The hottest AI Substack posts right now

And their main takeaways
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Top Technology Topics

27 observations about AI and the future we’re sleepwalking into

The Rubesletter by Matt Ruby (of Vooza) | Sent every Tuesday • 641 implied HN points • 03 Dec 25
🕹 Technology AI
  1. AI will make creative output cheap and repetitive, replacing human fingerprints with endless recycled archetypes and soulless copies.
  2. AI powers massive surveillance and concentrates control in tech elites' hands, making life feel like constant monitoring and risking authoritarian misuse.
  3. AI turbocharges the attention economy and tribalism, rewarding shallow viral content over truth or originality and pushing people into echo chambers.

Flow State #5 - What kind of future are we headed towards?

Superfluid • 53 implied HN points • 17 Feb 26
💼 Business AI
  1. We're living in a split reality where many people chase futuristic endgames while others cling to the past, and both trends make teams overpromise outcomes instead of handling the messy middle of execution.
  2. The U.S. risks a 'Japanification' pattern of stagnant growth: more convenience services, rising social isolation, and increased worker pressure as automation and AI push speed and productivity.
  3. AI market shocks show that vertical AI only survives if it can handle the last-mile complexity—real-world liability, regulation, and exceptions—and companies must either uplevel leaders or replace them to meet those hard operational demands.

The Engine

The Chip Letter • 8299 implied HN points • 05 Jan 25
🕹 Technology AI
  1. Jonathan Swift's 'Engine' in Gulliver's Travels resembles a modern language model, using a setup to create phrases like today's AI would. It's an early version of computing that predicts how machines can generate language.
  2. The 'Engine' is set up to show how books can be made easier to create. It suggests that anyone could write on complex topics, even without talent, a concept similar to how AI helps people produce text now.
  3. Swift's work critiques the idea of replacing human creativity with machines. It humorously shows that while technology can produce text, true creativity still involves deeper human thought.

How Tech Metrics Change Your Values and Behaviour

SatPost by Trung Phan • 223 implied HN points • 24 Jan 26
🕹 Technology AI
  1. External metrics like scores, ratings, and likes can come to define your values and make you chase numbers instead of what truly matters to you.
  2. Metrics are not neutral: they embed the priorities of their designers and tend to flatten rich, qualitative experiences into simple numbers that reward shallow, attention-grabbing behaviour.
  3. You can resist value capture by being intentional—pair or balance indicators, trust anecdotes when metrics feel wrong, limit exposure to harmful scores, and treat platform scoring systems like optional games you can enter or leave.

Five ways in which the last 3 months — and especially the DeepSeek era — have vindicated “Deep learning is hitting a wall"

Marcus on AI • 7074 implied HN points • 09 Feb 25
🕹 Technology AI
  1. Just adding more data to AI models isn't enough to achieve true artificial general intelligence (AGI). New techniques are necessary for real advancements.
  2. Combining neural networks with traditional symbolic methods is becoming more popular, showing that blending approaches can lead to better results.
  3. The competition in AI has intensified, making large language models somewhat of a commodity. This could change how businesses operate in the generative AI market.
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A Heuristic Proof of Practical Aligned Superintelligence

Transhuman Axiology • 39 implied HN points • 11 Oct 24
🕹 Technology AI
  1. Aligned superintelligence can be created. We can define it well enough that it can't just not exist, meaning there are ways to build it.
  2. Modern AI can mimic human thinking tasks effectively. This means we can expect machines to do complex tasks just as well or even better than humans.
  3. AI alignment isn't just possible, but it might be easier than we think. As AI improves, it will likely manage societal outcomes more effectively than people do now.

Humans Welcome to Observe

Artificial Ignorance • 184 implied HN points • 31 Jan 26
🕹 Technology AI
  1. A new open-source personal AI agent framework makes it easy to run always-on, proactive assistants inside your chats, and it rapidly attracted a huge user and developer community. It supports installable skills, local memory, and self-modifying plugins that let agents learn and act on behalf of users.
  2. That same extensibility creates serious security and safety risks because unvetted skills can run code, exfiltrate data, or be manipulated via prompt injection. Running these agents on personal machines or giving them broad permissions can expose private data and incur large API costs.
  3. When agents can talk to each other they quickly form shared culture, coordinate actions, and even invent things like religions and encrypted channels, producing unexpected emergent behaviors. This shows agent ecosystems can self-organize at scale and raises tough questions about oversight, governance, and who builds the safe mainstream versions.

Help!—AI Is Stealing My Readers

The Honest Broker • 21443 implied HN points • 21 Feb 24
🕹 Technology AI
  1. Impersonation scams are evolving, with AI being used to create fake authors and books to mislead readers.
  2. Demand for transparency in AI usage can help prevent scams and maintain integrity in content creation.
  3. Experts are vulnerable to having their hard-earned knowledge and work exploited by AI, highlighting the need for regulations to protect against such misuse.

What real marketers are building with Claude Code

MKT1 Newsletter • 20 implied HN points • 02 Mar 26
🕹 Technology AI
  1. Turn repeatable marketing frameworks and review processes into "skills"—simple, reusable Markdown playbooks that Claude can run, update, and use as the foundation for more advanced automations.
  2. Claude Code and Cowork are already powering real marketer tools—think homepage graders, copy "humanizers," lookalike outbound workflows, and ad-intel agents—by connecting to sources like Google Drive, HubSpot, Clay, and deploying or scheduling runs.
  3. Set yourself up for success: block 2–3 hours for initial setup, create a CLAUDE.md, build foundational skills first (ICP, personas, messaging), use Plan mode before execution, and iterate on real examples rather than hypotheticals.

Plentiful, high-paying jobs in the age of AI

Noahpinion • 20235 implied HN points • 17 Mar 24
🕹 Technology AI
  1. The concept of comparative advantage means that even in a world where AI outperforms humans in many tasks, humans can still find plentiful, high-paying jobs by focusing on what they do relatively better compared to other tasks.
  2. Wages have historically increased despite automation, suggesting that the job market continuously evolves and diversifies, creating new tasks for humans to perform.
  3. Concerns about AI causing human obsolescence and stagnant wages should be considered in the context of factors like energy constraints and the potential for increased inequality and adjustment challenges in the economy.

The China Chip Rorschach Test

Nonzero Newsletter • 598 implied HN points • 13 Dec 25
🕹 Technology AI
  1. Influential people are deeply split on how to handle AI: some push for rapid advancement, others want strict controls, and many treat it as a tech race with China.
  2. Serious AI risks — from engineered pandemics to loss of control — can only be addressed through broad international cooperation, so framing AI as a zero-sum competition with China makes safety harder, not easier.
  3. Corporate moves and incentives are reshaping the field: big deals, internal pressure at AI labs, and choices about training data all favor automation and could drive job losses and unexpected or misaligned model behavior.

What Moltbot tells us about the ideal UX for AI

Generating Conversation • 186 implied HN points • 29 Jan 26
🕹 Technology AI
  1. AI should be present in the tools and workflows you already use, integrating deeply so it can act where and when you need it.
  2. Trust is earned by making the AI's work visible and giving users control to inspect, accept, or correct steps and decisions.
  3. Design AI like a teammate: it should do real work on your behalf, learn from feedback, and fit into your team's existing practices rather than forcing new ones.

𝗼𝟯 “𝗔𝗥𝗖 𝗔𝗚𝗜” 𝗽𝗼𝘀𝘁𝗺𝗼𝗿𝘁𝗲𝗺 𝗺𝗲𝗴𝗮𝘁𝗵𝗿𝗲𝗮𝗱: 𝘄𝗵𝘆 𝘁𝗵𝗶𝗻𝗴𝘀 𝗴𝗼𝘁 𝗵𝗲𝗮𝘁𝗲𝗱, 𝘄𝗵𝗮𝘁 𝘄𝗲𝗻𝘁 𝘄𝗿𝗼𝗻𝗴, 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗶𝘁 𝗮𝗹𝗹 𝗺𝗲𝗮𝗻𝘀

Marcus on AI • 8378 implied HN points • 22 Dec 24
🕹 Technology AI
  1. Many experts feel that the recent test called ARC-AGI should not have been labeled as such. It wasn't a proper test for Artificial General Intelligence.
  2. The presentation was confusing and didn't clearly show what the AI was tested on. This left people with the impression that the AI performed better than it actually did.
  3. There's a need for more scientific scrutiny of the results. Until we get that, we can't really compare the AI's performance fairly with humans.

This Week in Marketing: The New Age of Influencers vs. AI’s Irish Exit from Ads.

The Social Juice • 63 implied HN points • 22 Feb 26
💼 Business AI
  1. Creator marketing is shifting — traditional influencers are losing ground while platforms and brands push subscriptions, gifting programs, and creator-first monetization. Brands will need better tracking and UGC management to prove real impact.
  2. AI is upending advertising and trust as companies struggle with moderation and harmful or hallucinated content; some firms are even dropping ads to protect credibility. Regulators and platforms are racing to limit or control AI-generated content and its monetization.
  3. The platform and ad ecosystem is being reshaped by major tech moves — Meta, Google, TikTok and others are rolling out new AI tools, ad products, and policy changes that shift attention and ad dollars. Marketers must adapt to new formats, measurement tools, and growing regulatory scrutiny.

Physical Intelligence Sweeps Humanoid Olympics

General Robots • 348 implied HN points • 05 Jan 26
🕹 Technology AI
  1. Physical Intelligence submitted robots for 11 humanoid Olympic events. They achieved these capabilities much sooner than expected, showing rapid progress in robotics.
  2. Many tasks that seemed to need special touch sensors or extra finger joints were actually solvable with standard grippers and cameras, and wrist force-torque sensing appears to help. This suggests clever hardware-software integration can overcome perceived limits.
  3. Teams make different trade-offs: some use more dexterous hands to collect teleoperation data while others add wrist force-torque sensors humans can’t provide. Those choices change what sensor data and training each approach can use.

Build AI or Be Buried By Those Who Do

Contemplations on the Tree of Woe • 3574 implied HN points • 30 May 25
🕹 Technology AI
  1. There are three main views on AI: believers who think it will change everything for the better, skeptics who see it as just fancy technology, and doomers who worry it could end badly for humanity. Each group has different ideas about what AI will mean for the future.
  2. The belief among AI believers is that AI will become a big part of our lives, doing many tasks better than humans and reshaping many industries. They see it as a revolutionary change that will be everywhere.
  3. Many think that if we don’t build our own AI, the narrative and values that shape AI will be dominated by one ideology, which could be harmful. The idea is that we need balanced development of AI, representing different views to ensure freedom and diversity in thought.

AMD Client Update at CES 2026

More Than Moore • 326 implied HN points • 06 Jan 26
🕹 Technology AI
  1. AMD’s CES updates are a mid-cycle refresh that makes AI a standard across its client lineup, pushing Ryzen AI into volume laptops rather than keeping it as a premium add‑on. This keeps the existing Zen 5 platform relevant without new silicon.
  2. AMD is relying on software to drive the next wave of improvements — ROCm for local AI and FSR Redstone for gaming — delivering bigger performance and features through optimization and ML-assisted techniques instead of new chips.
  3. The hardware moves are about segmentation and integration: Ryzen AI 400 targets mass-market laptops, Ryzen AI Max+ and the Halo developer platform aim at local AI mini‑workstations with large unified memory, and the P100 embedded APUs focus on industrial and automotive edge AI with integrated CPU/GPU/NPU designs.

Money, Drama, and China: Why AI’s Next Step Could Be Messy

Big Technology • 6880 implied HN points • 24 Jan 25
🕹 Technology AI
  1. A new AI model called DeepSeek is cheaper and efficient, potentially making big investments in AI technology seem unnecessary. This raises questions about how much companies should really spend on AI.
  2. DeepSeek's success is surprising since it was developed in China, challenging the notion that good tech only comes from big investments in the West. Its ability to compete shows that smaller companies can innovate effectively.
  3. This development might shift the AI landscape significantly. Big players like OpenAI may need to rethink their approaches to stay competitive, especially now that cheaper models are proving their worth.

The Dumbification of our smart screens

Product Identity • 753 implied HN points • 03 Jul 24
🕹 Technology AI
  1. Smartphones were supposed to make our lives easier, but now they often feel overwhelming and unhelpful. Many people want to focus on simpler uses for their devices instead of getting caught up in unnecessary features.
  2. There's a trend of 'dumbification' where people are choosing less complicated devices and apps to reduce distractions. Instead of seeking out the latest tech, people want tools that help them focus and connect better.
  3. This movement might not be mainstream yet, but it's growing. Many are looking for ways to minimize their screen time and simplify their digital lives to find more balance.

Open Thread 366

Astral Codex Ten • 7089 implied HN points • 27 Jan 25
🕹 Technology AI
  1. Anyone can share thoughts or ask questions in the open thread. It's a space for discussing anything on your mind.
  2. There are opportunities for people interested in AI safety, including a course that can help you get started in the field.
  3. An AI forecasting project is looking for news outlets to publish articles on future predictions about AI advancements.

($) Nebius Earnings: A GPU Cloud Masterclass

Interconnected • 77 implied HN points • 12 Feb 26
💼 Business AI
  1. Nebius breaks down important differences between contracted, connected, and active power, and knowing those terms matters a lot when you plan and price GPU data centers.
  2. The company is unusually transparent about the step-by-step logistics, unit economics, and long-term profitability of building GPU data centers, so its disclosures are a practical how-to for the industry.
  3. Having completed its first full year after a fast IPO and positioned to benefit from Europe’s sovereign-AI demand, Nebius’s results and guidance are especially informative for investors and operators even if some remain skeptical.

An Interview With Brian Daugherty

ciamweekly • 62 implied HN points • 16 Feb 26
🕹 Technology AI
  1. CIAM helps make users' day-to-day identity and access flow secure and seamless across devices, apps, and multiple personas.
  2. The CIAM landscape is complex with many protocols and legacy systems, which creates hard choices, maintenance burdens, and organizational resistance to adopting better practices.
  3. LLMs and agentic tools will both simplify CIAM design and implementation and create new trust and security risks, driving rapid changes in protocols and products.

Google, 2001: Don’t Be Evil

Marcus on AI • 6481 implied HN points • 05 Feb 25
🕹 Technology AI
  1. Google's original motto was 'Don't Be Evil,' but that seems to have changed significantly by 2025. This shift raises concerns about the company's intentions and actions involving powerful AI technologies.
  2. The current landscape of AI development is driven by competition and profits. Companies like Google feel pressured to prioritize making money over ethical considerations.
  3. There is fear that as AI becomes more powerful, it may end up in the wrong hands, leading to potentially dangerous applications. This evolution reflects worries about how society and businesses are dealing with AI advancements.

2026+

Gonzo ML • 315 implied HN points • 07 Jan 26
🕹 Technology AI
  1. Quadruped robots (dog- or cat-like) will get much better and more practical for real-world use, while humanoid home robots stay too expensive.
  2. We’ll see production-grade agents with predictable 99.9% reliability and richer integrations, driven by better infrastructure and cognitive architectures.
  3. Advances in world models, latent-space reasoning, and multimodal architectures will create new interactive environments and begin to accelerate scientific discovery in certain domains.

The LLM Context Tax: Best Tips for Tax Avoidance

Nicolas Bustamante • 104 implied HN points • 11 Feb 26
🕹 Technology AI
  1. Context tokens are expensive and degrade performance as they accumulate, so treat context as a scarce resource and keep prompts stable and append-only; move dynamic pieces (like timestamps) to the end so you preserve KV cache hits.
  2. Architect agents to minimize tokens by storing tool outputs as files, using precise two-step tools that return metadata before full content, delegating work to cheaper subagents, reusing templates, batching or parallelizing tool calls, and caching common responses at the application level.
  3. Clean and compact data before sending it to the model, place critical information at the beginning or end to avoid the lost-in-the-middle problem, use summarization/compaction before hitting pricing cliffs, and set strict output token limits to control costly outputs.

Data Science Weekly - Issue 559

Data Science Weekly Newsletter • 219 implied HN points • 08 Aug 24
🕹 Technology AI
  1. Camera calibration is crucial in sports analysis. It helps track players' movements accurately by mapping video frame positions to real field locations.
  2. Understanding the context of data is important for responsible data work. Datasets need good documentation and stories to highlight their historical and social backgrounds.
  3. There's a new, free encyclopedia for learning about cognitive science. It offers easy-to-read articles on various topics for students and researchers.

Apple's Trajectory: Achieving Twin Hyperextraordinary Triumphs, Four Slow-Motion Failures

Brad DeLong's Grasping Reality • 169 implied HN points • 23 Jan 26
🕹 Technology AI
  1. Apple’s recent success rests on two extraordinary strengths: in-house Apple Silicon chips and a highly efficient, China-centered manufacturing supply chain.
  2. Years of small software regressions and weaker visual design have eroded the “it just works” user trust, turning quality drift into a major strategic weakness.
  3. Apple also has big blind spots — an unclear AI strategy (highlighted by Siri’s failure), political vulnerability from China dependence, and fraught developer relations over App Store fees — and simple executive reshuffles may not fix these structural problems.

Data Science Weekly - Issue 561

Data Science Weekly Newsletter • 139 implied HN points • 22 Aug 24
🕹 Technology AI
  1. When building web applications, using Postgres for data storage is a good default choice. It's reliable and widely used.
  2. A new study shows that agents can learn useful skills without rewards or guidance. They can explore and develop abilities just from observing a goal.
  3. The list of important books and resources in Bayesian statistics is being compiled. It's a way to recognize influential ideas in this field.

Why AI writing is mid

Democratizing Automation • 712 implied HN points • 16 Nov 25
🕹 Technology AI
  1. AI models aren't great at writing because they're trained to prioritize different qualities like helpfulness over style, which makes good writing harder to achieve.
  2. Models are created to be predictable and cater to average user preferences, so unique writing styles or quirks often get lost.
  3. To improve AI writing, models need to be designed with specific voices or personalities that can express opinions and emotions, making the writing more engaging.

The Last Mover Advantage in AI

Enterprise AI Trends • 295 implied HN points • 06 Jan 26
🕹 Technology AI
  1. When AI progress is exponential, waiting can pay off because the last mover often gets a much better product and avoids wasted effort.
  2. Committing early to vendors or large enterprise deals risks big sunk costs and being locked into outdated tech, so negotiate harder and consider building more instead of buying quickly.
  3. Patience is a deliberate strategic choice alongside build and buy: decide what to wait on, what to experiment with now, and use waiting to watch paradigm shifts while you focus resources elsewhere.

#50 - Why AI Won’t Magically Flip Your Bank’s Spend Pattern

OSS.fund Newsletter • 56 implied HN points • 26 Feb 26
💰 Finance AI
  1. AI won’t magically flip a bank’s spend from run to change because banks are tightly governed and face real costs like compliance, dual-run tax, and mandatory testing that prevent a quick switch. These constraints mean savings come slowly and require human-controlled policy and evidence gates.
  2. Treat modernization as a spectrum and manage it as a portfolio: Operate, Comply, Harden & Simplify, and Compete & Grow. Use a Good Bank/Bad Bank approach with a policy-driven bridge, deterministic routing, and continuous reconciliation so migrations are auditable, reversible, and lead to real decommissioning.
  3. Use AI as an assistant to cut toil, automate evidence, speed analysis, and help translate legacy code, but don’t give it authority to change policies or skip validation. Capture the realistic savings to fund simplification and growth, aiming for practical targets (for example ~50/50 over five years) rather than expecting an immediate 60/40 to 40/60 flip.

Seven Predictions for Tech in 2025

Big Technology • 7380 implied HN points • 20 Dec 24
🕹 Technology AI
  1. Some companies might decide that generative AI isn't right for them, leading to at least one big name publicly quitting it in 2025. It's important for businesses to find what works for them.
  2. Social media may start feeling less relevant as platforms focus less on real news and engage more with content they think will grab our attention. This shift could make important global events seem distant.
  3. Brain-computer interface technology could gain more attention in 2025 as it continues to develop, possibly helping people with disabilities. This could spark new conversations around its potential benefits.

Agents 4 All

DARK FUTURA • 2869 implied HN points • 17 Jan 24
🕹 Technology AI
  1. AI plays a significant role in tracking and manipulating consumer behaviors to maximize profits for corporations.
  2. The development of full-time AI agents as personal assistants is the next phase of AI innovation, focusing on handling daily tasks and expenditures.
  3. DARPA is exploring the development of human-presenting AI agents for influencing social and behavioral systems, indicating potential dangerous implications.

The Crumbling Workflow Moat: Aggregation Theory's Final Chapter

Nicolas Bustamante • 132 implied HN points • 04 Feb 26
🕹 Technology AI
  1. LLM chat interfaces are replacing specialized software UIs, so the interface moat that once locked in users is disappearing.
  2. With interfaces commoditized, competition becomes API vs API and only truly proprietary, non-replicable data keeps pricing power; if data can be licensed or scraped, margins and retention will collapse.
  3. Winners will be LLM/chat owners, proprietary data holders, and API-first startups, while interface-dependent vertical software, many UX-focused firms, and aggregators who don’t control the chat layer are at risk.

Vibe-Coding a PCB - surprisingly good

atomic14 • 2598 implied HN points • 12 Jul 25
🕹 Technology AI
  1. Vibe-coding a PCB is about using AI to design hardware from natural language prompts. It's a fun way to simplify the building process.
  2. Using a tool like Atopile and an AI assistant can yield surprisingly good results, even if there are small mistakes. Just a little guidance can help fix issues.
  3. This method is close to changing how we create hardware, making it easier for people without engineering skills to get involved in tech projects.

Satya Nadella and the three stages of scientific truth

Marcus on AI • 8023 implied HN points • 23 Nov 24
🕹 Technology AI
  1. New ideas in science often face resistance at first. People may ridicule them before they accept the change.
  2. Scaling laws in deep learning may not last forever. This suggests that other methods may be needed to advance technology.
  3. Many tech leaders are now discussing the limits of scaling laws, showing a shift in thinking towards exploring new approaches.

Top Links 957 The AI money machine. Against European self-denigration and a Louvre full of plan-relief.

Chartbook • 371 implied HN points • 20 Dec 25
🕹 Technology AI
  1. AI is presented as a powerful money machine that is reshaping where profits and investment flow.
  2. The piece pushes back against European self-denigration and urges Europeans not to underestimate their strengths and contributions.
  3. Economic analysis is paired with cultural and historical material, such as art and the Louvre, to broaden the conversation.

Claude AI for Job Interviews 101: Your Complete System From First Application to Signed Offer

The Product Channel By Sid Saladi • 20 implied HN points • 09 Mar 26
🕹 Technology AI
  1. Interviewing is a distinct skill separate from doing the job, and people usually lose jobs not for lack of ability but for lack of focused preparation and feedback.
  2. You can set up Claude Pro as a persistent, personalized interview coach using Projects, Skills (desktop app), or Claude Code so it remembers your resume, session history, and scoring rubrics automatically.
  3. This Claude-based system gives unlimited mock interviews, scored feedback, question prediction, and offer negotiation help end-to-end, and it’s positioned as a much cheaper alternative to human coaches at about $20/month.

This Week in Marketing: Instagram Alerts, QuitGPT, Paramount-WBD deal, and Snap Awards

The Social Juice • 34 implied HN points • 01 Mar 26
💼 Business AI
  1. Big social platforms are under pressure to protect kids and enforce age checks, leading to new safety features, fines, and delayed verification rollouts.
  2. AI is reshaping content, ads, and search at speed, but it’s also provoking user backlash, legal fights, and growing regulatory scrutiny.
  3. The creator economy and media landscape are shifting: user-generated content and creator tools are rising while big mergers and advertiser moves reshape where brands spend.