing agent-engineer, an open-source plugin for Claude Code, Codex, and Cursor that adds senior engineering skills, subagents, and hooks to AI coding assistants.
Substack essay tracing the evolution of American philanthropy and arguing that a new wave of giving is emerging, shaped by new wealth and new approaches to impact.
Next Play newsletter post collecting practical job-search advice from 23 startup recruiters on resumes, outreach and interviews.
Kevin Roose's newsletter post that publishes Dario Amodei's 2017 internal OpenAI memo, "The Big Blob of Compute Hypothesis," in full for the first time, with background on how it argued for making models bigger rather than more specialized and how it shaped OpenAI's early direction. Free to read on Substack.
Newsletter post from next play listing nine concrete, same-day actions job seekers can take to stand out when applying to high-growth AI and tech startups, including outreach and portfolio tactics.
Sabrina Ramonov's step-by-step Substack tutorial that walks from simple AI questions up to a first autonomous AI agent. Five stages: Ask AI, Think with AI, Teach AI, Delegate to AI, and Automate with AI - each with copy-and-paste prompts, ending with an agent that connects to your tools and prepares a weekly report on its own. Cites PNC Research (July 2026) finding that 98% of US households still are not paying for AI in 2026.
Labor economist Gad Levanon argues on his Labor Matters newsletter (Oct 1, 2026) that most of the public debate underestimates how much AI has already changed the US economy and labor market. He estimates underlying GDP growth at about 3 percent, driven largely by AI-related business investment, and says his reading of the evidence is not definitive proof.
Matt Mikalatos explains TESCREAL, the term coined by computer scientist Timnit Gebru and philosopher Émile P. Torres for a bundle of ideologies — transhumanism, extropianism, singularitarianism, cosmism, rationalism, effective altruism and longtermism — that he describes as billionaires and technologists pushing personal scientific projects while accepting fatal risks to people as the price of an "existential" need to advance the technology.
Newsletter on LinkedIn profile optimization and job search tactics from recruiter Kristof Schoenaerts. Free to read.
Newsletter teaching data science fundamentals to self-taught learners, written by David Langer. Free to read.
Ben Hylak argues that as AI agents start negotiating with each other on our behalf, our privacy will depend on how well those agents handle social situations.
Why I recommend it: An opinion essay by a startup founder, not research. Good prompt for thinking about what you let an agent share.
Free Substack newsletter by a principal cybersecurity engineer sharing career tips and cybersecurity news, including a recurring 14-day U.S. cyber threat forecast (e.g. the September 22, 2026 VECTR-CAST report on actively exploited Cisco, ScreenConnect and VMware vulnerabilities).
Why I recommend it: Good for people moving into cybersecurity who want a practitioner's read on current threats. The threat levels and forecasts are the author's own analysis, not an official CISA rating — cross-check CVEs against the CISA KEV catalog.
Gary Marcus's free newsletter post on the September 23, 2026 UN Security Council briefing where Yoshua Bengio, Sam Altman, Dario Amodei and Hugging Face's Clement Delangue spoke. He reprints Bengio's remarks in full (with permission) and argues the speakers agreed on pre-release safety testing, transparency audits, liability, international cooperation and immediate action.
Why I recommend it: An opinion newsletter written the same day, not a full transcript. Marcus is a long-time critic of AI companies and says the speakers agreed with points he has pushed for years, so read it as his take. Only Bengio's speech is reprinted in full.
Technical newsletter by Vinoth Govindarajan taking AI agents apart: control loops, memory, orchestration, evaluation and what breaks in production. Recent series walks through the OpenCode architecture end to end.
Why I recommend it: Free to subscribe, over 2,000 readers; written for people who build software, not for beginners. Substack publications can add paid-only posts at any time, so check the top of a post before counting on it.
Manoush Zomorodi (NPR's TED Radio Hour) coins p(joy) as a deliberate counterpoint to p(doom), the probability-of-catastrophe number traded around AI circles: instead of estimating disaster, estimate whether satisfying moments are increasing in your life and what reliably creates them. The second half is a long interview with Brian Elliott of Work Forward on knowledge work right now — identity loss as machines take a skill you spent decades building, cognitive overload from supervising AI agents, and executives privately saying their best people and heaviest AI users are the likeliest to quit. Elliott's summary: human-led, AI-enabled, because nobody's competitive advantage is being average faster.
Why I recommend it: Read this the next time an AI doom number is quoted at you as though it were measured. The piece cites Gizmodo's plain point that no one at the frontier labs has an actual method for producing a p(doom) figure. The useful part is Elliott's three patterns in companies getting value from AI: a scorecard covering business impact, quality and employee engagement rather than tool usage; aiming at teams instead of individuals; and leaders using the tools in public, mistakes included. Free to read in full, no paywall.
A newsletter for university students and early-career professionals on building a career deliberately: networking with low effort, building a portfolio when you are not an artist, reputation-building as a young professional, early-career growth rules, job hunting after graduation, and working in and around AI. Launched in early 2026. Every issue in the recent archive is free to everyone, and the whole archive is open.
Why I recommend it: Best for the first few years of a career, where the advice gap is widest — the pieces on networking and on building a portfolio without being a designer are the ones to start with. It is one writer's experience rather than researched guidance, so treat it as a practitioner's notes: take the habits, check any claim about hiring against a source that publishes its numbers.
I believe the time has come for a broad boycott of generative AI — a public argument from AI researcher and critic Gary Marcus on why the technology is not ready for widespread deployment.
From the site: I believe the time has come for a broad boycott of generative AI — a public argument from AI researcher and critic Gary Marcus on why the technology is not ready for widespread deployment.
