20 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
Qiaochu Yuan (QC) on seeing Eliezer Yudkowsky as a prophet, and what that framing means for thinking about AI risk and the future.
From the site: I see Eliezer Yudkowsky as a prophet, and I mean that fairly literally.
Why I recommend it: Substack may show signup prompts, but the article itself was publicly accessible when added.
Substack from historian Rutger Bregman on moral ambition and doing work that matters, aimed at people considering a career built around impact.
From the site: Historian | Author of ‘Moral Ambition’ (2025), ‘Humankind’ (2020) and ‘Utopia for Realists’ (2014) | Co-founder of The School for Moral Ambition. Click to read Rutger Bregman, a Substack publication with tens of thousands of subscribers.
Why I recommend it: Directly relevant if you are rethinking what your career is for. It argues a position hard; take the questions, not the prescriptions.
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.
Personal Substack by 0xMovez AI covering AI, automation, and emerging technology for thousands of subscribers.
From the site: My personal Substack. Click to read 0xMovez's Substack, by 0xMovez AI, a Substack publication with thousands of subscribers.
Why I recommend it: AI and automation commentary; sample a few posts to see if the angle matches where you are in your career.
Psychologist and professor Jacqueline Nesi translates new research on technology, attention, and mental health into practical guidance for digital life.
Why I recommend it: A research-backed counterweight to hot takes about screens and AI. Good source material if you write or speak about technology and people.
Newsletter breaking down system design and backend engineering concepts with clear diagrams — interview-grade explanations of how large systems work.
Why I recommend it: Use the diagrams as interview prep. If you can redraw one from memory and explain the tradeoffs out loud, you are ready to talk about it in a system design round.
Writer and ecosystem lead at a16z, publishing on startups, founder communities, and early-career paths into venture and tech.
Why I recommend it: A good window into how venture and startup ecosystems actually hire and connect people. Useful if you want a non-engineering way into tech.
Newsletter testing and comparing AI coding tools and prompts, with side-by-side results for developers.
Why I recommend it: Skip the hype cycle and read the comparisons. Pick one tool from a recent test, use it on a real project, and write up what happened.
FinTech and AI strategist writing on financial technology, startups, and where money and AI intersect.
Why I recommend it: Follow if fintech or payments is your target industry. His posts are a quick daily read on what the sector is reacting to.
Newsletter on building media and creator businesses that last, including the economics behind AI-generated content.
Why I recommend it: A good weekly counterweight to platform hype — it focuses on revenue durability instead of view counts.
next play's breakdown of the different categories of AI companies hiring right now and where the momentum is heading.
Why I recommend it: Read it as a target list: pick two or three categories that match your background before you start applying.
Practical AI guidance for small business owners who aren't high-tech, from a fellow small business owner.
In plain terms: This newsletter provides practical artificial intelligence guidance written by a small business owner. You can learn how to use AI to help your business succeed, even if you are not high-tech.
Why I recommend it: Written for Main Street, not for engineers — start here if AI feels like it is not for you.
Analysis at the intersection of finance and technology trends, by Byrne Hobart.
In plain terms: This newsletter provides in-depth articles analyzing trends, strategies, and news across the technology and finance industries. You can read detailed company profiles to understand market shifts and explore an included job board.
Why I recommend it: Dense, but it explains where the money behind tech is actually going.
Machine learning research explained clearly, by Sebastian Raschka. 199K+ subscribers.
In plain terms: This newsletter breaks down recent machine learning and artificial intelligence research into clear explanations. You can read it to stay up to date on new developments in the field.
Why I recommend it: Patient, teacherly explanations of ML research — great for career switchers.
Power dynamics and inside stories from Big Tech, by Alex Kantrowitz.
In plain terms: This newsletter and podcast covers inside reporting on major tech companies and their impact on society. You can read weekly updates and listen to interviews to stay informed about the technology industry.
Why I recommend it: Good on how decisions inside big companies land on workers.
Weekly, deeply researched advice on building products, driving growth, and accelerating your career, for product leaders and founders.
In plain terms: This weekly newsletter provides in-depth advice on building products, driving business growth, and advancing your career. You can read it to learn practical strategies for founder and product leadership roles.
Why I recommend it: The most useful single source I know for how promotions, scope, and product careers actually work.
Weekly synthesis of AI research and policy by Jack Clark, Anthropic co-founder. 130K+ subscribers.
In plain terms: This weekly newsletter summarizes the latest artificial intelligence research and policy. You can read it to keep up with developments in AI technology.
Why I recommend it: Best place to understand the policy fights that will shape AI jobs.
Long-form strategy deep dives on companies, markets, and the people shaping them.
Why I recommend it: One long piece at a time — good weekend reading if you are building something.
Technical AI newsletter for engineers building on AI systems, covering evals, inference, and agentic architectures.
In plain terms: This technical newsletter and podcast covers how leading teams build artificial intelligence models, agents, and infrastructure. You can use it to learn how modern AI systems are built and keep your engineering knowledge up to date.
Why I recommend it: If you want an AI engineering job, this is the vocabulary you need.
Career intelligence, industry deep dives, and Big Tech analysis for senior engineers and engineering leaders, by Gergely Orosz.
In plain terms: This newsletter offers inside perspectives on Big Tech, startups, and the software industry. You can read its career insights and industry analysis to help navigate engineering and technology leadership roles.
Why I recommend it: Read this before a tech interview loop or a comp negotiation — it tells you how the other side thinks.
