The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

🔐 How TPMs Can AI - Dealing with Difficult Engineers and Leaders

Building Rome(s) • 9 implied HN points • 09 Aug 25
🕹 Technology AI
  1. Technical Program Managers (TPMs) can use AI tools to tackle common problems and improve their effectiveness. This approach can help them work smarter and enhance their impact.
  2. Real-world scenarios show how to deal with difficult engineering partners or leaders. These examples can inspire TPMs to think differently about their challenges.
  3. Using AI, like ChatGPT, can give TPMs various strategies tailored to their situations. Instead of just asking for solutions, they can seek advice that fits their style and goals.

The Long Game 169: AI Investment Thesis, Peter Attia, Earth AI, Science-Based Lifting

The Long Game by Mehdi Yacoubi • 3 implied HN points • 19 Nov 25
🕹 Technology AI
  1. Longevity works best when you focus on basics—build muscle, move often, eat and sleep reasonably well—and avoid turning health into constant self-surveillance that makes you feel fragile.
  2. The AI app market is unstable because foundational model providers can rapidly absorb app features, so most startups either need to generate quick cash, aim to be acquired, or specialize in niches with unique atom-level data, hardware, or heavy enterprise integration.
  3. Real competitive advantage comes from controlling the full loop: huge, cleaned datasets, continent-scale multimodal models, and cheap execution that ties AI to real-world testing, and founders should build from conviction rather than chasing what’s currently fundable.

War in the AI age

Comment is Freed • 39 implied HN points • 10 Nov 24
🕹 Technology AI
  1. AI is changing how wars are fought, especially with advanced technologies like drones. This creates new strategies and challenges for countries.
  2. The power of AI, especially large language models, is growing rapidly. This shift can change what it means to be human and how we interact with technology.
  3. AI could change negotiations and decision-making by providing vast knowledge and strategies. This might lead to heightened tensions, as AI could decide that conflict is the best solution.

The Computers Are Disappearing.

The Digital Anthropologist • 19 implied HN points • 10 Nov 23
🕹 Technology AI
  1. Computers are becoming less visible in our daily lives, blending into the background as they help us live more interesting and easier lives.
  2. The future may involve interacting with technology in more intuitive and less obtrusive ways, possibly through spoken commands, knobs, sliders, and interactive screens.
  3. As technology advances, we could see a shift towards simpler yet more sophisticated devices that perform tasks efficiently without unnecessary complexities or constant troubleshooting.

How to use OpenAI Assistant API, a step-by-step guide.

The Novice • 19 implied HN points • 09 Nov 23
🕹 Technology AI
  1. Initiate an Assistant by creating one on the OpenAI platform and setting instructions for its tasks and responses
  2. Initiate a thread by sending a POST request and including necessary headers for identification
  3. Post a request to your thread with a message to be processed by the Assistant
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📌 ML Engineering Event: Mastering AI and ML at Production Scale at apply()

TheSequence • 84 implied HN points • 19 Feb 24
🕹 Technology AI
  1. The event offers real-world insights from engineering leaders on ML model deployment and best practices.
  2. Participants can engage in sponsor-free knowledge sharing sessions with peers, focusing on in-depth discussions.
  3. Attendees have the opportunity to network with a diverse group of AI and ML engineers, including industry veterans and emerging leaders.

($) Do We Need Sovereign AI?

Interconnected • 77 implied HN points • 17 Mar 24
🕹 Technology AI
  1. Sovereign AI is a concept gaining attention, especially with Nvidia's involvement, and raises questions about AI infrastructure and global talent flow.
  2. The idea of sovereign AI has potential benefits in addressing issues like hallucination and data governance that plague generative AI.
  3. Global discussions are evolving around the necessity of sovereign AI to tackle complex AI challenges and leverage economies of scale.

How to communicate the reality of AI-assisted engineering in today’s hype cycle

Engineering Enablement • 14 implied HN points • 11 Jun 25
🕹 Technology AI
  1. When adopting AI tools, focus on solving real problems instead of just their flashy promises. It's important to communicate how the tools address specific issues in your organization.
  2. Implementing AI tools requires serious support and training for developers. It's not just about giving access; you need to ensure the team knows how to use them effectively.
  3. Share the impact of AI in ways that matter to your audience. Use metrics that show how AI helps the team and the business, and tell a story that highlights its value to different stakeholders.

What AI Can and Cannot Do for UX

Jakob Nielsen on UX • 87 implied HN points • 01 Feb 24
🕹 Technology AI
  1. AI has a strong role in user experience and professionals should embrace it.
  2. AI is creative, productive, and can create and analyze content at scale.
  3. AI may eventually design good user interfaces but will never replace the need for human users in user research.

How to intellectually debate AI while completely missing the point

Platforms, AI, and the Economics of BigTech • 11 implied HN points • 20 Jul 25
🕹 Technology AI
  1. The debate about AI often splits into two sides: those who fear job loss and those who believe innovation benefits everyone. However, both miss the real issue: while technology can create more value, it doesn't mean everyone benefits equally.
  2. AI changes not just tasks but the entire structure of industries. This means that instead of just focusing on jobs, we should look at how AI shifts power and influence in the economy.
  3. To truly understand AI's impact, we need to think about how it transforms systems and competition, rather than just the tasks it performs or the jobs it might replace. This broad view helps us see who really gains or loses from these changes.

AI and the Government

Who is Robert Malone • 14 implied HN points • 12 Jun 25
🕹 Technology AI
  1. AI is now a big part of our online lives, whether we like it or not. It's being used in search engines, social media, and more, so it's important to learn how to use it effectively.
  2. Generative AI can create new content like text, images, and videos. By understanding and using generative AI tools, you can enhance your research and creativity.
  3. The government is increasingly using AI for various tasks, like identifying fraud and managing healthcare data. While there are risks, it's essential to engage with AI tools to stay in control rather than letting them control you.

Attention Explained: When to use Self, Graph, and Target-Aware Attention

Recommender systems • 16 implied HN points • 25 May 25
🕹 Technology AI
  1. Self-attention helps summarize a list of information, making it easier to find what's most relevant, like recent videos you watched.
  2. Graph attention looks at how items in a network relate to each other, like understanding social connections in a network.
  3. Target-aware attention checks how relevant certain items are based on your past choices or queries, helping improve recommendations.

Edition 29: Security slows down Change Management and we have a chance to fix it

Boring AppSec • 15 implied HN points • 27 May 25
🕹 Technology AI
  1. Change management in IT often slows down security processes, making it hard for teams to implement new features quickly. Many companies find this review process lengthy and unproductive.
  2. Using AI, like LLMs, could help automate security reviews, making the process faster and more efficient. This can potentially save days or weeks by compressing what used to take a long time into just a few minutes.
  3. Finding the right name for these new automated reviews is tricky, as the current options don't fully capture the goal. Still, the focus should be on how to secure changes rather than just assessing risks.

Cogito v2, GLM-4.5 , first open-source MoE Video Model, fully autonomous ML agent, FLUX.1 Krea [dev], Qwen3-Coder-Flash, Manus Wide Research, Runway Aleph, Intern-S1, Step3, Action Agent & more

AI Brews • 10 implied HN points • 01 Aug 25
🕹 Technology AI
  1. Several new AI models have been released, including models for reasoning and video generation. These advancements promise improved performance in various AI tasks.
  2. Open-source AI projects are on the rise, allowing developers and researchers to access and contribute to innovative AI technologies more easily.
  3. New features in AI tools, like autonomous agents and enhanced context management, are making it easier for users to navigate complex workflows and streamline their tasks.

Hello App Developer

Sector 6 | The Newsletter of AIM • 19 implied HN points • 07 Nov 23
🕹 Technology AI
  1. OpenAI introduced GPT Builder, making it easier for anyone to create applications using conversational AI. This means more people can turn their ideas into apps without needing a lot of technical skills.
  2. Sam Altman emphasized that natural language will play a big role in how we use computers in the future. This shift could change the way we interact with technology every day.
  3. The announcement includes a 'Startup Mentor' app that provides advice to founders and developers. This app uses real-life knowledge and lectures from Altman to help guide new projects.

Why AI Won't Cause Unemployment

Marc Andreessen Substack • 163 HN points • 04 Mar 23
🕹 Technology AI
  1. Throughout history, fears of technology causing unemployment have not matched reality in capitalist economies.
  2. AI may face barriers due to regulations that already make technology illegal in many sectors of the economy.
  3. Sectors heavily regulated by the government see rising prices without technological innovation, while less regulated sectors witness falling prices due to technological advancement.

S. Somasegar on the Present and Future of Generative AI

TheSequence • 161 implied HN points • 15 Mar 23
🕹 Technology AI
  1. Generative AI is a subsegment of intelligent applications with potential in enterprise and consumer use cases.
  2. Developer tools will be reimagined with foundation models, enhancing productivity and code quality.
  3. New capabilities in generative AI models include the use of 'agents' for natural language interpretation and actions.

Building my own guillotine

Startup Strategies • 142 implied HN points • 19 May 23
🕹 Technology AI
  1. The author has been experimenting with generative AI and has created something intriguing.
  2. The author used to write many blog posts per day to maximize earnings.
  3. To continue reading, a 7-day free trial is available for accessing the full post archives.

This landscape does not exist

Conspirador Norteño • 32 implied HN points • 28 Dec 24
🕹 Technology AI
  1. Facebook is flooded with AI-generated images, often coming from pages that aren't run by regular users. These images sometimes get a lot of attention, but they mainly come from content farms.
  2. Many Facebook pages post the same AI-generated images around the same time, with slight changes to avoid detection. This suggests they might all be operated by the same group of people.
  3. The AI-generated images often look strange and unrealistic, with obvious glitches like odd-looking roads and animals. They tend to have brighter colors than real photos, making them easy to spot.

How Should Large Language Models Be Evaluated?

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 06 Nov 23
🕹 Technology AI
  1. When evaluating large language models (LLMs), it's important to define what you're trying to achieve. Know the problems you're solving so you can measure success and failure.
  2. Choosing the right data is crucial for evaluating LLMs. You'll need to think about what data to use and how it will be delivered in your application.
  3. The process of evaluation can be automated or involve human input. Deciding how to implement this process is key to building effective LLM applications.

Reasoning Models, visually explained 🤔

Year 2049 • 11 implied HN points • 17 Jul 25
🕹 Technology AI
  1. Reasoning models take time to think through problems step-by-step, unlike standard LLMs that give quick answers. This helps them break down complex questions and find better solutions.
  2. While reasoning models can work better for complex problems, they might fail on simpler ones and can overthink too much. Sometimes, basic LLMs are faster and more accurate.
  3. Choosing the right AI model for your task is important. Not every problem needs a reasoning model, so understanding their strengths and limitations can help set realistic expectations.

Where is the autonomy in AI?

Sunday Letters • 19 implied HN points • 06 Nov 23
🕹 Technology AI
  1. AI models like large language models need human guidance to perform tasks effectively. Humans help by providing prompts and correcting errors.
  2. Even complex tasks require a lot of human involvement. AI can't work fully independently; it can't just be told to 'write a book' without further instruction.
  3. There is still a long way to go in developing AI that can handle complex, open-ended problems alone. Current systems struggle with autonomy and can't yet replicate human planning and organization.

($) Tracking Global AI Talent Flow

Interconnected • 77 implied HN points • 08 Mar 24
🕹 Technology AI
  1. China is producing a significant amount of AI talent at the undergraduate level, with many choosing to stay in the country for graduate studies and work.
  2. Tracking AI talent flow through conferences like NeurIPS provides valuable insights into global trends and migration patterns.
  3. Understanding the definition and limitations of how AI talent is measured is crucial when interpreting and drawing conclusions from talent tracking analyses.

Deskilling on the Job

Data: Made Not Found (by danah) • 145 implied HN points • 21 Apr 23
🕹 Technology AI
  1. AI can lead to deskilling on the job, affecting pilots, surgeons, and other professions.
  2. Training has shifted from on-the-job to expecting skills at hiring, creating gaps in talent and opportunity.
  3. Efficiency with technology should balance quality and quantity, avoiding deskilling highly skilled professionals.

The White House Weighs in on AI

Technically Optimistic • 19 implied HN points • 03 Nov 23
🕹 Technology AI
  1. The Executive Order on AI safety issued by the White House focuses on incentivizing widespread and equitable adoption of AI, promoting cross-sector collaboration and accountability, and prioritizing human interests in AI development.
  2. The EO includes measures for sharing safety test results, creating standards for red-teaming, and protecting against the misuse of AI for biological warfare to hold developers of powerful AI systems accountable.
  3. Everyday Americans can benefit from increased privacy protection, efforts to prevent algorithmic discrimination, and the focus on AI education and worker support mentioned in the Executive Order.

Tutorial: How to narrate video with Sora, GPT-Vision, and ElevenLabs

Artificial Ignorance • 79 implied HN points • 28 Feb 24
🕹 Technology AI
  1. The emergence of tools like Sora from OpenAI is revolutionizing video production with realistic outputs and seamless object interactions.
  2. Creating nature documentaries and other narrative videos through automated processes involving Sora, GPT-Vision, and ElevenLabs is becoming increasingly feasible.
  3. The future of entertainment and media is set to be transformed by AI-driven technologies, enabling faster video generation and real-time content creation for indie filmmakers and creators.

Will AI skyrocket inequality?

Economic Forces • 12 implied HN points • 03 Jul 25
💼 Business AI
  1. AI might change job markets and wages, but we need to examine how it affects skilled and unskilled workers. Understanding labor demand and supply can help explain these changes.
  2. There is a potential for AI to increase inequality, especially between those with higher education and those without. However, AI might make some skilled tasks easier for less-educated workers, which could balance things out.
  3. As AI evolves, the way we categorize jobs might need to change. We should look at how AI creates new job roles and affects wages within different skill groups.

The Programmers of the Future

Based Meditations • 8 HN points • 12 Mar 24
🕹 Technology AI
  1. The future of programming may shift towards a focus on creativity and innovation rather than just logic and coding skills.
  2. The impact of AI and automation on the programming industry is uncertain, leading to a potential rise in independent artists creating software.
  3. There is a growing trend of passionate developers moving away from traditional software jobs to pursue artistic endeavors, potentially transforming software development into a form of art.

The Mathematical Capabilities of ChatGPT.

Deep-Tech Newsletter • 39 implied HN points • 17 Feb 23
🕹 Technology AI
  1. Recently published research suggests that ChatGPT's mathematical abilities are below those of an average mathematics graduate student.
  2. There is skepticism that large language models like ChatGPT will lead to Artificial General Intelligence due to their poor mathematical reasoning performance.
  3. ChatGPT has been subject to criticisms and shortcomings, with some considering it less innovative and revolutionary compared to expectations.

My writing robot

Kyle Chayka Industries • 127 implied HN points • 15 Jul 23
🕹 Technology AI
  1. Artificial intelligence is becoming more integrated into our lives, used for tasks like writing and answering questions.
  2. AI tools can mimic a person's style but struggle to create original content or meaningful arguments.
  3. Working with AI for writing may not be as efficient or satisfying, especially for deep thinking and knowledge synthesis.

OpenAI Deep Research Explains Itself

From the New World • 26 implied HN points • 06 Feb 25
🕹 Technology AI
  1. AI hardware has evolved significantly, from early specialized chips to powerful GPUs and TPUs. These advancements make training AI models much faster and more efficient.
  2. The design of algorithms, especially with transformers, has greatly improved AI's ability to understand and generate language. These models can now learn complex patterns that were hard to capture before.
  3. Building and maintaining large AI systems requires careful planning and practices. Companies need efficient workflows and monitoring systems to manage data, hardware, and software effectively.

Saturday 25th November, 2023 - Passing the Baton of Chaos (Issue #142)

Mark Smith’s Newsletter • 19 implied HN points • 25 Nov 23
🕹 Technology AI
  1. The baton of chaos shifted from Elon Musk and social media to OpenAI, causing a frenzy globally.
  2. Amid the chaos, significant developments in banking, society, social media renaissance, and reality simulation were happening.
  3. Podcasts covered topics like Bitcoin for banking failures, AI and regulatory capture, and the impact of software in government and technology.

Accelerationism is Terrorism

Never Met a Science • 105 implied HN points • 17 Oct 23
🕹 Technology AI
  1. Accelerationism is a form of terrorism fueled by unsustainable concentration of power.
  2. Engineers now hold societal power, overshadowing the importance of humanities.
  3. Accelerating technological development without understanding its consequences is dangerous and dehumanizing.

How the UK AI Safety Summit Can Make AI Safer: A Single Policy Proposal

Eva’s Substack • 19 implied HN points • 31 Oct 23
🕹 Technology AI
  1. The UK AI Safety Summit aims to address risks from powerful AI systems and create national and international AI regulation.
  2. A proposed key principle is to monitor and control the use of computational resources for advanced AI to reduce risks.
  3. Another suggestion is to establish a concrete threshold for compute usage above which AI development should be restricted or prohibited, paving the way for international AI regulations.

Resisting Deterministic Thinking

Data: Made Not Found (by danah) • 145 implied HN points • 10 Apr 23
🕹 Technology AI
  1. Deterministic thinking can lead to polarization and distrust in discussions about the future.
  2. Embracing probabilistic thinking is essential for understanding how technologies shape different possible futures.
  3. Projectories can be both beneficial and detrimental, highlighting the need for more nuanced and reflexive thinking about the impacts of technology.

Robot Revolution?

Daniel Pinchbeck’s Newsletter • 14 implied HN points • 31 May 25
🕹 Technology AI
  1. AI is taking over many jobs, especially in tech and creative fields, causing big layoffs and making it hard for new graduates to find work.
  2. There’s a growing concern that AI could create a rich vs. poor divide where a few tech owners become extremely wealthy while most people become jobless and struggle to get by.
  3. To address these changes, we need new ideas about how society should work, moving away from just making money to focusing on community, creativity, and ensuring everyone has what they need.

Technically Monthly (July 2025)

Technically • 12 implied HN points • 02 Jul 25
🕹 Technology AI
  1. AI models are evolving to think and reason more like humans. This change could make them more useful for complex tasks, beyond just predicting words.
  2. Code reviews can slow down development significantly. Understanding their impact might help teams find ways to speed up this process.
  3. Multi-tenant architecture lets multiple customers share the same server resources. This can make services cheaper and easier to manage.