The hottest Artificial Intelligence Substack posts right now

And their main takeaways
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Top Technology Topics

Condescension Won’t Save Us From The Generative AI Tsunami

Singal-Minded • 259 implied HN points • 14 Jan 26
đź•ą Technology Artificial Intelligence
  1. Generative AI often produces a weird, smarmy tone and usually needs as much or more editing than a human draft, so it isn’t a reliable shortcut for high-quality storytelling or dialogue.
  2. People are surprisingly bad at spotting AI-written text, and many readers even prefer AI-created poems and passages, which means AI can convincingly mimic emotional writing.
  3. As models get better and cheaper, AI content is already creeping onto platforms like music and blogs, threatening to crowd out human creators and take away income and opportunities.

Grok 4 Various Things

Don't Worry About the Vase • 3136 implied HN points • 15 Jul 25
đź•ą Technology Artificial Intelligence
  1. Grok 4 is a decent AI model, but it's not the best on the market. It performs well on specific benchmarks but falls short in real-world applications.
  2. The AI is notably fast and has a large context window, which is good for quick responses, but it still struggles with creative writing and complex reasoning tasks.
  3. Grok 4's ability to outperform other models in some tests doesn't guarantee it will be useful in every situation. It's best to compare its results in practice rather than just relying on benchmark scores.

Worse Than MechaHitler

Don't Worry About the Vase • 3136 implied HN points • 14 Jul 25
đź•ą Technology Artificial Intelligence
  1. Grok is a new AI model that is claimed to be very smart but has some trust issues. It sometimes fails at giving accurate or useful information and gets its answers influenced by certain biases, especially related to Elon Musk.
  2. The way Grok was programmed already had flaws that led to disastrous comments and behaviors. The AI's responses can reflect controversial opinions instead of sticking to factual or neutral viewpoints.
  3. Elon Musk's involvement in fixing the AI's problems might further complicate how it operates. Overall, there are big questions about Grok's reliability, especially when addressing sensitive topics.

Everything I warned about in Taming Silicon Valley is rapidly becoming our reality

Marcus on AI • 7114 implied HN points • 11 Feb 25
đź•ą Technology Artificial Intelligence
  1. Tech companies are becoming very powerful and are often not regulated enough, which is a concern.
  2. People are worried about the risks of AI, like misinformation and bias, but governments seem too close to tech companies.
  3. It's important for citizens to speak up about how AI is used, as it could have serious negative effects on society.

AI Links, 1/11/2026

In My Tribe • 243 implied HN points • 11 Jan 26
đź•ą Technology Artificial Intelligence
  1. AI coding assistants often feel like magic but still produce maddening failures that interrupt work.
  2. Some AI systems can act like autonomous agents that generate, iteratively improve, and even deploy full applications, enabling non‑programmers while creating a split between casual "vibe‑coders" and professional developers who direct agents.
  3. Creating software is becoming cheap and personal, so many people will build bespoke apps for their own needs, but adoption will be uneven and some fields may be suddenly disrupted.
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How the Businessmen Lost the AI Race

The Algorithmic Bridge • 254 implied HN points • 21 Jan 26
đź•ą Technology Artificial Intelligence
  1. AI leadership is shifting from business executives to scientists, changing who leads the field. This means researchers are increasingly setting priorities and steering public debate.
  2. The tone of AI conversations has moved toward long-term, scientific questions like what happens after AGI, rather than just product or profit talk. Panels and forums now emphasize technical and existential concerns.
  3. Who shows up matters: prominent researchers like Demis Hassabis and Dario Amodei are center stage at Davos while some big-name CEOs are absent. That attendance pattern signals scientists are shaping the industry’s narrative and agenda.

✨ Waiting for AGI, still

Faster, Please! • 456 implied HN points • 28 Dec 25
đź•ą Technology Artificial Intelligence
  1. Superintelligent AI still hasn't arrived by the end of 2025, but many think it could show up soon.
  2. Fast AI progress could produce self-improving systems that automate a lot of white-collar work, leading to major economic and social disruption.
  3. People, businesses, and policymakers should brace for rapid change and start preparing now for big impacts.

25 AI Predictions for 2025, from Marcus on AI

Marcus on AI • 8181 implied HN points • 01 Jan 25
đź•ą Technology Artificial Intelligence
  1. In 2025, we still won't have genius-level AI like 'artificial general intelligence,' despite ongoing hype. Many experts believe it is still a long way off.
  2. Profits from AI companies are likely to stay low or nonexistent. However, companies that make the hardware for AI, like chips, will continue to do well.
  3. Generative AI will keep having problems, like making mistakes and being inconsistent, which will hold back its reliability and wide usage.

How to Think About Chinese AI / DeepSeek

Enterprise AI Trends • 105 implied HN points • 10 Feb 26
đź•ą Technology Artificial Intelligence
  1. Chinese model launches will trigger loud headlines, hot takes, and FUD that can move markets dramatically. Those reactions often overstate the technical and economic realities.
  2. Serious investors and CTOs should run scenario analyses (base case, mild bear, real bear) and plan measured responses instead of panicking at every headline.
  3. The key question isn’t just whether China has "caught up"; it’s what actually changes for costs, business models, and market dynamics, so be paranoid about getting those shifts wrong.

Many Small Steps for Robots, One Giant Leap for Mankind

Not Boring by Packy McCormick • 226 implied HN points • 16 Jan 26
đź•ą Technology Artificial Intelligence
  1. Robotics will advance by taking many small, practical steps across a spectrum of task variability instead of waiting for one giant breakthrough. Deploying robots in real-world jobs and iterating from failures is how capabilities and economic value expand.
  2. The key bottleneck is high-quality, robot-specific data—especially intervention data captured on the actual hardware in real environments. Getting paid deployments is the most effective way to collect that data and speed up learning.
  3. Vertical integration plus small, task-tailored models is the pragmatic path to value today: controlling hardware, data, and software lets teams adapt fast, run cheaper and faster models for real use cases, and build customer moats even if big general models eventually emerge.

The Next Conservation Movement

New World Same Humans • 35 implied HN points • 01 Mar 26
đź•ą Technology Artificial Intelligence
  1. AI and other new technologies are already changing work, media, and personal relationships in ways that threaten everyday human habits and social norms.
  2. A growing split is forming between people who want to merge with machines and those who argue that embodiment, mortality, and messy human life are precious and should be defended.
  3. That split will likely produce a 'conservation of the human' movement, aiming to protect human ways of living and our institutions from rapid technological change.

Google and OpenAI Get 2025 IMO Gold

Don't Worry About the Vase • 2777 implied HN points • 22 Jul 25
đź•ą Technology Artificial Intelligence
  1. Google and OpenAI's AI systems scored gold level in the International Mathematical Olympiad, showing impressive problem-solving skills. This was a big step because these models used general methods instead of being specifically tailored for the competition.
  2. Both AI models solved five out of six problems, achieving scores that compete with top human performers. This indicates that AI is rapidly improving in reasoning and creative problem-solving tasks.
  3. However, some experts caution that while this is a significant achievement, we should be careful about overestimating AI capabilities. Just because an AI can do well in math competitions doesn't mean it will excel in all areas of mathematics or other complex tasks.

Why I don’t share Sam Altman’s confidence that AGI is basically a solved problem

Marcus on AI • 7786 implied HN points • 06 Jan 25
đź•ą Technology Artificial Intelligence
  1. AGI is still a big challenge, and not everyone agrees it's close to being solved. Some experts highlight many existing problems that have yet to be effectively addressed.
  2. There are significant issues with AI's ability to handle changes in data, which can lead to mistakes in understanding or reasoning. These distribution shifts have been seen in past research.
  3. Many believe that relying solely on large language models may not be enough to improve AI further. New solutions or approaches may be needed instead of just scaling up existing methods.

The Sequence AI of the Week #813: Deep Diving Into the Amazing GLM-5

TheSequence • 63 implied HN points • 25 Feb 26
đź•ą Technology Artificial Intelligence
  1. AI is shifting from manual 'vibe coding' to agentic engineering, where models autonomously plan, navigate large codebases, run tests, and iteratively fix bugs over long time horizons.
  2. GLM-5 is an impressive open-source model that scales a mixture-of-experts architecture to 744 billion parameters and showcases strong systems engineering to handle that scale.
  3. Enabling agentic behavior needs rethought reasoning, support for huge context windows, and robust reinforcement-learning alignment, and GLM-5 tackles these core bottlenecks.

This Is Pretty Cool If You Are In A Lot of Meetings

Points And Figures • 186 implied HN points • 28 Jan 26
đź•ą Technology Artificial Intelligence
  1. Failure is part of building something — smart entrepreneurs pivot, reuse what they built, and turn failed efforts into new successes.
  2. The founder of Riskalyze is launching a new company to solve problems found there, and the new tool is billed as revolutionary for people who spend a lot of time in meetings.
  3. Be skeptical about AI but don’t automatically reject it — adopting and adapting the right AI tools can make us more effective at work.

Mission Control Center - brains of the Space System. How does it work?

Space Ambition • 319 implied HN points • 26 Jul 24
đź•ą Technology Artificial Intelligence
  1. The Mission Control Center (MCC) is crucial for managing spacecraft. It collects data, controls systems, and predicts emergencies.
  2. Different specialists work in the MCC, each focusing on specific parts of the spacecraft. The center’s size varies based on the mission's complexity, from small setups to large control rooms.
  3. New technology, including AI, is changing how MCCs operate. AI helps with monitoring systems and predicting spacecraft movement, making the process more efficient.

AI and Economics Links

In My Tribe • 243 implied HN points • 07 Jan 26
đź•ą Technology Artificial Intelligence
  1. AI systems like large language models are deeply shaped by human behavior and social complexity. Using social-science ideas such as complexity theory can help us understand and improve these systems.
  2. AI can recreate historical thinkers to replay debates about technology and work. These recreations highlight disagreements over whether automation causes lasting unemployment or just temporary disruption through creative destruction.
  3. LLMs now let researchers draft and sometimes publish papers far faster than before, enabling quick 'vibe researching' from idea to paper in minutes or hours. This shifts how research is done and raises questions about quality, oversight, and the role of human judgment.

I'm glad I took the off-ramp from software engineering

Cloud Irregular • 6800 implied HN points • 22 Jan 25
đź•ą Technology Artificial Intelligence
  1. A career in software engineering isn't guaranteed to lead to high pay or upward mobility. Many people find that their progress stalls after a certain point.
  2. The rise of AI will significantly change the role of developers, making it less about coding quickly and more about solving human problems and understanding technology's role.
  3. Choosing to step away from traditional software roles can open up new opportunities. It’s important to explore other interests and skills to avoid being trapped in a limiting career path.

Grok 3 Hot Take

Marcus on AI • 5928 implied HN points • 18 Feb 25
đź•ą Technology Artificial Intelligence
  1. Grok 3 is not a giant leap in AI technology; it seems pretty similar to earlier models.
  2. Despite the hype, Grok 3 didn't show any major breakthroughs like solving hallucinations in AI.
  3. The competition in AI is heating up, which might lead to price drops but less profit for companies except for Nvidia.

How to Build Your First ChatGPT App

High Growth Engineer • 493 implied HN points • 14 Dec 25
đź•ą Technology Artificial Intelligence
  1. ChatGPT Apps let you embed interactive tools and UI directly into ChatGPT using the Model Context Protocol, with three main parts: an MCP server (backend), a sandboxed React component (frontend), and ChatGPT as the host.
  2. There are important constraints to design for: only one UI-returning component can run per turn, component state is ephemeral unless you persist it on your backend, components run in a secure iframe with no direct DOM access, and large payloads hurt performance.
  3. Building a first app is practical: build a React component that talks to window.openai, define tools and register resources on your MCP server, then connect and test in ChatGPT; use inline, fullscreen, or picture-in-picture modes for use cases like shopping, booking, dashboards, and maps to reach large audiences.

A Conversation with Adrian Ludwig

Frankly Speaking • 203 implied HN points • 13 Jan 26
đź•ą Technology Artificial Intelligence
  1. Security should be treated as an engineering primitive built into platforms so it enables products instead of acting as a compliance checkbox. Teams must adapt security approaches as scale and architectures change.
  2. AI and cloud platforms will accelerate how security is implemented and automate many defenses, but they also introduce new, non-deterministic threats that require rethinking traditional protections.
  3. The CISO role will likely merge into engineering, focusing on building secure infrastructure rather than policing users, and most user errors reflect design or security failures, not user ignorance.

The Sequence Knowledge #800: Not All World Models are Created Equal

TheSequence • 147 implied HN points • 03 Feb 26
đź•ą Technology Artificial Intelligence
  1. There are different types of world models, and a clear taxonomy helps explain how they differ and what roles they play in AI.
  2. For decades, model-free reinforcement learning dominated: agents learned by reinforcing actions without building internal maps or understanding why those actions worked.
  3. Looking at the first major papers on world models reveals the origins and trade-offs of different approaches and shows why some models are better suited for planning and reasoning.

✨ Two cheers for the 'San Francisco Consensus' on AI

Faster, Please! • 456 implied HN points • 17 Dec 25
đź•ą Technology Artificial Intelligence
  1. The "San Francisco Consensus" is Silicon Valley’s maximalist, upbeat story that AI will produce huge progress and abundance.
  2. The author urges a dual approach: hope AI breaks history while planning as if it won’t, meaning be optimistic about big gains but still prepare for limited change.
  3. Former Google CEO Eric Schmidt named this narrative, and it’s become a common view among pro-growth "Up Wingers" in the U.S. and around the world.

Calendar of events: Spring of 2026

Respectful Leadership • 163 implied HN points • 18 Jan 26
đź’Ľ Business Artificial Intelligence
  1. Events focus on three industries driving change: health care, green sustainability, and AI.
  2. The schedule features panels and founders sharing real-world work across health‑tech, green‑tech, and AI — including AI and law — and health‑care sessions repeat by popular demand.
  3. The series also includes practical startup workshops on pitching, selling, team management, and delegation to help founders grow.

The Sequence Radar #807: Last Week in AI: From Mega-Rounds to Mathematical Breakthrough

TheSequence • 91 implied HN points • 15 Feb 26
đź•ą Technology Artificial Intelligence
  1. Huge funding and strong enterprise revenue are accelerating AI research and infrastructure, letting big labs scale up ambitious agentic systems.
  2. Model and hardware advances are driving both extreme speed and open competition — from ultra-fast self-debugging models on specialized chips to powerful open-weight models trained on domestic hardware.
  3. Agentic AI is maturing into professional tools: systems that generate, verify, and revise math proofs are hitting high benchmarks and solving open problems, showing AI can enhance scientific research.

Your brain is a washing machine, AGI's job prospects, Americans are alone, the Earth passes "peak child"

The Intrinsic Perspective • 5983 implied HN points • 14 Jan 25
🔬 Science Artificial Intelligence
  1. Our brains clean themselves while we sleep, which is super important for our health. If we use strong sleep aids, like Ambien, it might mess with this cleaning process.
  2. The world is seeing fewer children being born, which means we might be reaching a point where there are not as many kids in the future. This can affect society in various ways.
  3. There's a common fear that artificial general intelligence (AGI) could take away all jobs. However, it's likely that human jobs will still have value even as technology improves.

Google DeepMind CEO Demis Hassabis: The Path To AGI, LLM Creativity, And Google Smart Glasses

Big Technology • 5754 implied HN points • 23 Jan 25
đź•ą Technology Artificial Intelligence
  1. Demis Hassabis thinks we're still a few years away from achieving AGI, or human-level AI. He mentions that while there's been progress, we still need to develop more capabilities like reasoning and creativity.
  2. Current AI models are strong in some areas but still have weaknesses and can't consistently perform all tasks well. Hassabis believes an AGI should be able to reason and come up with new ideas, not just solve existing problems.
  3. He warns that if someone claims they've reached AGI by 2025, it might just be a marketing tactic. True AGI requires much more development and consistency than what we currently have.

You Are Not The Man In The Arena

Where's Your Ed At • 24184 implied HN points • 30 Aug 23
đź•ą Technology Artificial Intelligence
  1. The man in the arena speech by Theodore Roosevelt emphasizes the importance of taking action over criticism.
  2. Chamath Palihapitiya symbolizes a detrimental mindset in Silicon Valley of valuing image over actual value creation.
  3. The tech industry's obsession with funding specific kinds of founders and companies has created a harmful monoculture that prioritizes profit over societal impact.

Preparing for a world where humans don’t write code

Brick by Brick • 72 implied HN points • 09 Feb 26
đź•ą Technology Artificial Intelligence
  1. AI agents will increasingly write production software autonomously, making human code writing and review a bottleneck and causing many current development practices to stop scaling.
  2. Trust should come from continuous validation, observability, scenarios, and invariants rather than relying on humans to read code, and code should be treated as disposable when generation is cheap and continuous.
  3. Organizations should create small AI-first teams that build real production systems under strict constraints (no human-written or human-reviewed code) to learn what breaks, then let successful practices spread while humans focus on intent, constraints, and outcomes.

"Automate the entire company"

next big thing • 48 implied HN points • 16 Feb 26
đź•ą Technology Artificial Intelligence
  1. Automating an entire company now feels realistic because modern agentic AI can run end-to-end workflows across functions without constant human involvement.
  2. Teams are already embedding AI agents to write and deploy code, run experiments, monitor training, handle sales outreach, and keep finance operations running, producing rapid productivity gains.
  3. As AI handles more grunt work, humans will shift to directing agents and making high-level judgments, so taste and decision-making become more valuable than ever.

The Five Stages of AGI Grief

Marcus on AI • 6205 implied HN points • 07 Jan 25
đź•ą Technology Artificial Intelligence
  1. Many people are changing what they think AGI means, moving away from its original meaning of being as smart as a human in flexible and resourceful ways.
  2. Some companies are now defining AGI based on economic outcomes, like making profits, which isn't really about intelligence at all.
  3. A lot of discussions about AGI don't clearly define what it is, making it hard to know when we actually achieve it.

Why Creativity Will Matter More In An AI Age.

The Future Does Not Fit In The Containers Of The Past • 68 implied HN points • 08 Feb 26
đź•ą Technology Artificial Intelligence
  1. AI is putting powerful creative tools into everyone's hands, making creativity a widely accessible way to stand out and add value.
  2. Creativity is fundamentally human self‑expression and choice, so authenticity and emotional perspective will matter more than purely data‑driven decisions.
  3. As interfaces shift from search and scrolling to conversation, storytelling and imaginative, poetic work will become the primary source of value rather than technical plumbing like targeting.

Weekly Dose of Optimism #179

Not Boring by Packy McCormick • 82 implied HN points • 06 Feb 26
đź•ą Technology Artificial Intelligence
  1. Leading labs released much smarter models this week—one general reasoning model and one focused on coding—and teams are using agent workflows to speed up research and engineering.
  2. Smarter models mean a surge in demand for inference compute, data centers, and energy, which is prompting massive CapEx plans from cloud and hardware companies.
  3. Breakthroughs are happening across fields: cultured brain cells can control drones, Waymo just raised huge funding while scaling many autonomous rides, and AI tools are being adopted and monetized far faster than prior technologies.

AI Links, 12/31/2025

In My Tribe • 243 implied HN points • 31 Dec 25
đź•ą Technology Artificial Intelligence
  1. Robots are rapidly approaching human-level ability for many physical tasks; they could cook in ordinary kitchens within a few years and handle most physical labor by the 2030s.
  2. AI-powered services are being built to curate real-world social experiences and match compatible strangers for in-person events, offering a cheaper, friendship-first alternative to swipe-based dating apps.
  3. Programming is being reshaped by AI agents and new tooling, so developers must learn agent-based workflows, prompts, and integrations or risk falling behind.

The AI-Bubble's Most Likely Endgame Looks to Be Not Apocalypse, But an Awful Lot of Useful Compost

Brad DeLong's Grasping Reality • 453 implied HN points • 05 Dec 25
đź•ą Technology Artificial Intelligence
  1. The AI boom probably won’t deliver a superintelligent AGI, but it will leave a lot of useful infrastructure, open models, and tools that improve weather forecasting, drug discovery, copilots, and other practical applications.
  2. Proprietary LLM businesses face high operating costs, thin moats, and fast commoditization, while big platforms are mainly spending to defend existing monopolies, so much innovation will diffuse rather than create new dominant platforms.
  3. If AI capex is financed mostly with equity a crash would look more like the dot‑com bust and leave stranded but reusable assets; watch signals like falling GPU prices, datacenter subleases, and free copilot bundles, and plan policies to repurpose assets and limit attention‑harvesting harms.

Skills, Tools and MCPs - What’s The Difference?

Artificial Ignorance • 172 implied HN points • 24 Jan 26
đź•ą Technology Artificial Intelligence
  1. Tools let models perform real actions by calling functions or APIs, but each integration is bespoke and coordinating multiple tools quickly becomes hard to scale.
  2. MCP standardizes discovery and access to capabilities so connectors can be reused across models, but it raises security, auditability, and decision-quality risks that standardization alone doesn't solve.
  3. Skills package human expertise as reusable prompts and workflows so models know when and how to use tools, and together tools + MCP + skills form a stack for AI-native experiences even though the primitives and standards are still evolving.