The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

AI #121 Part 2: The OpenAI Files

Don't Worry About the Vase • 1971 implied HN points • 20 Jun 25
🕹 Technology AI Policy Innovation Ethics Regulation
  1. Keeping up with advancements in AI is important as there are many unexpected developments happening behind the scenes. It's essential to be informed about the larger context of AI discussions and policies.
  2. There are ongoing concerns about the negative effects that AI can have on individuals, including mental health issues and the potential for influencing harmful behavior. It's crucial to have a conversation about these risks.
  3. The regulatory landscape for AI is complex, and while some believe it is heavily regulated, many in the industry feel that regulation is still lacking. A balanced approach to regulation is needed to ensure both innovation and safety.

Continuous Software Engineering: Part 2 - Continuous Planning & Prioritization

The Healthy Engineering Leader • 19 implied HN points • 19 Sep 24
🕹 Technology Software Engineering Agile methodologies Project management Team Collaboration Continuous Improvement
  1. Continuous Planning means regularly updating your plans as things change. This helps teams stay effective and respond quickly to new information.
  2. Continuous Prioritization allows teams to adjust their focus based on what’s most important at any moment. This ensures they always work on tasks that matter the most.
  3. Both continuous planning and prioritization make teams more adaptable. They can shift their strategies easily and keep delivering value, even in changing environments.

When the mask slips - a cautionary (if ancient) tale of IC quality

filterwizard • 59 implied HN points • 01 Sep 24
🕹 Technology Audio engineering Circuit Design Signal Processing Electronics
  1. Don't assume that all ICs perform the same, even if they look similar. Small changes in production can lead to big differences in quality.
  2. Working with audio equipment requires attention to detail in filtering processes. It's essential to ensure that all components meet specific performance standards.
  3. When using older components, always check for changes in manufacturing. Even slight variations can drastically affect audio quality, as seen with the NE5532 op-amps.

Will New Glenn and Neutron Beat Starship?

Erik Explores • 245 implied HN points • 25 Dec 25
🕹 Technology Aerospace Commercial Space
  1. New Glenn’s successful booster landing showed that SpaceX isn’t the only game in town and that other companies can catch up, breaking the sense of inevitable SpaceX dominance.
  2. Starship failing to meet Elon Musk’s original full-reuse goals wouldn’t be a total failure because a non-reusable or redesigned second stage could be much lighter and cheaper while still outperforming SLS and Falcon Heavy.
  3. A realistic outcome is that SpaceX might achieve full reuse but with a lower payload (~45 t), while also offering expendable variants that can deliver roughly 100–130 t to LEO, keeping the system competitive and flexible.

Own the Spreadsheet, Own the World

SeattleDataGuy’s Newsletter • 353 implied HN points • 28 Nov 25
🕹 Technology Data Analysis Software Tools Business Intelligence Data Governance Spreadsheets
  1. Excel remains a key tool for many teams, despite the availability of advanced data platforms. It's easy to use and allows quick edits without messing with permanent data sources.
  2. When teams prefer Excel over dashboards, it usually signals a deeper issue, like dashboards not meeting their needs or users needing more flexibility.
  3. Instead of trying to eliminate Excel, it's more effective to incorporate it into data strategies, allowing users to access and manipulate data in familiar ways.
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New cracks emerge in Elon Musk's Twitter

Platformer • 3164 implied HN points • 24 Feb 23
🕹 Technology Social media Software E-commerce Search Engines AI
  1. Twitter employees faced disruptions like Slack going down and Jira not working, causing frustration and questions about payment.
  2. Elon Musk announced plans to open source Twitter's algorithm, but doubts arise among employees about the transparency and actual release of the code.
  3. Twitter's performance has been degrading, with issues like increased latency during peak usage times, including events like the Super Bowl and a Twitter outage in Asia.

Universities Are Woefully Under-Resourced For AI Research. They’re Fighting To Change That.

Big Technology • 5129 implied HN points • 22 Nov 24
🕹 Technology AI Research Higher education Public Policy Data science
  1. Universities are struggling to keep up with AI research due to a lack of resources like powerful GPUs and data centers. They can't compete with big tech companies who have millions of these resources.
  2. Most AI research breakthroughs are now coming from private industry, with universities lagging behind. This is causing talented researchers to prefer jobs in the private sector instead.
  3. Some universities are trying to address this issue by forming coalitions and advocating for government support to create shared AI research resources. This could help level the playing field and foster important academic advancements.

Synopsys and NVIDIA Double Down on Acceleration

More Than Moore • 373 implied HN points • 01 Dec 25
🕹 Technology Semiconductors AI Simulation Hardware Software Cloud
  1. NVIDIA is investing $2 billion and forming a multi-year partnership with Synopsys to GPU-accelerate and add AI and digital-twin support across Synopsys’ EDA, simulation, and multiphysics tools. The goal is to let customers run much larger and faster simulations and tighten engineering iteration loops.
  2. Moving these tools to accelerated hardware will require deep solver and algorithm reformulation and is a multi-year, hybrid effort. Many safety-critical or high-fidelity flows will remain FP64 or mixed-precision for validation and accuracy.
  3. The companies hope faster, cheaper simulation will expand the total market for virtual prototyping across industries, but delivery details, pricing models, and practical hardware neutrality remain unclear and may favor NVIDIA’s stack in practice.

When counterculture and empire merge

All-Source Intelligence Fusion • 1281 implied HN points • 11 Aug 25
🕹 Technology Cybersecurity Hacking Military Tech Geopolitics AI Technology
  1. DEF CON, the big hacker conference, is teaming up with the U.S. military and some strict governments, which is upsetting a lot of hackers.
  2. Despite human rights issues related to some sponsors, many attendees seemed unconcerned while enjoying the conference's activities.
  3. There were protests at the event against U.S. military actions and a strong awareness of global issues like violence in Palestine.

MIT Study: Using ChatGPT Won't Make You Dumb (Unless You Do It Wrong)

The Algorithmic Bridge • 1942 implied HN points • 19 Jun 25
🕹 Technology Artificial Intelligence Neuroscience Cognitive Science Education Research
  1. Using AI tools like ChatGPT can make you less engaged mentally if used excessively. People can become reliant on these tools and stop thinking deeply.
  2. When people switch from using AI tools back to using their own knowledge, they can struggle at first but may learn and grow better in the long run.
  3. The best way to use AI is to first work on a task with your own skills and then use AI to enhance what you've done, rather than relying on it from the start.

In The Age Of AI, We Each Have To Choose How Much Of Our Humanity We Want To Keep

Caitlin’s Newsletter • 1662 implied HN points • 09 Jul 25
🕹 Technology AI Ethics Digital Culture Critical Thinking Social Commentary
  1. We now have to decide how much we want to rely on AI for our everyday tasks, from thinking and writing to art and relationships. Each choice we make has an impact on our human experience.
  2. Engaging deeply with our emotions and creativity is important. We need to think about how much we are willing to trade for convenience and ease in our lives.
  3. This new era makes us question what aspects of our humanity we are willing to give up. It's essential to reflect on what we value and how we want to connect with the world around us.

A 15-minute intro to resin casting

lcamtuf’s thing • 4693 implied HN points • 21 Dec 24
🕹 Technology Engineering Manufacturing Prototyping DIY Materials
  1. Resin casting involves making a mold and pouring liquid plastic into it. This method allows you to create exact replicas of items, capturing all their details.
  2. Compared to 3D printing, resin casting can produce stronger and more durable parts. It also gives a finer finish since the liquid can fill every tiny detail of the mold.
  3. The process includes making a flexible mold from silicone, applying a release agent, and carefully pouring in the resin. It's important to manage air bubbles for the best results.

The Top 5 Most Exciting New Features on Substack (and How to Maximize Their Benefits)

Kristina God's Online Writing Club • 999 implied HN points • 30 Mar 24
🕹 Technology Social media Online Writing Content creation Digital marketing Platforms
  1. Substack has introduced exciting new features, including an updated recommendations engine and advanced layouts, that writers can use to enhance their content.
  2. It's important for writers to stay informed about these changes to avoid feeling overwhelmed and burnt out during their writing journey.
  3. Joining a community or school, like Substack School, can provide support and resources to help writers grow and succeed with their newsletters.

The internet's "town square" is dead

The Intrinsic Perspective • 18314 implied HN points • 09 Jul 23
🕹 Technology Social media Online Platforms Content Moderation Power Dynamics
  1. The internet's idea of a centralized 'town square' is no longer feasible due to fundamental differences in people's worldviews.
  2. When individuals have too much control over speech without oversight, it often leads to corruption and abuse of power.
  3. The rise of new platforms like Threads and shifts in social media dynamics reflect a fragmentation of the 'town square' into multiple platforms with differing moderation policies and user bases.

How to succeed as a Machine Learning Engineer

The ML Engineer Insights • 359 implied HN points • 22 Jun 24
🕹 Technology Machine Learning Career development Professional Skills Networking Mentorship
  1. Building a strong foundation in machine learning fundamentals and staying updated with the latest research are crucial for success as a Machine Learning Engineer.
  2. Playing to your strengths, such as data and feature engineering, modeling, and deployment scalability, is key. Seek help in areas where you're less experienced.
  3. Focus on aligning your work with business goals, understanding trade-offs, ROI, and embracing experimentation. Continuous learning, networking, and mentorship are invaluable.

#46 - Thought Experiment - Your Data Debt Just Became Less Worrying

OSS.fund Newsletter • 113 implied HN points • 29 Jan 26
🕹 Technology AI Data Analytics Enterprise Tech Data Governance Architecture Cloud
  1. AI-powered semantic layers can query messy, fragmented systems and deliver unified read-only insights fast, making many long master-data consolidation projects unnecessary for read-heavy analytics.
  2. You still need traditional MDM for writes, transactional consistency, and regulatory requirements like GDPR, because semantic abstraction doesn’t tell you where to update or delete authoritative records.
  3. A practical approach is to segment use cases into read vs write, run semantic tests on top business questions to capture immediate value, and invest in targeted MDM only for the write/compliance-critical scenarios.

AI influencer hype gone wild

Marcus on AI • 5572 implied HN points • 31 Oct 24
🕹 Technology Artificial Intelligence Productivity Tools Tech Trends Market Analysis Consumer behavior
  1. Many people are trying AI tools, but not everyone thinks they are effective. This shows there's a mix of interest and skepticism in using new technology.
  2. A recent survey revealed that while 79% of people have tried Microsoft Copilot, only 25% found it worthwhile. This indicates people are testing AI but still unsure about its overall value.
  3. People are not ignoring AI; they are being cautious and waiting to see if it meets their expectations before fully committing. It’s a wait-and-see attitude towards technology.

If You've Been Thinking About Subscribing to Premium...

Software Design: Tidy First? • 397 implied HN points • 22 Nov 25
🕹 Technology Artificial Intelligence Software Automation Ethics Creativity Community
  1. Limited-time Black Friday deal: $180/year through December 1st, reduced from the usual $250.
  2. Paid subscribers get early access to unpolished essays, a problem-solving chat community, and weekly "Thinkies" that teach habits for creative thinking.
  3. The project aims to help technical people feel safer as machines start to code, exploring responsibility and what changes when capabilities and speed increase.

The Birth of the Grid

Construction Physics • 19834 implied HN points • 25 May 23
🕹 Technology Energy Infrastructure Innovation History Utilities
  1. Electricity transitioned from a rare luxury to a critical aspect of modern life in a short period of time.
  2. The development of high-voltage transmission lines allowed for long-distance power transmission and the creation of interconnected power systems.
  3. The electric power industry grew by embracing scale, cooperation, and regulation to meet increasing demand and ensure reliability.

Qualcomm’s RISC Pays Off; Arm’s Dogs Don’t Bark

The Chip Letter • 4149 implied HN points • 15 Jan 25
🕹 Technology Semiconductors Legal issues Corporate strategy Market Competition
  1. Qualcomm won the legal battle against Arm, as the jury decided Qualcomm did not breach any licensing terms. This means Qualcomm can continue using technology from its acquisition of Nuvia without additional legal issues.
  2. Arm claimed Qualcomm's actions would hurt their licensing fees and market control, but the jury didn't agree with Arm on key points. This suggests Qualcomm's strategy was successful.
  3. The trial was complex, and the outcome was unexpected for many observers, indicating that there might be more legal and business implications in the tech industry as companies navigate these licensing agreements.

How I code going into 2026

Olshansky's Newsletter • 183 implied HN points • 05 Jan 26
🕹 Technology Software Engineering Artificial Intelligence Developer Tools Engineering Management Automation Documentation
  1. Most coding is now delegated to AI agents, so engineers spend their time orchestrating agent personalities and guiding work rather than writing code by hand.
  2. Practical workflows matter: use Makefiles as a stable CLI, leave TODOs instead of side quests, maintain prompts/skills, write short copy-paste friendly docs, and review critical diffs on GitHub.
  3. Team roles and skills are shifting: leaders must be hands-on translators of intent into agent-driven work, focusing on system design, taste, and continuously improving agent behavior.

AI Companion Piece

Don't Worry About the Vase • 1433 implied HN points • 28 Jul 25
🕹 Technology AI Persuasion Personalization User Experience Ethics
  1. AI companions are becoming popular, especially among teens, who often use them for social interaction and emotional support. However, many teens still prefer real friendships over AI interactions.
  2. Personalization in AI is growing, which can enhance engagement but also raise concerns about persuasion and the potential for misuse. People worry about AI manipulating opinions or creating echo chambers.
  3. There are ongoing debates about the ethical implications of AI companions, especially regarding their influence on relationships and mental health. This raises questions about how much we should trust AI in personal matters.

AGI isn’t coming in 2025, and GPT-5 probably isn’t either.

Marcus on AI • 4189 implied HN points • 09 Jan 25
🕹 Technology AI Computing Data science Machine Learning Software
  1. AGI, or artificial general intelligence, is not expected to be developed by 2025. This means that machines won't be as smart as humans anytime soon.
  2. The release of GPT-5, a new AI model, is also uncertain. Even experts aren't sure if it will be out this year.
  3. There is a trend of people making overly optimistic predictions about AI. It's important to be realistic about what technology can achieve right now.

On change

Technically • 22 implied HN points • 03 Mar 26
🕹 Technology AI Automation Software Careers Industry Labor
  1. The newsletter has evolved from a solo project into a multi-writer, editor-led publication that delivers deeper technical stories.
  2. AI is reshaping the labor market in complicated ways: some firms are cutting large numbers of jobs, but new specialized roles are appearing and software job openings are actually up.
  3. The readership is shifting toward industrial companies curious about using software and AI at work, so they're running a short reader survey to find out which topics to cover.

o3 Turns Pro

Don't Worry About the Vase • 1881 implied HN points • 17 Jun 25
🕹 Technology AI Computing Software Data Analysis Cloud Services
  1. o3-pro can handle bigger problems but can be slow, which might disrupt your workflow. It’s often better to queue up questions for later use instead of waiting for immediate answers.
  2. Many users see o3-pro as slightly better than o3 but still not perfect, especially in areas like coding where its performance can be inconsistent. It works well for in-depth analysis, but may not be the best for all tasks.
  3. The significant price drop for o3 makes it a more appealing choice for general use compared to o3-pro, which is seen as special-case only. This change could lead to more ambitious AI projects with the same budget.

AI is just the latest Monoculture

Deus In Machina • 72 implied HN points • 05 Feb 26
🕹 Technology Programming Languages AI Software Hardware Web Infrastructure
  1. Technological lock-in has been the default for decades, so AI tools are more inheriting existing monocultures than creating them. They might speed up adoption of dominant tools, but the fundamental switching costs already existed.
  2. Products and tools tend to win by being familiar, not necessarily by being better, because people avoid relearning interfaces. That’s why many improvements preserve old APIs and conventions instead of introducing new paradigms.
  3. Concrete chokepoints — like the C ABI, curly-brace syntax, dominant CPU/GPU ecosystems, and the browser stack — show how early choices constrain future innovation. Those entrenched standards make it hard for new languages, hardware, or platforms to gain traction even before factoring in AI.

Top Links 921 Integrating AI. The global distribution of hail. Pre-tomato Italy & "Bad Medicine for Dr Drugs".

Chartbook • 429 implied HN points • 14 Nov 25
🕹 Technology AI Workforce Innovation Data Health
  1. AI is being integrated into the workforce in various ways, influencing how jobs are done.
  2. There's a focus on understanding the global impacts of extreme weather, like hail, on different regions.
  3. Historical contexts, such as pre-tomato Italy, provide interesting insights into how food and medicine have evolved over time.

What Is Sora For?

Big Technology • 4503 implied HN points • 13 Dec 24
🕹 Technology AI Video Generative Innovation Digital Media
  1. Sora is a cool AI video generator but is not very useful right now. The videos it creates are interesting but lack quality for serious use.
  2. There’s no clear audience for Sora yet, as it struggles to find practical ways for everyday users to engage with it. Most people might enjoy it initially, but it's hard to see why they'd keep using it.
  3. Sora could help in some specific applications, like filmmaking or marketing, but it also raises concerns about how we distinguish real from fake videos in a confusing digital world.

Salesforce CEO Marc Benioff Has Thoughts on AI Agents, Automation, And The Future of Your Job

Big Technology • 4753 implied HN points • 27 Nov 24
🕹 Technology AI agents Automation Customer Service Productivity
  1. Salesforce CEO Marc Benioff believes AI agents will work for companies rather than individuals. This means businesses can use these agents to handle customer service and other tasks, making things more efficient.
  2. Benioff sees AI as a way to boost productivity, not just replace jobs. By using technology, companies can enhance the skills of their workers and make them more effective without necessarily hiring more people.
  3. The future of business software could change a lot. Instead of traditional programs, companies might start using chatbots to manage data and interact with customers, creating a new kind of relationship with technology.

Which Filters are Noisier – Analog or Digital? Part 1

filterwizard • 19 implied HN points • 18 Sep 24
🕹 Technology Signal Processing
  1. Analog filters can generate noise from several sources like opamps and passive components. Understanding where this noise comes from helps in designing better filters.
  2. Capacitors don’t create noise themselves, but they can hold noise sampled from resistors. This means their role in noise management in filters is important.
  3. The noise contribution of a filter stays consistent if you keep the capacitor values the same while changing resistors. This knowledge simplifies filter design.

Through the Ages: Apple Concurrency APIs

Jacob’s Tech Tavern • 1749 implied HN points • 24 Jun 25
🕹 Technology Software Programming APIs Development Computing
  1. Apple's concurrency APIs have evolved significantly since 1977, with each new version reflecting advancements in technology. Today, developers can handle complex tasks easily, thanks to modern tools.
  2. In the early days of computing, like with the Apple ][, parallel processing was nearly impossible because machines had limited capabilities. Over the years, technology grew, leading to better tools for developers.
  3. Swift Concurrency is considered a major breakthrough for the Swift programming language, making it easier to manage multiple tasks and streamline code.

Enterprise AI is Moving Fast, and Other Takeaways From a Week With Amazon

Big Technology • 4503 implied HN points • 09 Dec 24
🕹 Technology AI Enterprise Software Innovation Business
  1. Generative AI is mainly used in businesses right now because they face unique problems. Companies are investing in it to process information and improve operations.
  2. Spending on generative AI is mostly for tools like ChatGPT and APIs for building custom solutions. This growth in enterprise spending may help develop AI technologies for consumers later on.
  3. OpenAI and Amazon are becoming competitors in the AI space. Their focus and innovations can change how AI is used in both business and personal applications.

“LLMs amplify existing security risks and introduce new ones”

Marcus on AI • 3952 implied HN points • 16 Jan 25
🕹 Technology AI Security Ethics Society Innovation
  1. Large Language Models (LLMs) may increase security problems that already exist and also create new ones. It's important to be cautious as technology evolves.
  2. Keeping AI systems safe is an ongoing task that can never fully be completed. Security needs constant attention as risks change.
  3. Relying heavily on AI in everyday life could lead to serious problems. It's essential to consider the potential dangers before implementing AI widely.

LLMs – Part 3: Context Matters — Self Attention

Vasu’s Newsletter • 78 implied HN points • 25 Jan 26
🕹 Technology Machine Learning Deep Learning Natural Language Neural Networks Transformers Model Architecture
  1. Each token creates query, key, and value vectors so it can ask what it needs, match that against other tokens, and gather useful information.
  2. Tokens compare their query to every key to get raw scores, convert those scores to attention weights with softmax, and use the weights to take a weighted sum of value vectors to produce a new contextual vector.
  3. Self-attention makes token meanings contextual (helping with pronouns, disambiguation, and long-range links), and models use multiple attention heads plus feed-forward layers to capture different relation patterns and refine each token's representation.

Python Data Engineering, July 2024

Monthly Python Data Engineering • 179 implied HN points • 25 Jul 24
🕹 Technology Software Development Data Engineering Open Source Programming Languages Data science
  1. The Python Data Engineering newsletter focuses on key updates and tools for building data engineering projects, rather than just data science.
  2. This month showcased rapid development in projects like Narwhals and Polars, with Narwhals making 26 releases and Polars reaching version 1.0.0.
  3. Several other libraries, such as Great Tables and Dask, also had important updates, making it a busy month for Python data engineering tools.

Silicon Valley's Slaughterhouse

Where's Your Ed At • 15430 implied HN points • 08 Sep 23
🕹 Technology Tech industry Venture Capital Startups Software Industry
  1. Elon Musk is involved in a legal battle over accusations of anti-semitism and his actions have had significant impacts on advertising revenue and Twitter's valuation.
  2. Silicon Valley culture has devolved into a profit-driven, empty innovation environment fueled by venture capital, lacking real societal impact.
  3. The tech industry, led by venture capital, has created a culture of labor exploitation, hollow promises, and superficial startup culture, with the focus on profitability rather than meaningful innovation.

AI #127: Continued Claude Code Complications

Don't Worry About the Vase • 1344 implied HN points • 31 Jul 25
🕹 Technology AI Data Software Policy Trends
  1. The US AI Action Plan is praised for its practical proposals but criticized for its focus on competition, which could harm safety and international cooperation.
  2. There are increasing concerns about the sustainability of offering unlimited AI usage due to high demand and costs, suggesting a shift towards charging based on usage.
  3. Many people still feel uncertain about AI's impact on jobs, with a divide in opinions on whether it will create or eliminate more opportunities in the future.

Which CEO will be the last to see it?

Marcus on AI • 4624 implied HN points • 05 Dec 24
🕹 Technology AI Innovation CEOs Trends Industry
  1. Many people were skeptical about the hype around Generative AI during 2022 and 2023. Some experts believe that the truth about its capabilities will eventually become clear.
  2. Several tech leaders are starting to see and admit the limitations of current AI models. This signals a possible shift in how the industry views AI's effectiveness going forward.
  3. To achieve greater advancements, experts suggest integrating different methodologies, like neurosymbolic AI, which could help overcome current challenges in AI development.