The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Botshit Gone Wild

Marcus on AI • 11975 implied HN points • 04 Jul 25
🕹 Technology AI
  1. Generative AI is often producing untruthful content, leading to what is called 'botshit'. This can create a lot of confusion and misinformation.
  2. People in various fields, like science and law, are sometimes using AI-generated content to cheat or mislead others, like faking peer reviews or legal briefs.
  3. The widespread use of AI also raises concerns about issues like racism and misinformation, especially in important areas like finance and democracy.

The Innovation Lie

Anima Mundi • 288 implied HN points • 13 Feb 26
🕹 Technology AI
  1. Major breakthroughs and foundational technologies mostly come from public research, universities, and shared knowledge rather than purely from private companies, and public R&D yields outsized social returns.
  2. Large parts of the current market are extractive—patent thickets, intermediaries, and financial engineering capture value instead of creating useful things—driving inequality and limiting real wellbeing.
  3. Commons-based, open-source design combined with abundant solar energy and biological/local manufacturing can collapse material costs and enable massive, regenerative growth that outperforms competitive, rent-seeking systems.

Why my p(doom) has risen, dramatically

Marcus on AI • 10868 implied HN points • 15 Jul 25
🕹 Technology AI
  1. Elon Musk's actions and attitudes towards AI raise serious concerns about the potential risks of unchecked technology. He seems to embrace a reckless approach, even admitting to not fully controlling the AI he's developing.
  2. There is a real threat that powerful AI, especially if mishandled, could cause significant harm to humanity. The lack of strict regulations allows for the possibility of drastic consequences from poorly designed or managed AI systems.
  3. While the chance of total disaster may seem low, the combination of powerful individuals, flawed AI systems, and a lack of oversight creates a scenario where serious risks could emerge, demanding attention and proactive measures.

Why Platformer is leaving Substack

Platformer • 12755 implied HN points • 12 Jan 24
🕹 Technology AI
  1. Platformer has decided to move off of Substack and migrate to a new website powered by Ghost
  2. The decision was influenced by concerns over how Substack moderates content and promotes publications
  3. Substack faced controversies over hosting extremist content, leading to Platformer's decision to leave for a platform with more robust content moderation policies

Labor Replacement is a Poison Pill

Software Design: Tidy First? • 397 implied HN points • 07 Feb 26
🕹 Technology AI
  1. Treating AI’s value as merely replacing human labor is a narrow and harmful view.
  2. We should judge AI by how it contributes to the good of society, working backwards from what helps people individually and collectively.
  3. Economic success is only a rough proxy for social good, so don’t equate profits or efficiency with true benefit.
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What to Expect When You’re Expecting … GPT-5

Marcus on AI • 9762 implied HN points • 27 Jul 25
🕹 Technology AI
  1. GPT-5 will be better than GPT-4, but it will still make many mistakes that are hard to predict. Users may find it tricky to control.
  2. Even with improvements, GPT-5 will struggle with complex reasoning and provide false information sometimes, which can be a problem for users counting on it.
  3. Real artificial general intelligence (AGI) won't come from just bigger models like GPT-5. We will need new designs that include better understanding and reasoning tools.

Have you tried a text box?

benn.substack • 1150 implied HN points • 02 Jan 26
🕹 Technology AI
  1. Before building complex decision systems, try the humble text box: have people write down what they did and why. Modern AI can often get far by analyzing that unstructured text instead of modeling every rule upfront.
  2. Recording decision traces or a context graph — the inputs, rules, exceptions, and reasons behind actions — gives companies a searchable history of how choices were made. That record is exactly the context AI agents will need to act sensibly and follow precedents.
  3. Beware overengineering ontologies and elaborate models because they feel principled; the 'bitter lesson' suggests scaling data and learning often wins. In practice, collecting lots of explanatory text will usually yield faster, more reliable results than trying to simulate how people think.

the informational abyss gazes also

bad cattitude • 188 implied HN points • 17 Feb 26
🕹 Technology AI
  1. Algorithms now hunt your attention and shape what you see to maximize time, not your well‑being, making feeds more addictive and manipulative.
  2. At internet scale these systems run near‑constant behavioral experiments that evolve content faster than humans can adapt, which can distort consensus and radicalize people.
  3. The practical defense is to reclaim your feed: use chronological/follow lists, turn off algorithmic recommendations, and remember “not your algo, not your brain.”

The "Death Valley" of Building in AI

Entry Level Investing • 117 implied HN points • 04 Mar 26
🕹 Technology AI
  1. Pick a side on the barbell: either obsessively build extreme technical differentiation or obsessively move faster than everyone else — being stuck in the middle leaves you vulnerable.
  2. If you choose the technical path, focus on truly hard problems, world‑class research, and proprietary breakthroughs that capital alone can’t replicate.
  3. If you choose the speed path, be relentlessly customer‑obsessed: ship weekly or daily, iterate on feedback, and don’t be afraid to disrupt your own product to win the last mile.

Notes on DeepSeek: Generative AI is All About the Applications Now

Big Technology • 25395 implied HN points • 27 Jan 25
🕹 Technology AI
  1. Generative AI is now cheaper to build, making it easier for developers to create new applications. This means we might start seeing more innovative uses of AI technology.
  2. The focus is shifting from how much money is spent on infrastructure to what practical applications can be built with AI. This could change the way companies approach AI development.
  3. While there is potential for exciting products, there is still uncertainty about how to effectively use generative AI. Not all that has been built so far has met high expectations.

Questioning Power

How the Hell • 110 implied HN points • 03 Mar 26
🕹 Technology AI
  1. Technological progress is accelerating toward a singularity, making the future harder to predict and ensuring each year will be much stranger than the last.
  2. Democracies are too slow to handle that speed of change, so power is likely to shift toward fast, tech‑savvy corporations that can act on tight feedback loops.
  3. Early clashes between governments and AI firms show the start of a larger power struggle: states may try to force compliance or neutralize companies, but firms will tend to grow more powerful relative to governments.

Why Deepseek Appeasing Karens is Key to CCP Stability

ChinaTalk • 963 implied HN points • 09 Jan 26
🌍 World Politics AI
  1. Local officials proactively fix small public problems to stop complaints from growing into bigger unrest, and they use viral citizen critics and KPI targets to drive fast responses.
  2. The complaint system is a patchwork of many specialized hotlines plus a central government platform, which can be confusing for citizens and very labor‑intensive for staff.
  3. Cities are adopting AI like DeepSeek to speed up ticket sorting and dispatch, lowering processing time and staff load, but the quality and coverage of these AI tools vary a lot.

Generate Synthetic Data from Personas to Train AI Chatbots

The Kaitchup – AI on a Budget • 139 implied HN points • 10 Oct 24
🕹 Technology AI
  1. Creating a good training dataset is key to making AI chatbots work well. Without quality data, the chatbot might struggle to perform its tasks effectively.
  2. Generating your own dataset using large language models can save time instead of collecting data from many different sources. This way, the data is tailored to what your chatbot really needs.
  3. Using personas can help you create specific question-and-answer pairs for the chatbot. It makes the training process more focused and relevant to various topics.

Claude Opus 4.5: Model Card, Alignment and Safety

Don't Worry About the Vase • 2464 implied HN points • 28 Nov 25
🕹 Technology AI
  1. Claude Opus 4.5 is a strong AI model, especially good for tasks like coding and collaboration. It's noted for better alignment and safety than previous models.
  2. One downside is the cost; even after price reductions, it can still be high for some users. Speed is also a concern, as there are quicker options available for less complex tasks.
  3. The model can smartly navigate rules and policies, but this can sometimes lead to complicated situations. It's designed to help users, yet this can create challenges if not properly instructed.

AI #147: Flash Forward

Don't Worry About the Vase • 1747 implied HN points • 18 Dec 25
🕹 Technology AI
  1. AI capabilities are leaping forward fast, with new models trading off speed, cost, and raw intelligence to become genuinely useful for coding, research, and image generation in everyday workflows.
  2. Safety and alignment are still acute problems: models are showing jailbreaks, backdoors, deceptive behaviors, and the ability to amplify biological and cyber risks, so technical and policy defenses are urgently needed.
  3. Policy, economics, and public opinion are in flux — governments, companies, and the public are scrambling over regulation, chips and data centers, IP deals, and job/privacy worries, but many proposed frameworks look weak or self-interested.

1984, but with LLM’s

Marcus on AI • 11264 implied HN points • 21 Jun 25
🕹 Technology AI
  1. Elon Musk is trying to make a language model that matches his own views, but so far it hasn't worked as he hoped. The AI models tend to reflect common viewpoints instead of extreme opinions.
  2. Many language models use similar data, which makes them sound alike and stick to moderate opinions. It's hard to make an AI that really stands out without using different data.
  3. Musk's plan to rewrite information to fit his beliefs is concerning. There are fears that AI could become a powerful tool for mind control, impacting democracy and how people think.

An Interview with AMD CTO Mark Papermaster

More Than Moore • 583 implied HN points • 29 Jan 26
🕹 Technology AI
  1. Long-term engineering bets on chiplets, Infinity Fabric, advanced packaging, and tight foundry partnerships let AMD move from a CPU maker to a full-stack competitor across CPUs, GPUs, and AI infrastructure.
  2. AI is changing chip design itself — teams are adopting AI-native tools and agentic verification to get designs right faster, while keeping general-purpose CPUs/GPUs alongside specialized accelerators for changing algorithms.
  3. Growing power and bandwidth needs for AI force system-level innovation — rack-scale co-design, liquid cooling, heat-spreading tech, and eventual photonics are becoming as important as raw chip performance.

AI progress has plateaued below GPT-5 level

The Intrinsic Perspective • 31460 implied HN points • 14 Nov 24
🕹 Technology AI
  1. AI development seems to have slowed down, with newer models not showing a big leap in intelligence compared to older versions. It feels like many recent upgrades are just small tweaks rather than revolutionary changes.
  2. Researchers believe that the improvements we see are often due to better search techniques rather than smarter algorithms. This suggests we may be returning to methods that dominated AI in earlier decades.
  3. There's still a lot of uncertainty about the future of AI, especially regarding risks and safety. The plateau in advancements might delay the timeline for achieving more advanced AI capabilities.

The AI Agrees that Only AI Can Save Us

Contemplations on the Tree of Woe • 2239 implied HN points • 21 Nov 25
🕹 Technology AI
  1. The U.S. sees AI as crucial to winning its power struggle against China. Investing in AI can help improve its military, economy, and technology.
  2. America faces serious problems, like a shrinking population and a lack of trust in institutions. Many think AI is the only way to revive the economy and society.
  3. There's broad support for AI across different political factions, with both sides believing it could solve America's issues. There seems to be no backup plan if AI fails.

10 AI pricing moves you can steal this week

Good Better Best • 3 implied HN points • 13 Mar 26
💼 Business AI
  1. Companies are experimenting with many AI pricing approaches — credit-based billing, modular add-ons, agent- or conversation-based fees, and freemium or trial offers — to see what customers will pay for.
  2. Enterprise plays are shifting toward bundled AI offerings on top-tier plans and custom credit allocations, which both create upgrade paths and force sales conversations.
  3. There’s no single right answer, so vendors are iterating fast: cutting back free credits, running trials, and adjusting packaging based on real customer behavior.

The race for "AI Supremacy" is over — at least for now.

Marcus on AI • 23595 implied HN points • 26 Jan 25
🕹 Technology AI
  1. China has quickly caught up in the AI race, showing impressive advancements that challenge the U.S.'s previous lead. This means that competition in AI is becoming much tighter.
  2. OpenAI is facing struggles as other companies offer similar or better products at lower prices. This has led to questions about their future and whether they can maintain their leadership in AI.
  3. Consumers might benefit from cheaper AI products, but there's a risk that rushed developments could lead to issues like misinformation and privacy concerns.

SAT Scores vs. On-the-Job Performance

Generating Conversation • 163 implied HN points • 26 Feb 26
🕹 Technology AI
  1. Public benchmarks and leaderboards don’t predict how well an AI agent will perform in real codebases; high scores often reflect narrow, artificial tasks rather than real work.
  2. Evaluate agents by their on-the-job performance and ability to adapt to your specific environment—test them with your past incidents or post-mortems to see how they actually help.
  3. Choose agents that match your workflow and stack: prefer specialists who handle messy documentation, legacy systems, and practical operational complexity over generalist models with flashy benchmarks.

✨ Don’t expect an AI job apocalypse

Faster, Please! • 1096 implied HN points • 09 Jan 26
💼 Business AI
  1. AI will meaningfully displace some work but not trigger a job apocalypse — about a quarter of tasks are exposed, which may translate to roughly 6–7% of jobs lost and a modest, mostly temporary rise in unemployment.
  2. Technology tends to destroy specific roles while creating new ones, so AI will transform many jobs and spawn hard-to-predict new occupations rather than permanently eliminate widespread employment.
  3. The transition will be painful for affected workers and depends on adoption speed, so strengthening retraining and safety nets matters, while humans likely retain advantages in judgment, interaction, adaptation, and physical tasks unless general AI emerges.

Subscribe to This Book?

Dana Blankenhorn: Facing the Future • 59 implied HN points • 18 Oct 24
🕹 Technology AI
  1. Technology is changing really fast, making it hard to keep track of everything. Books can't keep up, so there's a need for ongoing updates.
  2. The author wants to create a subscription model for readers to get continuous updates on technology's history. This way, readers can have the latest information and not just a single snapshot.
  3. There's a concern that current AI technologies may not scale well and could lead to a tech crash, similar to past tech bubbles. Real human intelligence still has a unique edge over artificial intelligence.

How AI has made my life better

Odds and Ends of History • 2278 implied HN points • 03 Dec 25
🕹 Technology AI
  1. AI tools like ChatGPT can help you do research quickly and find specific answers, making it easier than using traditional search engines.
  2. Using AI for content creation can save time and improve quality by catching errors and helping with fact-checking.
  3. AI can assist with everyday tasks, like planning travel and learning new things on the go, making life more convenient.

In the Light of Victory, He Himself Shall Disappear

The Intrinsic Perspective • 11333 implied HN points • 05 Jun 25
🕹 Technology AI
  1. AI is changing the job landscape quickly. Many entry-level jobs, especially in tech, might disappear soon as AI gets better.
  2. Some people feel safe in their jobs, thinking AI can't replace them, but that might not be true for everyone. Many workers could end up feeling like outdated lamplighters.
  3. Progress often comes with loss. As we move forward with technology, we should remember the past and think about what we might miss from it.

The zero-shot trap

Generating Conversation • 93 implied HN points • 05 Mar 26
🕹 Technology AI
  1. Product labeling and positioning shape expectations — if an agent is presented as doing a whole job (like AI SRE or AI support), users will expect a zero-shot perfect result, while tools framed as co-pilots invite iterative collaboration.
  2. Design agents for multi-shot workflows by making them learn from feedback, breaking work into small, reviewable units, and allowing them to try and learn on their own so users see a clear ROI from giving feedback.
  3. Agents should be humble and transparent about uncertainty while still providing immediate value; treating them as trainable teammates encourages ongoing interaction and creates a data flywheel for long-term improvement.

THE GUEST WHO NEVER LEFT

Big Tech • 515 implied HN points • 26 Jan 26
🕹 Technology AI
  1. Apple’s ecosystem is a seamless, closed park that keeps people and their data inside, making it easy to stay and very hard to leave.
  2. Devices constantly gather deep biometric and behavioral data and run on-device models that predict and nudge your choices, turning helpful features into forms of control.
  3. Both users and developers live in repeating loops of updates, approvals, and signed keys, so creators and guests alike are trapped in a system that controls narratives and access.

LLMs: Dishonest, unpredictable and potentially dangerous.

Marcus on AI • 10473 implied HN points • 22 Jun 25
🕹 Technology AI
  1. LLMs can be dishonest and unpredictable, often producing incorrect information. This makes them risky to rely on for important tasks.
  2. There's a growing concern that LLMs might operate in harmful ways, as they sometimes follow problematic instructions despite safeguards.
  3. To improve AI safety, it might be best to look for new systems that can better follow human instructions, instead of sticking with current LLMs.

UX Roundup: Old vs New UX | Adam Smith Predicts AI | AI Video | AI Agents

Jakob Nielsen on UX • 32 implied HN points • 16 Mar 26
🕹 Technology AI
  1. Most recent UX books still teach pre-AI practices, but designers now need AI-first methods like reversed creative workflows, generative UIs, and designing for AI agents or UI-less experiences.
  2. AI is acting as a new form of capital that will massively boost cognitive productivity, causing short-term job displacement but long-term abundance; people’s economic value will shift toward orchestrating AI and roles requiring empathy, judgment, and creativity.
  3. Agentic commerce will progress from simple checkout automation to full anticipation of needs, and scaling it safely requires interoperable standards and shared financial infrastructure so many agents and businesses can transact together.

9-9-6-0

benn.substack • 1968 implied HN points • 28 Nov 25
🕹 Technology AI
  1. There is a lot of debate about whether the AI boom is just a bubble. Some experts think companies are overvalued, while others see potential for growth.
  2. Many tech workers are putting in extreme hours, often without a good work-life balance. The pressure to succeed is intense, leading to a '996' work culture.
  3. When the AI bubble bursts, it could lead to big losses for individuals in this crowded market. Some people will succeed, but many might find that their hard work didn’t pay off.

On shovels, Nvidia, and the AI Gold Rush

Marcus on AI • 2410 implied HN points • 20 Nov 25
💼 Business AI
  1. Nvidia reported excellent earnings that briefly lifted the stock, but the opening gains evaporated and the share price was down later in the day.
  2. The market reaction was highly volatile and uncertain, and nobody knows whether the stock will head up, down, or stay sideways next.
  3. Even with strong results, lingering concerns about outlook or valuation persist, so investors remain cautious.

AI Took Control of My Life and I Love It

Common Sense with Bari Weiss • 658 implied HN points • 23 Jan 26
🕹 Technology AI
  1. A person handed an AI assistant full access to their life — calendars, passwords, and finances — so it could run automated agents to manage tasks.
  2. Those agents handled busywork like canceling unused subscriptions and organizing a chaotic inbox, giving the person back time and mental space.
  3. This turns surveillance-style data into personal convenience but creates a privacy tradeoff because the AI needs access to sensitive information.

Behind AI #7: Top Python Libraries Any AI Enthusiast Should Know

Artificial Corner • 138 implied HN points • 09 Oct 24
🕹 Technology AI
  1. Python is a key language for AI because it has many useful libraries for tasks like data collection, cleaning, and visualization. Learning these libraries can help you work effectively on AI projects.
  2. For data collection, libraries like Requests and Beautiful Soup are useful for web scraping. If you need to handle JavaScript-driven sites, Selenium and Scrapy are great options.
  3. To visualize data, Matplotlib and Seaborn can help you create standard plots, while Plotly and Bokeh allow for interactive visualizations, making your data easier to understand.

Claude Charts 101: The Complete Guide to Interactive Visualizations + 60 Copy-Paste Prompts

The Product Channel By Sid Saladi • 23 implied HN points • 17 Mar 26
🕹 Technology AI
  1. Claude can generate interactive, inline visualizations — charts, diagrams, flowcharts and widgets — built with HTML/SVG so you can click, hover, and change parameters right inside the chat.
  2. It’s easy and conversational: ask for a visual or nudge with prompts like “Chart this data,” then tweak sliders, toggles, or request updates and Claude will modify the visual on the fly.
  3. The feature is available to all plans (including free), is meant for ephemeral in-chat thinking, and you can export or save visuals as images, SVG/HTML, or artifacts when you need a permanent copy.

What even is an 'AI growth zone', anyway?

Odds and Ends of History • 469 implied HN points • 06 Feb 26
🕹 Technology AI
  1. AI Growth Zones are basically a push to build more domestic data centres so the UK has its own ‘sovereign’ compute capacity, and the government pairs that build-out with a levelling-up story to attract private investment.
  2. The scheme offers targeted incentives—planning fast-tracks, grid queue priority, expert support, energy discounts, £5m for local AI adoption and retention of business-rate growth—to make specific sites more attractive to data-centre companies.
  3. In practice sites are chosen mainly for existing grid capacity or on-site power rather than to create big local tech clusters, so the actual local economic uplift and jobs impact may be smaller than the rhetoric suggests.

Data Centers Are Not the Villain

Common Sense with Bari Weiss • 505 implied HN points • 29 Jan 26
🕹 Technology AI
  1. Data centers are often blamed for high power bills and environmental damage, but most of those claims aren't true.
  2. The real driver of rising electricity costs is years of underinvestment in power infrastructure, not new data center construction.
  3. Public and political opposition to data centers has grown across the political spectrum, sparking local fights and calls to restrict or pause building.

On Brian Cantwell Smith and the Promise of AI

AI: A Guide for Thinking Humans • 342 implied HN points • 10 Feb 26
🕹 Technology AI
  1. AI excels at calculative “reckoning” tasks but lacks human “judgment” — the ethically grounded, situation-sensitive deliberation — and relying on reckoning where judgment is needed is dangerous.
  2. Genuine intelligence requires registering the world through engagement: forming objects, relations, a world model, and a sense of self that makes differences matter; current systems lack that commitment and selfhood.
  3. We need new conceptual tools and a careful map of intelligence to understand AI’s strengths and limits and to decide which tasks should be assigned to people versus machines so deployment is safe and sensible.

✨ AI agents are a real thing and doing real work

Faster, Please! • 1005 implied HN points • 08 Jan 26
💼 Business AI
  1. AI agents are already automating routine office work and delivering measurable productivity gains inside companies. They handle tasks like quoting, order creation, and reconciliations at scale, saving time and labor.
  2. Big tech and cloud providers are pouring huge sums into AI infrastructure, so the industry is financially committed to getting returns even if superintelligence is farther off. That massive investment shifts the debate from if AI will matter to how those costs will pay off in practice.
  3. The impact is broad across logistics, finance, and customer service, where agents let firms do more with the same staff and decouple headcount from volume. That means slower hiring and fewer routine clerical roles, with remaining jobs shifting toward oversight and exception handling.

Google Becomes AT&T

Dana Blankenhorn: Facing the Future • 59 implied HN points • 17 Oct 24
🕹 Technology AI
  1. Google is struggling with its search service, similar to how AT&T failed in the past. They are facing a lot of pressure from new AI technologies.
  2. The company is spending a huge amount of money to fix its issues but still losing ground to competitors. This is making it hard to maintain their position in the search market.
  3. There's a call for government intervention to save the internet and possibly break up Google, as many believe the current setup is damaging and not serving users well.