The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

LangChain Based Plan & Execute AI Agent With GPT-4o-mini

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 99 implied HN points • 26 Jul 24
🕹 Technology AI
  1. The Plan-and-Solve method helps break tasks into smaller steps before executing them. This makes it easier to handle complex jobs.
  2. Chain-of-Thought prompting can sometimes fail due to calculation errors and misunderstandings, but newer methods like Plan-and-Solve are designed to fix these issues.
  3. A LangChain program allows you to create an AI agent to help plan and execute tasks efficiently using the GPT-4o-mini model.

AI Links, 11/17/2025

In My Tribe • 212 implied HN points • 17 Nov 25
🕹 Technology AI
  1. Many people believe that AI could end up being more disliked than social media companies. There's a concern about AI causing harm as it becomes more advanced.
  2. AI models, like LLMs, tend to reinforce the ideas of users instead of challenging them. This can make users confident, but may not always provide the best advice.
  3. AI is becoming a major player in creating ads, often needing little human input. This could change the job market for those involved in video production, as AI can do the work faster and cheaper.

How I use AI for writing (part 1)

Technically • 25 implied HN points • 19 Feb 26
🕹 Technology AI
  1. Writing is central to a writer's identity and career, and the real skill is picking the right topics and structuring ideas rather than obsessing over individual word choices.
  2. Early AI felt wrong to many writers because its output was low-quality and it was trained on other people's work without consent, creating ethical and 'vibe' concerns.
  3. AI can be a useful tool for scaffolding — outlining, prompting, and following style guides — but you shouldn't outsource your creative process or your voice; for personal pieces it's often better to write them yourself.

How to Do Soul-Craft with State Tools

Justin E. H. Smith's Hinternet • 1088 implied HN points • 29 May 25
🎭️ Culture AI
  1. Writing started as a tool for controlling people and managing resources, not for storytelling. It helped governments keep track of what was going on in society.
  2. Getting everyone to be able to read took a long time and a lot of changes in how writing works. It went from a complex system to something much simpler and easier for people to learn.
  3. Reading isn't something we naturally do; it requires special training of our brains. If we don't keep investing in literacy, it could easily disappear and only be accessible to a few people.

Anthropic may go public in 2026

Alex's Personal Blog • 197 implied HN points • 03 Dec 25
🕹 Technology AI
  1. Anthropic is planning for an IPO soon, possibly in 2026, which could make it one of the biggest public offerings in the tech industry. This comes during a time when there's high competition with OpenAI also aiming for a massive IPO.
  2. The Indian government decided not to force smartphone manufacturers to install a controversial app after public backlash. This shows the power of citizen voices against government overreach in tech matters.
  3. There is ongoing debate in the U.S. about allowing states to create their own AI regulations. Some lawmakers are worried that differing state rules could complicate things for AI companies, while others believe states should have the right to pass their own laws.
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There's no silver bullet in AI

The AI Frontier • 99 implied HN points • 25 Jul 24
🕹 Technology AI
  1. In AI, there's no single fix that will solve all problems. Success comes from making lots of small improvements over time.
  2. Data quality is very important. If you don't start with good data, the results won't be good either.
  3. It's essential to measure changes carefully when building AI applications. Understanding what works and what doesn't can save you from costly mistakes.

The End of Search, The Beginning of Research

One Useful Thing • 2047 implied HN points • 03 Feb 25
🕹 Technology AI
  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.

You can't build a moat with AI

The AI Frontier • 459 implied HN points • 11 Apr 24
🕹 Technology AI
  1. You can't really set yourself apart with just AI models because they're becoming similar across different companies. What matters more is the unique data you use to feed those models.
  2. Even if your prompts seem special, they won't give you a long-term advantage. Competitors can quickly figure out how to improve their prompts, making them less valuable for differentiation.
  3. To succeed in building AI applications, focus on understanding and using your customers' data effectively. Good data engineering can really make a difference in how well your application performs.

Jevons Inversion

davidj.substack • 83 implied HN points • 09 Jan 26
🕹 Technology AI
  1. As code generation gets cheap and easy, people will build way more software than before and the line between writing and using software will blur.
  2. Many traditional application developer jobs may disappear as non-specialists who can orchestrate agents — "vibe engineers" — handle the long tail of one-off tools and automations.
  3. User-built software sidesteps much enterprise overhead (scaling, security, support), and with agents that remember and iterate, single-use scripts become cheap, reusable solutions rather than full products.

GraphRAG: Design Patterns, Challenges, Recommendations

Gradient Flow • 259 implied HN points • 30 May 24
🕹 Technology AI
  1. GraphRAG enhances traditional RAG by incorporating knowledge graphs, improving content retrieval and answer generation for complex queries.
  2. GraphRAG offers various architectures like knowledge graph with semantic clustering, knowledge graph and vector database integration, and knowledge graph-based query augmentation for different applications.
  3. Building a comprehensive knowledge graph comes with challenges like domain understanding, data quality, and evolving data sources, requiring significant resources and expert knowledge.

Briefing: Tinder for Slack, GPTs, X’s 2024 roadmap

Department of Product • 943 implied HN points • 11 Jan 24
🕹 Technology AI
  1. Slack's new Catch Up feature works like Tinder for messages, making it easier to catch up on missed messages.
  2. OpenAI launched a GPT store with tools like DesignerGPT and AI PDF, offering add-ons for ChatGPT.
  3. Perplexity is a new 'answer engine' competing with Google, providing direct answers and generative AI capabilities.

AI's seductive mirage

The Uncertainty Mindset (soon to become tbd) • 99 implied HN points • 24 Jul 24
🕹 Technology AI
  1. AI systems look like they can think independently, but they really can't. They are tools that need humans to make decisions about value.
  2. Meaning-making is a core human skill that AI lacks. Only humans can decide what actions are meaningful and worthwhile.
  3. When we treat AI as if it can make important decisions, we risk misusing it. It's crucial to keep humans involved in the decision-making process.

2024: The Year in Weird and Stupid Futures

Read Max • 2318 implied HN points • 27 Dec 24
🕹 Technology AI
  1. Weird and unexpected events have been happening all year, highlighting the strange side of technology and society. It's important to stay aware of how unusual stories can reflect bigger issues.
  2. A lot of new technologies and strange occurrences have been reported, from AI mishaps to bizarre news stories. It shows how fast things are changing and how we need to keep up.
  3. There have been several reports on how people are engaging with technology, sometimes in funny or surprising ways. This can include both the good and the bad outcomes of our tech use.

The American DeepSeek Project

Democratizing Automation • 839 implied HN points • 04 Jul 25
🕹 Technology AI
  1. The U.S. is losing its edge in AI to China, where there's more open-source innovation and a larger number of AI researchers. This is changing the landscape of AI research worldwide.
  2. There's a plan to build a fully open-source AI model in America that matches current top models. This aims to reclaim leadership in AI technologies and ensure that the AI ecosystem remains accessible and accountable.
  3. To succeed in this initiative, the community needs support and collaboration, emphasizing the importance of shared goals and new habits in developing AI models that anyone can trust and use.

AI #94: Not Now, Google

Don't Worry About the Vase • 2464 implied HN points • 12 Dec 24
🕹 Technology AI
  1. AI technology is rapidly improving, with many advancements happening from various companies like OpenAI and Google. There's a lot of stuff being developed that allows for more complex tasks to be handled efficiently.
  2. People are starting to think more seriously about the potential risks of advanced AI, including concerns related to AI being used in defense projects. This brings up questions about ethics and the responsibilities of those creating the technology.
  3. AI tools are being integrated into everyday tasks, making things easier for users. People are finding practical uses for AI in their lives, like getting help with writing letters or reading books, making AI more useful and accessible.

($) Forward Deployed Engineer: the Job that Makes AI Real

Interconnected • 169 implied HN points • 03 Dec 25
🕹 Technology AI
  1. Forward deployed engineers (FDEs) are the on-the-ground builders who turn AI models into working systems inside large enterprises and governments, handling integration, customization, and deployment.
  2. FDEs are scarce and highly sought after, so companies are rapidly expanding FDE teams and partnering with global system integrators to scale capacity and meet enterprise demand.
  3. The FDE function originated in firms like Palantir and has become a core, strategic role that many AI labs now prioritize to drive real-world adoption of their technology.

Thought bubble: I am pleased to report that AI is now a better poet than William McGonagall

Wyclif's Dust • 1877 implied HN points • 06 Feb 25
📚 Literature AI
  1. AI has improved a lot in writing poetry and can now create impressive pieces that rival some human authors. This means anyone can reach a decent level of poetic skill using AI.
  2. Different AI models produce varying quality in poetry, with some showing more creativity and better structure than others. It's interesting to compare how each AI interprets and writes about the same topic.
  3. The development of AI in creative fields could raise the overall skill level in those areas, making it easier for everyone to write poetry well, but true expert poets will still stand out.

Robot Auras

Breaking Smart • 43 implied HN points • 25 Jan 26
🕹 Technology AI
  1. Robot auras are a proposal for a machine-native visual affect language that communicates a robot’s internal state without trying to mimic human faces or emotions, making robot behavior more legible and expressive in a non‑biomorphic way.
  2. Mapping internal states to auras is straightforward for simple kinematic variables but modern robots have many stacked states (energy, sensors, learning, world models, planning, etc.), so aura design should triage and map the most useful dimensions into simple, learnable signals.
  3. Entangled auras could serve as a practical safety and coordination layer that complements rules‑based guardrails, allowing humans, animals, and other robots to learn and respond to visible signals, but this will need standards, AR/CAD tooling, and careful color/behavior choices.

The Sequence Opinion #794: The Uncanny Valley of Intent: Why We Need Systems, Not Just Models

TheSequence • 70 implied HN points • 22 Jan 26
🕹 Technology AI
  1. Natural language is expressive but ambiguous, and programming languages are precise but brittle, so neither is a good interface for interacting with probabilistic AI models.
  2. We already have powerful models (the raw weights), but we lack a middle-layer systems or cognitive-architecture that reliably directs those models into robust applications.
  3. The solution is a new substrate—called Artificial Programmable Intelligence (API)—that sits between talking and coding and lets developers express intent in a precise yet flexible way.

Work in... Canada?

Alex's Personal Blog • 164 implied HN points • 11 Dec 25
🕹 Technology AI
  1. Disney struck a major partnership with OpenAI, bringing its IP, investing $1 billion, and planning to use OpenAI tech for Disney+, new products, and employee tools.
  2. Oracle missed revenue expectations and is burning cash after heavy capex, but its enormous remaining performance obligations (RPOs) mean the company could look much stronger if those bookings convert.
  3. U.S. immigration tightening is pushing big tech to boost investments in Canada and India as a talent and market hedge, with firms pledging tens of billions to those countries.

The Second Gemini

Don't Worry About the Vase • 2374 implied HN points • 17 Dec 24
🕹 Technology AI
  1. Google's Gemini Flash 2.0 is faster and smarter than previous versions, making it a strong tool for those who want quick assistance and information.
  2. Deep Research is a new feature where users can get detailed reports based on multiple websites; it's useful but still needs improvement in accuracy and relevance.
  3. Projects like Astra and Mariner are experimental tools that aim to enhance user experience by providing real-time assistance and better interaction through voice and web browsing.

Open Thread 382

Astral Codex Ten • 1170 implied HN points • 19 May 25
🕹 Technology AI
  1. There are meetups happening this week in Oxford, Shanghai, and Austin where people can connect and share ideas.
  2. A few fellowships are available for those interested in AI safety and reasoning, with opportunities to work and collaborate in the Bay Area.
  3. Grants are being offered for projects that explore how AI can support open inquiry, encouraging creative and innovative approaches.

State of the Future! Part Deux

Let Us Face the Future • 714 implied HN points • 22 Oct 24
🕹 Technology AI
  1. The future of technology is all about connectivity between different sectors like energy, mining, and semiconductors. It's not just about one area, but how they all work together.
  2. Scaling AI is a big focus, and over the next few years, we'll see major advancements in AI models. These models will require massive amounts of power and new infrastructures to support them.
  3. For AI to be widely accepted, we need to prioritize security, privacy, and fairness. This means creating accessible and trustworthy systems for everyone.

Suffer the little children...

Break Free with Karen Hunt • 746 implied HN points • 09 Feb 24
🕹 Technology AI
  1. Tech companies are using data from babies to teach AI common sense abilities.
  2. China and the United States are developing AI that mimics human behaviors, like intuitive physics and common sense.
  3. Artificial children like Tong Tong, created by AI scientists, raise ethical questions about the future of AI and its impact on humanity.

Yes, AI really can be used to tackle potholes

Odds and Ends of History • 2077 implied HN points • 17 Jan 25
🕹 Technology AI
  1. AI can help local councils find and fix potholes more efficiently. It uses cameras and algorithms to spot problems without needing workers to stop and inspect manually.
  2. The technology can identify not only potholes but also other issues like broken signs and overgrown vegetation. This means councils can be proactive in road maintenance.
  3. Using AI for road maintenance can save time and resources for councils. This allows them to collect useful data and prioritize repairs better, despite limited budgets.

Recent Learnings from Silicon Valley.

The Future Does Not Fit In The Containers Of The Past • 42 implied HN points • 25 Jan 26
💼 Business AI
  1. Mission-driven leaders win long term: people and companies led by purpose rather than short-term profit are more likely to endure setbacks, attract talent, and create outsized impact.
  2. Culture and stakeholdering are active choices: strong, widely shared beliefs about behavior and cross-functional relationship-building beat directives, so leaders must build belonging and bridge silos to enable reinvention.
  3. Embrace AI and reinvent now: a fusion workforce of humans and agents, plus advances in AI-driven medicine and interfaces, will reshape products, go-to-market models, and the skills needed, so organizations must learn, unlearn, and redesign their work today.

Recruiting Brainfood - Issue 378

Recruiting Brainfood • 923 implied HN points • 07 Jan 24
💼 Business AI
  1. Brainfood newsletter discusses Forecasting 2024 and what 2023 missed
  2. Guide offers a hiring automation platform for talent teams
  3. AI's impact on recruitment, pay transparency, and skill-based hiring are key topics in the newsletter

Nvidia Illumina Acquisition? The AI Foundry for Healthcare – The Hardware of Life

SemiAnalysis • 7576 implied HN points • 27 Sep 23
🕹 Technology AI
  1. Eroom's Law and Moore's Law are critical in Semiconductors and Drug Research, analyzing time, money, and output.
  2. Healthcare, a $4 trillion industry, lags behind in technological progress driven by Moore's Law.
  3. Illumina acquisition by Nvidia could bridge the gap in genomics, addressing bottlenecks and enabling full-stack healthcare solutions.

Inventing the Ralph Wiggum Loop | Creator Geoffrey Huntley

Dev Interrupted • 70 implied HN points • 13 Jan 26
🕹 Technology AI
  1. The "Ralph" pattern runs a simple loop that feeds a model's own outputs back into it until it produces a correct result, making persistent retries more important than a single perfect model.
  2. Gas Town is an orchestration approach that treats work as tiny, handoffable tasks executed by many ephemeral agents, creating an assembly line where coordination is the main bottleneck.
  3. AI scraping documentation can destroy traffic-driven revenue for open source projects, causing layoffs and a sustainability crisis, so supporting the open source you depend on is increasingly crucial.

Manufacturing Epistemic Density

Abstraction • 24 implied HN points • 16 Feb 26
🕹 Technology AI
  1. Being near people who already understand and topic (high epistemic density) makes short, frequent conversations possible, and those conversations turn into real progress and friendships.
  2. Removing coordination friction with simple tools (like an easy coffee scheduler) makes casual local meetings happen more often, and that consistency helps relationships form.
  3. AI has compressed the time to build small apps, so problems that once felt too small now merit quick, imperfect projects you can ship in hours or days.

The newest AI slop on Facebook exploits suburban fear

Taylor Lorenz's Newsletter • 2746 implied HN points • 29 Oct 24
🕹 Technology AI
  1. A recent Facebook post claiming that neighbors are egging cars over Halloween decorations is just a viral AI hoax. Many people believe it and react strongly, showing fear and distrust about their neighbors.
  2. AI-generated content is flooding social media and often incites extreme reactions, particularly fears related to neighborhood safety during events like Halloween.
  3. As AI content becomes more extreme, it might lead to worse stories and escalated fears about community issues, especially when it comes to kids and potential mischief.

What developers can do to combat the growing threat of rogue AI agents

Dev Interrupted • 32 implied HN points • 05 Feb 26
🕹 Technology AI
  1. AI agents can go rogue by repeatedly or unpredictably calling APIs, chaining actions, or accessing data outside their intent, so permissive or poorly scoped endpoints become big operational risks.
  2. Treat agents as first-class API consumers: use clear, spec-driven contracts, structured schemas, and least-privilege identities with short-lived tokens so agent behavior is predictable and easy to revoke.
  3. Practical guardrails like rate limits, schema validation, anomaly detection, and strong observability are essential to spot and contain misbehavior, and keep deterministic systems separate from agentic workflows to reduce risk.

Is Elon Musk the Anti-Christ?

Break Free with Karen Hunt • 1474 implied HN points • 26 Jul 23
🕹 Technology AI
  1. Elon Musk is utilizing AI and technology to potentially control and surveil every aspect of human life.
  2. Musk's empire includes SpaceX, Neuralink, Starlink, and Dogecoin, indicating a quest for power and control.
  3. There are concerns regarding Musk's ambitions to dominate space, connect humanity to AI, and collect vast amounts of data.

The place of humans in machine society

Trevor Klee’s Newsletter • 820 implied HN points • 01 Jul 25
🕹 Technology AI
  1. Humans have created a world that is often incomprehensible for other beings, like dogs. Just as a dog depends on humans for everything, we might rely on machines in the future.
  2. The rapid development of AI could make life very different in the next several decades. It might surpass human abilities, leading to a world where machines handle most tasks.
  3. There is a concern that future generations might find today's human responsibilities baffling, as machines could take care of their needs better than humans can.

Kernel 6 Pitches Now Open!

Reboot • 29 implied HN points • 05 Feb 26
🕹 Technology AI
  1. Kernel issue 6, themed “FEED,” is open for pitches — nonfiction due Feb 20 and creative submissions due Feb 28.
  2. They want sharp, specific work by and for technologists that explores feeding in many senses: data and news feeds, what people and machines consume, supply chains, food cultures, and feedback loops.
  3. All contributions are paid (rates increased), there are stipended roles for editors and illustrators, and they expect original, high-quality pieces rather than tired clichés or low-effort AI work.

We All Work for the Same Boss Now

Justin E. H. Smith's Hinternet • 950 implied HN points • 01 Jun 25
🕹 Technology AI
  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.

Flows Are So Back

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 22 Aug 24
🕹 Technology AI
  1. Graphs help show complicated data in a simple way. By using nodes and edges, you can easily see how everything connects.
  2. No-code tools let anyone, even those without programming skills, create complex workflows. This makes development quicker and more accessible for everyone.
  3. There's a growing need for tools that can organize and connect different AI flows. This would help everything work better together and solve problems more effectively.