The hottest AI Substack posts right now

And their main takeaways
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Top Technology Topics

The hard thing about building AI applications

Generating Conversation • 140 implied HN points • 27 Feb 25
🕹 Technology AI Software Innovation Product Design User Experience
  1. Good AI should figure things out for you before you even ask. It should make your life easier by anticipating what you need without requiring a lot of input.
  2. Trust is key for AI systems. They should be honest about what they don't know and explain their level of confidence. This helps users rely on them more.
  3. AI should take complex information and boil it down to what's important and easy to understand. It should help you find insights quickly without overwhelming you with details.

The Knowledge Illusion

In Bed With Social • 416 implied HN points • 27 Oct 24
🚌 Education Learning Knowledge Technology AI Critical Thinking
  1. AI can provide quick answers, but this doesn't lead to real understanding. It's important to engage in learning actively to truly grasp the knowledge.
  2. The value of knowledge is changing with technology. While access to information is easier now, it can lead to shallow thinking if we rely on AI too much.
  3. Learning should be about growth, not just getting answers. We should use AI to inspire deeper questions and foster our critical thinking instead.

On OpenAI's Model Spec 2.0

Don't Worry About the Vase • 985 implied HN points • 21 Feb 25
🕹 Technology AI Machine Learning Software Development Data Ethics Tech Policy
  1. OpenAI's Model Spec 2.0 introduces a structured command chain that prioritizes platform rules over individual developer and user instructions. This hierarchy helps ensure safety and performance in AI interactions.
  2. The updated rules emphasize the importance of preventing harm while still aiming to assist users in achieving their goals. This means the AI should avoid generating illegal or harmful content.
  3. There are notable improvements in clarity and detail compared to previous versions, like defining what content is prohibited and reinforcing user privacy. However, concerns remain about potential misuse of the system by those with access to higher-level rules.

‘We Were Wrong’

Magic + Loss • 159 implied HN points • 29 Oct 24
🕹 Technology Internet Media AI Nostalgia Culture
  1. WIRED's first website, HotWired, launched the digital age by covering topics that traditional media missed. It helped introduce many people to the online world.
  2. The internet has evolved into a chaotic space filled with dangers like misinformation, cybercrime, and trolls. This raises the question of whether it was handled well from the start.
  3. Even though WIRED helped shape the internet, it recognizes its role in the problems that have emerged over the years and reflects on how things might have been different.

Prompting is Managing

Breaking Smart • 125 implied HN points • 19 Jun 25
🕹 Technology AI Management Education Cognition Research
  1. Using AI tools like chatbots is similar to managing interns. It's not about doing the work yourself but overseeing the process.
  2. Focusing on sameness in writing can help maintain quality, but it may also limit creativity. Good management knows when to stick to the rules and when to encourage originality.
  3. We need to change how we teach writing and management skills for the AI era. It’s important to build skills for overseeing new technologies rather than just avoiding them.
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AI-generated Anki cards are not to be trusted

De Novo • 121 implied HN points • 13 Jun 25
🚌 Education Learning Memory Technology AI Biology
  1. AI-generated Anki cards can have mistakes that may lead to learning incorrect information. It's important to double-check AI content, especially on complex topics.
  2. Relying on AI for learning new material may not be wise, as it could lead to errors that are not obvious at first glance.
  3. Even when asking different AI systems to review the same content, they can miss errors or indicate correct information as wrong. Human oversight is crucial.

Using AI: Queries, Conversations, and Projects

In My Tribe • 303 implied HN points • 11 Jun 25
🕹 Technology AI Machine Learning Human-computer interaction Software Development Educational Technology
  1. A conversation with AI is different from simply asking a question. You can explore topics more deeply and learn from the back-and-forth interaction.
  2. Using AI for projects is essential to becoming skilled with it. It’s like doing a group assignment, where you can create something together.
  3. Providing clear instructions and materials to AI helps it assist you better. Treating it like a partner, rather than just a tool, can lead to better results.

The Mask Comes Off: A Trio of Tales

Don't Worry About the Vase • 2150 implied HN points • 14 Feb 25
🕹 Technology AI Innovation Ethics Safety Regulations
  1. Sam Altman presents an overly optimistic view of AI's future while downplaying its risks. He talks about amazing advancements but doesn't address the potential dangers seriously.
  2. OpenAI claims it can design AI to complement humans instead of replacing them, but that seems unrealistic. Many believe there is no solid plan to prevent job losses caused by AI.
  3. Elon Musk's recent bid for OpenAI's nonprofit is more about raising its value than actually buying it. This move highlights concerns about how AI's future will be managed and whether profit motives will overshadow safety.

AI #103: Show Me the Money

Don't Worry About the Vase • 2374 implied HN points • 13 Feb 25
🕹 Technology AI Software Data Innovation Automation Regulation
  1. The Paris AI Anti-Safety Summit failed to build on previous successes, leading to increased concerns about nationalism and lack of clear plans for AI safety. It's making people worried and hopeless.
  2. Elon Musk's huge bid for OpenAI's assets complicates the situation, especially as another bid threatens to overshadow the original efforts to secure AI's future.
  3. OpenAI is quickly releasing new versions of their models, which brings excitement but also skepticism about their true capabilities and risks.

HOISTED FROM COMMENTS: RAFAEL KAUFMANN: Carving Nature at the Joints: Faithful Representation, the Platonic Dream, & the Unreasonable Near-Success of GPT LLM MAMLMs

Brad DeLong's Grasping Reality • 69 implied HN points • 25 Jun 25
🕹 Technology AI Machine Learning Philosophy Data science Automation
  1. Machines, like large language models, can imitate human language because they find patterns hidden in how we express ourselves. They simplify the chaos of our words into something easier to understand.
  2. Even though these models are good at predicting responses, they struggle with truly understanding the world. They can replicate language well, but grasping the deeper meaning remains a challenge.
  3. The hope is that with better training and understanding causal relationships, these models could evolve to not only imitate but truly comprehend the world around them.

Immortality and its Discontents

Nonzero Newsletter • 225 implied HN points • 28 Feb 25
🕹 Technology AI Health Philosophy Politics Innovation
  1. There's a growing interest in immortality and how technology, like AI, could help us live longer. Some people believe that embracing these advancements is the key to a better future.
  2. Not everyone agrees with how some tech entrepreneurs are promoting longevity. Critics say their methods and products are often unproven and may not lead to the promised health benefits.
  3. Studies show that bad behavior learned in one area can spread to other areas, especially with AI. Just like in humans, training AI on negative examples can lead to undesirable outcomes in different contexts.

The Sequence Engineering #661: Create Your Own Deep Research Agent with DeerFlow

TheSequence • 119 implied HN points • 11 Jun 25
🕹 Technology Software AI Automation Research Development
  1. DeerFlow is an open-source tool that helps automate research tasks. It uses multiple agents to make research faster and easier.
  2. The framework can do many tasks, like searching the web and creating reports, with little help from people. This makes it very efficient.
  3. It's designed for developers and engineers who want to build research systems that can grow and adapt easily.

The Impact of the Calibration Dataset for AutoRound and AWQ Quantization

The Kaitchup – AI on a Budget • 39 implied HN points • 31 Oct 24
🕹 Technology AI Data science Machine Learning Quantization Model optimization
  1. Quantization helps reduce the size of large language models, making them easier to run, especially on consumer GPUs. For instance, using 4-bit quantization can shrink a model's size by about a third.
  2. Calibration datasets are crucial for improving the accuracy of quantization methods like AWQ and AutoRound. The choice of the dataset impacts how well the quantization performs.
  3. Most quantization tools use a default English-language dataset, but results can vary with different languages and datasets. Testing various options can lead to better outcomes.

We're Finding Out What Humans are Bad At

Am I Stronger Yet? • 799 implied HN points • 18 Feb 25
🕹 Technology AI Computing Engineering Innovation Robotics
  1. Humans are not great at some tasks, especially ones like multiplication or certain physical jobs where machines excel. Evolution didn't prepare us for everything, so machines often outperform us in those areas.
  2. In tasks like chess, humans can still compete because strategy and judgment play a big role, even though computers are getting better. The game requires thinking skills that humans are good at, though computers can calculate much faster.
  3. AI is advancing quickly and becoming better at tasks we once thought were uniquely human, but there are still challenges. Some complex problems might always be easier for humans due to our unique brain abilities.

The Lamplighter Problem

Jeff Giesea • 718 implied HN points • 22 Oct 24
🕹 Technology AI Automation Labor Economy Politics
  1. AI is likely to displace a huge number of jobs, similar to how lamplighters lost their roles when electric lights came in. We need to prepare for these changes now to help people transition to new work.
  2. The Lamplighter Problem shows us that job loss due to automation is not just an economic issue but also a political and social one. If we don’t address it, it could lead to bigger problems in society.
  3. There are different opinions on how to handle the rise of AI. Some people think we should slow down and reconsider, while others want to speed up its development. We need to find a balanced approach that helps everyone.

Talkin’ bout an AI Revolution: 3 scenarios

Faster, Please! • 365 implied HN points • 26 Feb 25
🕹 Technology AI Innovation Economics Forecasting Trends
  1. By 2030, we might still be at the start of a major AI development period. It's okay because this means we have a lot of exciting advancements ahead.
  2. More traditional institutions, like big banks, are now seriously talking about AI. This shows that AI is becoming a big deal in the mainstream world, not just in tech circles.
  3. Experts believe that as AI keeps getting better, the 2020s could see various new economic and technological changes. This could change how we live and work in many ways.

How Anthropic Builds Claude’s Personality

Big Technology • 2877 implied HN points • 29 May 25
🕹 Technology AI Chatbots Ethics Research Innovation
  1. Anthropic builds its chatbot, Claude, to have a personality similar to a friendly traveler. This means it tries to be open and adaptable when talking to different people.
  2. Instead of strict rules, Claude's behavior is based on a set of qualities, like kindness and wit, that should naturally show in all its conversations.
  3. The chatbot's personality is fine-tuned after training by using examples of what good conversation looks like, guiding it to respond in ways that reflect the desired traits.

xAI and DeepSeek Have Shattered the AI Industry’s Golden Tenet

The Algorithmic Bridge • 297 implied HN points • 26 Feb 25
🕹 Technology AI Software Innovation Industry Infrastructure
  1. AI is going through ups and downs, with some people losing trust because the hype isn't matching reality. But just like with other big inventions, these struggles are normal.
  2. There's a debate in the AI community about whether the focus should be on building more powerful models or making them work better in real life. Each approach has its supporters.
  3. Even with AI's growth, some people are still worried about its impact on their daily lives, emphasizing the need to balance development with public concerns.

Claude Plays Pokémon

Teaching computers how to talk • 62 implied HN points • 28 Feb 25
🕹 Technology AI Gaming Research Metrics Innovation
  1. AI playing games like Pokémon can show us how smart it really is. It might be better than other tests because games need quick thinking and problem solving.
  2. Recent projects like Claude playing Pokémon on Twitch highlight how slow and confused current AI can be. It took Claude a long time to beat just one part of the game.
  3. Today's AI tests often focus on math or coding, but playing games might give a clearer picture of intelligence. We should use games to see if AI can think and adapt like humans do.

What does slow AI look like?

The Sublime Newsletter • 1941 implied HN points • 12 Oct 24
🕹 Technology AI Productivity Software Human-Computer Innovation
  1. People often feel stressed because productivity tools are designed to make us work faster, but that doesn't match how we naturally want to create things.
  2. Instead of rushing to produce more content quickly, we should focus on making fewer things but doing them better and with more care.
  3. It's okay to take time in the creative process; in fact, taking time can help us create something truly wonderful.

What would a $2,000-a-month ChatGPT look like?

Enterprise AI Trends • 168 implied HN points • 19 Feb 25
🕹 Technology AI Software Pricing Enterprise Markets
  1. The future of AI will see two main pricing categories: low-end for general users and high-end for specialized, enterprise-focused users. There's not much room in the middle.
  2. High-end AI products will need to be built on strong industry knowledge and proprietary data to be successful. This means startups might struggle to compete.
  3. AI companies can charge a lot because their products provide immense value in competitive fields, where even a small advantage can lead to big profits.

#2: Search continues for someone with an opinion on AI

12challenges • 171 implied HN points • 24 Feb 25
🕹 Technology AI Startups Digital Culture Innovation
  1. There's a lot of chatter around AI, and it can feel overwhelming with so many opinions coming from everywhere. Not everyone can be right, and sometimes it’s nice to take a step back.
  2. The writer is working on making their tech publication more engaging, including designing a cool interactive button that enhances the reader experience. Adding fun elements can make a project feel exciting.
  3. Getting back into the habit of writing and sharing can be challenging, but it's important to push through and not aim for perfection. Staying persistent is key to finding your audience.

The World's Largest Search Doesn't Want You to Search

The Honest Broker • 45746 implied HN points • 19 Feb 25
🕹 Technology Search Engines AI Digital Platforms Privacy Data Management
  1. Search engines, especially Google, are moving away from their main job of helping people find information. Instead, they want to keep users on their platforms with AI results that don’t always give good answers.
  2. Google prioritizes its advertising and profitability over providing reliable search results. People often end up with low-quality information or ads instead of what they are really looking for.
  3. Many users are losing trust in Google and other big tech companies because they feel the platforms are not serving their needs. If this trend continues, it could lead to serious consequences for these companies.

The state of B2B monetization in 2025

Kyle Poyar’s Growth Unhinged • 520 implied HN points • 04 Jun 25
💼 Business Software Pricing Subscription SaaS AI
  1. Traditional pricing models like flat-rate and seat-based are losing popularity. Companies are now favoring hybrid pricing to better match value and costs.
  2. Hybrid pricing is becoming the go-to choice for software companies, providing flexibility and a better upselling opportunity while keeping it simple for customers.
  3. Outcome-based pricing is highly desired but rarely adopted because it's complicated. Most companies struggle with measuring and ensuring consistent results for customers.

While the West Hesitates China Marches Forward

The Algorithmic Bridge • 637 implied HN points • 21 Feb 25
🕹 Technology AI Innovation Government Data Globalization
  1. China is rapidly adopting AI technology, using systems like DeepSeek across government operations to improve efficiency and decision-making. This shows their proactive approach to embracing innovation.
  2. DeepSeek has emerged as a competitive AI model that rivals established Western technologies, highlighting China's growing capabilities in the tech sector. China is focused on getting results, not just discussing ideas.
  3. The cultural mindset in China emphasizes efficiency and action, contrasting with the West's tendency to debate and regulate rather than implement. This difference in attitude could impact global technological leadership.

A note on Unreported Truths and AI-written stories

Unreported Truths • 40 implied HN points • 12 Jun 25
🕹 Technology AI Content creation Social media Digital marketing Email Marketing
  1. Some writers use AI to create many posts quickly, which can spam your inbox. This is seen as a bad shift in how content is created.
  2. Real engagement comes from genuine writing. The writer promises to share meaningful content without relying on AI or spammy tactics.
  3. The writer values the community built around their work and encourages everyone to support it by subscribing, ensuring quality over quantity.

How Super Apps & Platforms Are Turning AI On Its Head

High ROI Data Science • 79 implied HN points • 30 Oct 24
🕹 Technology AI Platforms Apps Business Models Consumer behavior
  1. Super apps in Asia grow by offering many services to a smaller customer base, unlike Big Tech that focuses on single services for many users. This helps them cater better to local needs.
  2. The advantages of super apps include faster product development, lower costs for data collection, and a unique competitive edge through exclusive data. They can quickly adapt to market changes too.
  3. Wrtn, a South Korean startup, shows how a super app can combine multiple AI services into one platform. This model offers better value to users and keeps them engaged with ads instead of multiple expensive subscriptions.

10 Takeaways From Tech’s Biggest News Week of the Year

Big Technology • 3002 implied HN points • 23 May 25
🕹 Technology AI Software Innovation Business Networking
  1. AI models are still getting better with size, but people are also focusing on new algorithms to improve them. This means companies like NVIDIA will continue to thrive for now.
  2. There's a growing belief that algorithm improvements might be more important than just making AI bigger. This might change how we think about developing AI in the future.
  3. AI technology is rapidly evolving, especially in video generation and coding, which could lead to significant advancements and some ethical concerns as it becomes more powerful.

No More Forms to Fill Out

In My Tribe • 318 implied HN points • 08 Jun 25
🕹 Technology AI Software Education Communication Innovation
  1. Filling out forms is a common part of life, but it often feels outdated. Instead of forms, we could use conversations with AI to make communication easier.
  2. Using AI like Claude, teachers can upload their syllabi and have an interactive conversation to turn their ideas into structured course content. This way, the process becomes more collaborative and flexible.
  3. This new method allows for ongoing adjustments and real-time feedback, leading to a stronger connection between the content and the user's needs. It's not just about filling out information, but working together to create something meaningful.

Building a "Vertical Agent"

The Security Industry • 13 implied HN points • 24 Feb 25
🕹 Technology AI Software Security SaaS Data
  1. Vertical agents are a new trend gaining interest for their potential impact in various fields. They utilize specialized AI to cater to specific industries or tasks.
  2. AI tools like HarvestIQ.ai can assist organizations in managing their security tools and processes. They can streamline research and decision-making by providing quick insights and analysis.
  3. The future may see AI agents that fully understand an organization's needs. These agents could help businesses choose the right tools and maintain compliance more effectively.

The rise of reasoning machines

Democratizing Automation • 538 implied HN points • 12 Jun 25
🕹 Technology AI Machine Learning Computing Software Development Data science
  1. Reasoning is when we draw conclusions based on what we observe. Humans experience reasoning differently than AI, but both lack a full understanding of their own processes.
  2. AI models are improving but still struggle with complex problems. Just because they sometimes fail doesn't mean they can't reason; they just might need new methods to tackle tougher challenges.
  3. The debate on whether AI can truly reason often stems from fear of losing human uniqueness. Some critics focus on what AI can't do instead of recognizing its potential, which is growing rapidly.

Introducing RunLLM: The first AI Support Engineer

Generating Conversation • 163 implied HN points • 24 Feb 25
🕹 Technology AI Software Product Development Customer Support Productivity
  1. RunLLM is an AI designed to help support teams by managing technical questions and documentation, making the process easier for both support staff and customers.
  2. One challenge for support teams is that technical products often create complex questions that can overwhelm them. RunLLM helps lighten that load by providing quick and accurate answers.
  3. Instead of just answering questions, RunLLM engages with users, helping to boost their confidence in seeking help and improving overall customer satisfaction.

Evo 2 Can Design Entire Genomes

Asimov Press • 490 implied HN points • 19 Feb 25
🕹 Technology AI Biotechnology Genomics Computing Research
  1. Evo 2 is a powerful AI model that can design entire genomes and predict harmful genetic mutations quickly. It can help scientists understand genetics better and improve genetic engineering.
  2. Unlike earlier models, Evo 2 can analyze large genetic sequences and understand their relationships, making it easier to see how genes interact in living organisms.
  3. While Evo 2 offers exciting possibilities for bioengineering, there are also concerns about its potential misuse. It's important to handle such powerful technology responsibly to avoid harmful applications.

The End of Search, The Beginning of Research

One Useful Thing • 2047 implied HN points • 03 Feb 25
🕹 Technology AI Research Software Innovation Automation
  1. New AI Reasoners can think better and solve tougher problems by producing thinking steps before answering. This makes them more effective than earlier chatbots.
  2. AI agents are being developed to autonomously pursue goals, but they currently face limitations when tackling complex tasks. They show promise with narrow, task-specific applications.
  3. OpenAI's Deep Research represents how specialized AI can work like a human researcher by engaging deeply with academic topics, paving the way for significant advancements in research efficiency.

Google and Stage Two of the AI Boom

Dana Blankenhorn: Facing the Future • 39 implied HN points • 30 Oct 24
🕹 Technology AI Cloud Computing Data Business
  1. Nvidia's rise marked the start of the AI boom, with companies heavily buying chips for AI tools. This growth continues, and Nvidia is now a leading company.
  2. Google's cloud revenue is growing quickly at 35%, while overall revenue growth is slower at 15%. This shows strong demand for AI services from Google.
  3. Despite revenue growth, Google's search revenue isn't doing as well, rising only 12%. This could mean they are losing some of their search market share.

This Rumor About GPT-5 Changes Everything

The Algorithmic Bridge • 4788 implied HN points • 16 Jan 25
🕹 Technology AI Machine Learning Software Development Data science Tech industry
  1. There's a belief that GPT-5 might already exist but isn't being released to the public. The idea is that OpenAI may be using it internally because it's more valuable that way.
  2. AI labs are focusing on creating smaller and cheaper models that still perform well. This new approach aims to reduce costs while improving efficiency, which is crucial given the rising demand for AI.
  3. The situation is similar across major AI companies like OpenAI and Anthropic, with many facing challenges in producing new models. Instead, they might be opting to train powerful models internally and use them to enhance smaller models for public use.

Sam Altman’s GPT5 Tweet: Line by Line Analysis

Enterprise AI Trends • 295 implied HN points • 14 Feb 25
🕹 Technology AI Product Business Innovation Market
  1. GPT-5 will simplify how users interact with AI by combining different models into one. This means users won’t need to learn about what each model does, making it easier for everyone to use.
  2. There will be different levels of intelligence that users can access by paying more. This 'pay-for-sophistication' model allows users to get better answers while also helping OpenAI make more money.
  3. GPT-5 will act like a smart assistant that decides how to process user requests. This means better performance and less complexity for developers, as the AI will automatically choose the best way to respond.

We All Work for the Same Boss Now

Justin E. H. Smith's Hinternet • 950 implied HN points • 01 Jun 25
🕹 Technology AI Information Digital Culture Media Communication
  1. Technology can bring both good and bad changes, but we need to be aware of both sides. It's important not to worship or destroy new technology, but to think critically about its impact.
  2. Our current tech revolution, like the past ones, may lead to losses and hardships for many people, even as it also creates new opportunities. It's crucial to recognize that upheaval can be part of progress.
  3. The way we understand technology's role in society has shifted over time, and we must learn from history to navigate current challenges. We can't ignore the potential threats that come with new advancements.