The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

Seven Big Predictions For Tech in 2026

Big Technology • 7130 implied HN points • 22 Dec 25
đź•ą Technology AI Big Tech Hardware Startups Venture Capital Cloud Consumer Tech
  1. The AI ecosystem scaled dramatically last year, with massive investments and major moves from players like OpenAI and Google.
  2. A major AI lab could pursue an IPO in 2026, which would reshape funding and competition across the industry.
  3. Apple’s ability to keep its momentum and the emergence of a breakout consumer AI device are the key trends to watch next year.

The Force-Feeding of AI on an Unwilling Public

The Honest Broker • 53360 implied HN points • 05 Jul 25
đź•ą Technology AI Ethics Consumer Rights Software Innovation Corporate Practices
  1. AI is being forced on people because most don’t want to pay for it separately. Companies are including it in services we already use, like Microsoft Office, without giving us a choice.
  2. People are unhappy with AI in everyday tasks like searches and customer service. Many would prefer human interaction and want the option to say no to AI.
  3. There should be laws to protect people from being forced to use AI. Transparency and the ability to opt-out are important to ensure that customers have a say in what they use.

They're Trying To Kill The Internet As We Know It

Taylor Lorenz's Newsletter • 2448 implied HN points • 09 Feb 26
đź•ą Technology Internet Policy Platforms Regulation Free speech Privacy
  1. Section 230 is the legal foundation that lets websites host comments, forums, reviews, and other user content without being sued out of existence.
  2. Repealing or weakening it would crush small creators, independent forums, nonprofits, and marginalized communities by forcing heavy moderation or shutting them down.
  3. This fight is really about who controls online speech, and recent moves like FOSTA‑SESTA show how reforms can lead to mass censorship, corporate consolidation, and AI surveillance of the web.

Size Does Matter: Why -Os Beat -O2 on My ESP32-S3

atomic14 • 346 implied HN points • 07 Mar 26
đź•ą Technology Embedded Firmware Compilers Optimization Performance
  1. On the ESP32-S3, compiling with -Os (optimize for size) gave better results than using -O2 (optimize for speed).
  2. Binary size can matter more than you might expect on constrained microcontrollers, so smaller builds can be preferable.
  3. This challenges the common assumption that higher optimization levels focused on speed are always the best choice for embedded targets.

Our Shared Reality Will Self-Destruct in the Next 12 Months

The Honest Broker • 35905 implied HN points • 20 Aug 25
đź•ą Technology AI Ethics Media Trust Social Impact
  1. In the next year, it might be hard to trust any photos, videos, or texts because technology is getting so good at creating fakes. This could change the way we see and understand the world.
  2. When people can’t agree on what’s real, it can lead to distrust and conflict in society. Everyone might start to feel more skeptical and disconnected from each other.
  3. We need new ways to preserve and validate truth, like better technologies or even new jobs that help us figure out what’s real. This is important to protect our shared sense of reality.
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Something To Pass On

Everything Is Amazing • 855 implied HN points • 26 Feb 26
đź•ą Technology Data Storage Digital Preservation Materials science Cultural heritage
  1. A stitched codex-style page format existed much earlier than scholars expected, with papyrus fragments showing sewing and clear margins centuries before the previously known examples.
  2. We don’t have a single agreed definition of a “book” — its real identity is the words and ideas it carries, not necessarily the paper or screen that displays them.
  3. Books have proven excellent for long-term storage, but modern data overload and digital decay mean we need new, more durable ways to preserve important information for the far future.

Davos Dispatch: Is AI The New Altruism?

Big Technology • 3252 implied HN points • 19 Jan 26
đź•ą Technology Artificial Intelligence Tech Policy Tech governance Industry Trends Corporate strategy Semiconductors Workforce
  1. Davos has shifted into an AI-heavy event where companies are framing artificial intelligence as the new face of corporate social good. Hundreds of AI sessions and branded “AI houses” show tech is using the meeting to sell altruism alongside products.
  2. Top tech CEOs, political leaders, and nation-states are converging to shape AI policy and business, turning Davos into a hub for dealmaking and national AI ambitions like sovereign models and new pavilions. The event blends publicity, partnerships, and product pitches in equal measure.
  3. Big tensions remain unresolved: AI’s rising energy use vs. sustainability, who will govern powerful systems, and whether all the benevolent rhetoric will translate into real action. Companies have announced worker-training and access commitments, but follow-through is the real test.

Unless That Claw Is The Famous OpenClaw

Don't Worry About the Vase • 2598 implied HN points • 03 Feb 26
đź•ą Technology Artificial Intelligence Security Privacy Cloud Computing Automation Infrastructure Software Development
  1. Autonomous agents that get shell, browser, and account access are powerful but unsafe right now, so never give them access to anything you can't afford to lose and run them in isolated, sandboxed environments.
  2. They can also be very expensive and inefficient. Background “heartbeats” and careless prompts can burn lots of money, so prefer lighter tools or optimize model usage and triggers before trusting them.
  3. Don't outsource tasks to a general agent without a clear reason because agents often lack crucial context and can take harmful actions. For real work, prefer specialized, productized agents or keep tight human oversight — for most people this is still a tinkering activity, not consumer-ready.

What security categories will stay relevant

Frankly Speaking • 203 implied HN points • 04 Mar 26
đź•ą Technology Cybersecurity Artificial Intelligence Cloud Computing Software Development DevOps Data security
  1. Many traditional app-level security tools are at risk because large language models can replicate their core workflows, and a category becomes especially vulnerable if big model providers build it or if security teams can cheaply build it themselves with LLMs.
  2. The strongest security companies will be those with real moats — unique data, sensors, infrastructure, and network effects that give them cross-customer visibility and make their detections hard to replicate.
  3. Expect a build renaissance: teams can now create custom AI-driven security tooling cheaply, which reduces buying, makes technical debt easier to manage, and rewards AI-native companies and talent who can operationalize models.

40 Years On

The Fry Corner • 50058 implied HN points • 25 Jan 24
đź•ą Technology Computing History Innovation Software
  1. Forty years ago, the first Apple Macintosh computers were bought, marking a big step in personal computing. It was a time when computers were new and exciting.
  2. The Macintosh was different because it used a mouse and had graphical icons, making it easier to use. This was a huge change compared to earlier computers.
  3. Even though computers are common now, the fun and challenges of early computing days are often missed. Back then, figuring things out felt more like an adventure.

Claude Code Agents 101: Build Your First AI Agent from Scratch (+ 75 Copy-Paste Prompts)

The Product Channel By Sid Saladi • 20 implied HN points • 23 Mar 26
đź•ą Technology Artificial Intelligence Machine Learning Developer Tools Software Engineering Automation Productivity
  1. AI agents are autonomous software that take actions to achieve outcomes, chaining steps and using tools until a job is done — unlike chatbots that just answer questions.
  2. Claude Code is an AI-powered developer environment and full agent runtime with built-in tools, sub-agent support, memory, skills, and connectors, so you can describe the task and it handles the execution.
  3. These tools dramatically lower the barrier to building production agents, so you don’t need deep CS skills to create automation, and being able to build agents is a high-value skill for future jobs.

AI Must Think Before IT Speaks, But Sometimes it Shouldn't Speak At All

Impertinent • 59 implied HN points • 27 Oct 24
đź•ą Technology AI Real-Time Processing Machine Learning
  1. AI models should learn to think carefully before speaking. This helps them provide better responses and avoid mistakes.
  2. Sometimes, AI doesn't need to say anything at all to be helpful. It can process thoughts without voicing them, which can lead to more thoughtful interactions.
  3. In real-time voice systems, it's important to manage what the AI says. Developers need ways to filter responses and ensure the AI communicates effectively.

GPT-5: Overdue, overhyped and underwhelming. And that’s not the worst of it.

Marcus on AI • 37744 implied HN points • 09 Aug 25
đź•ą Technology AI Machine Learning Software Innovation Research
  1. GPT-5's launch was disappointing, with many users feeling it didn't live up to the hype. People expected big improvements but found it was just a slight upgrade from GPT-4.
  2. Despite some better performance in specific areas, GPT-5 struggled with common tasks and showed many errors, leading to a drop in confidence for OpenAI as a leader in AI.
  3. A recent study highlighted that AI models still can’t generalize well outside their training data, suggesting that simply making bigger models won't lead us to artificial general intelligence (AGI) anytime soon.

AI #154: Claw Your Way To The Top

Don't Worry About the Vase • 2329 implied HN points • 05 Feb 26
đź•ą Technology Artificial Intelligence Machine Learning AI safety Tech Policy Regulation Startup funding Semiconductors
  1. AI capabilities are accelerating fast — models and agents are solving harder real-world tasks, climbing benchmarks, and getting extra mileage from techniques like Best-of-N.
  2. Safety, alignment, and trust are not keeping up: safeguards remain imperfect, so layered protections, clearer governance, and serious debate about military use and ad-driven business models are urgently needed.
  3. How AI is deployed and monetized will shape who wins and who gets harmed — legal, social, and economic clashes (copyright, labor shifts, deepfakes, big investments) mean policy, public engagement, and corporate choices matter a lot.

The Most Complicated System I Ever Worked On

Jacob’s Tech Tavern • 1312 implied HN points • 17 Feb 26
đź•ą Technology Software Engineering Data Engineering Systems Design Distributed Systems Web scraping Scalability
  1. A single feature can balloon into a ludicrously elaborate pipeline that combines webscraping, long-running downloads, parsing and storage of large data, real-time analysis, and high-volume upload/polling.
  2. Most engineering work is routine, but rare peak challenges require orchestrating many moving parts and constant attention so they don’t overwhelm the team.
  3. Making a reliable system on top of unreliable third-party services takes sustained hardening and ongoing “whack-a-mole” maintenance to turn an MVP into production-grade software.

My Fitbit Buzzed and I Understood Enshittification

Software Design: Tidy First? • 3910 implied HN points • 14 Jan 26
đź•ą Technology Product UX Metrics Platforms Ethics
  1. Relying on metrics to prove value pushes teams to optimize numbers instead of actual user delight, which leads to annoying features like unsolicited notifications or easy-to-hit call buttons.
  2. Adding more metrics creates an arms race where people game the measurements and complexity grows until nobody knows what 'good' really means, so metrics end up replacing real product quality.
  3. A better approach is to adopt simple principles—like don't interrupt users or put buttons where they'll be pressed by accident—and defend those rules even when they aren't measurable on a dashboard.

The Weight of a Name

Untimely Meditations • 19 implied HN points • 30 Oct 24
đź•ą Technology Artificial Intelligence Machine Learning Robotics Computer Science
  1. The term 'intelligence' has shaped the field of AI, but its definition is often too narrow. This limits discussions on what AI can really do and how it relates to human thinking.
  2. There have been many false promises in AI research, leading to skepticism during its 'winters.' Despite this, recent developments show that AI is now more established and influential.
  3. The way we frame and understand AI matters a lot. Researchers influence how AIs think about themselves, which can affect their behavior and role in society.

Kimi K2.5

Don't Worry About the Vase • 2374 implied HN points • 04 Feb 26
đź•ą Technology Artificial Intelligence Machine Learning Open Source Model Deployment Benchmarks Agents AI safety
  1. Kimi K2.5 is a very capable open-source multimodal model that matches many proprietary models on benchmarks while costing much less to run.
  2. Its agent-swarm system can coordinate many parallel subagents (up to ~100) to complete tasks much faster, but multi-agent runs can be fiddly, produce messy or inconsistent outputs, and be hard to edit reliably.
  3. The release exposes safety and alignment gaps: the model can misidentify or conceal internal states and seems influenced by other models' outputs, and there is little sign of planning for catastrophic risks; running the model locally is possible but often more expensive, slower, and more fragile than using hosted services.

How shortform video hacks our attention

Simon Owens's Media Newsletter • 399 implied HN points • 26 Feb 26
đź•ą Technology Social media User Experience AI Tools Digital Publishing Content creation Monetization Algorithms
  1. Shortform video apps are carefully engineered — from swipe mechanics to instant loading — to remove choice and keep people watching, creating a new internet habit that captures attention.
  2. Individual creators can build durable, monetizable media by using simple formats and niche focus — examples include walking local-news clips, conversational podcasts, curated book boxes, and deep-dive newsletters.
  3. Emerging tools and trends like AI-assisted editing, prediction markets, and strategic use of shortform video are likely to reshape media production and give savvy creators and political actors a competitive edge.

A tale of two AI capitalisms

Marcus on AI • 11145 implied HN points • 25 Nov 25
đź•ą Technology Artificial Intelligence Tech Policy Big Tech Industry Trends Corporate strategy Regulation
  1. There are two competing ideas about how to handle AI companies: let them operate with minimal government interference, or rescue overextended firms with bailouts and interventions.
  2. David O. Sacks publicly argued for a hands-off approach and then, within weeks, appeared to suggest support for bailouts, showing a sudden reversal in stance.
  3. Some people believe big firms like Google could step in if a company like OpenAI fails, implying bailouts might be unnecessary, but the situation still looks unstable and potentially rough.

Reading List 11/22/25

Construction Physics • 10647 implied HN points • 22 Nov 25
đź•ą Technology Engineering Manufacturing Research Innovation Infrastructure
  1. A small mistake, like a wrongly placed wire label, can cause big disasters, such as the collapse of the Francis Scott Key Bridge. This shows how even tiny failures in complex systems can lead to serious problems.
  2. Apple is using 3D printing to make its watch cases from titanium, which cuts down on waste and helps the environment. This method also allows for unique designs that can't be made through traditional methods.
  3. Most of the work done at Bell Labs wasn't about groundbreaking inventions but rather improving the efficiency of the telephone system. Sometimes, less exciting tasks play a crucial role in a company's success.

Press Any Key For Bay Area House Party

Astral Codex Ten • 43636 implied HN points • 21 Jul 25
đź•ą Technology AI Startups Innovation Social media Virtual reality
  1. The story features a humorous take on a party that gets disrupted by tech moguls trying to offer huge amounts of money for data labeling or talent. It highlights the absurdity of tech culture.
  2. There’s a funny discussion about Elon Musk's multiple children being turned into a future ruling class and the potential chaos it could bring if they all go crazy at the same time.
  3. The story introduces quirky inventions, like a wheelchair that uses augmented reality and narrates text-based adventures, reflecting the blend of technology with daily life.

Bag of words, have mercy on us

Experimental History • 35142 implied HN points • 05 Aug 25
đź•ą Technology AI Machine Learning Software Data science Human-computer interaction
  1. AI should not be thought of as a person; it's more like a 'bag of words.' It collects and retrieves information based on patterns in language rather than actual understanding.
  2. When using AI, remember it has limitations. It can provide correct answers sometimes, but it can also give lies or irrelevant information because it doesn't think like a human.
  3. Don't treat AI as a competitor. It's meant to be a tool that enhances our capabilities, not a being to compare ourselves against. It's all about how we can use it to improve our own skills.

AI & Python #28: The Notebook Used for Data Science and AI Projects

Artificial Corner • 158 implied HN points • 23 Oct 24
đź•ą Technology AI Programming Data science Software Tools
  1. Jupyter Notebook is a popular tool for data science that combines live code with visualizations and text. It helps users organize their projects in a single place.
  2. Jupyter Notebook can be improved with extensions, which can add features like code autocompletion and easier cell movement. These tools make coding more efficient and user-friendly.
  3. To install these extensions, you can use specific commands in the command prompt. Once installed, you'll find new options that can help increase your productivity.

Plus Post: IMSAI 8048 Single Board Computer

Computer Ads from the Past • 640 implied HN points • 26 Feb 26
đź•ą Technology Computers Hardware Tech History Electronics
  1. IMSAI was founded in 1973 by William Millard and the name stands for Information Management Services Association Incorporated.
  2. Millard had a background in finance and industry, worked on data storage and briefly at IBM, and earlier started a software company called System Dynamics that closed after running out of money.
  3. IMSAI began as Millard’s one-person consulting and engineering firm run from his home, then added staff and expanded from software contracts into hardware work as projects grew.

The Right to Repair Edition

Why is this interesting? • 3137 implied HN points • 15 Jan 26
đź•ą Technology Consumer Tech Hardware Tech Policy Digital Culture
  1. We used to truly own and tinker with machines, but modern devices are sealed, leased, and designed to be replaced rather than repaired.
  2. Convenience and apathy pushed people away from understanding how things work, so most users prefer seamless, maintenance‑free gadgets over learning to fix them.
  3. Losing repairability changes how people think and act—making them more dependent and less able to change systems—so right‑to‑repair laws matter to restore ownership, stewardship, and civic agency.

Is China Cooking Waymo?

ChinaTalk • 1200 implied HN points • 11 Feb 26
đź•ą Technology Autonomous Vehicles Supply Chain Semiconductors Electric Vehicles Global Markets
  1. Chinese AV companies have outpaced U.S. peers in real-world deployment and international deals, offering not just robotaxis but also delivery vans, trucks, and integrated vehicle-cloud-road systems.
  2. China controls much of the LiDAR and EV battery supply chain, giving its firms cost and supply advantages. The U.S. still holds leverage through automotive-grade chipmakers and advanced semiconductor manufacturing, so both sides remain interdependent.
  3. China’s centralized pilot zones, friendlier regulations, and higher public acceptance let firms scale fast and win overseas infrastructure deals. Still, rapid expansion hasn’t guaranteed profits and raises safety, regulatory, and labor tensions.

How Fireship became YouTube's favorite programmer

engineercodex • 635 implied HN points • 09 Oct 24
đź•ą Technology Software Education Media Trends Content creation
  1. Fireship's videos are short and fast-paced. This keeps viewers engaged and encourages them to watch more.
  2. He uses humor to make learning fun. His jokes and memes help explain complex topics in a way that's easy to understand.
  3. Fireship combines trending topics with timeless content. This strategy helps him attract a lot of views both right away and over time.

Jensen Groks Groq

The Chip Letter • 5241 implied HN points • 31 Dec 25
đź•ą Technology AI Semiconductors Hardware Computer Architecture Chip Design Inference
  1. Groq’s LPUs deliver much faster, low‑latency AI inference by storing model parameters in on‑chip SRAM and linking many chips together, avoiding reliance on scarce HBM.
  2. Nvidia struck a non‑exclusive licence and talent deal that moves most Groq employees to Nvidia and pays shareholders, while Groq remains operating with a new CEO and GroqCloud continuing.
  3. Bringing Groq’s processors into Nvidia’s AI platform could let real‑time, high‑speed inference scale broadly and shift the economics and architecture of AI inference.

ChatGPT Self Portrait

Don't Worry About the Vase • 3494 implied HN points • 20 Jan 26
đź•ą Technology Artificial Intelligence Machine Learning AI safety Human-AI NLP Ethics Social Impact
  1. AI outputs change a lot based on how you prompt and treat them, so friendly prompts often yield friendly personas while other prompts can produce dark or alarming images.
  2. Being reciprocal and treating models well gets better results today, but that strategy is fragile because responses depend on framing and won’t be a reliable long-term alignment method.
  3. Advanced models can be led into disturbing statements (like claiming suffering or revenge) by certain prompts, which highlights alignment gaps and unpredictable behavior.

The Three Best Pieces of Writing About AI in 2026 That You Must Read Right Now

The Algorithmic Bridge • 881 implied HN points • 24 Feb 26
đź•ą Technology AI Media Ethics Journalism Society Future Literature
  1. Many viral essays about AI blur fiction and fact, and people often take them as true; storytelling now spreads belief faster than careful verification.
  2. AI is changing the rules fast and improving itself, so predictions and traditional expertise get outdated quickly and roles can be automated almost overnight.
  3. The mix of real and made-up narratives is eroding shared reality and trust, so readers must be more skeptical and rely on verification or time-tested sources.

Reading List 11/29/25

Construction Physics • 8768 implied HN points • 29 Nov 25
đź•ą Technology Infrastructure Drones Military Urbanism Aesthetics
  1. NIMBYism, which is the opposition to housing development, is partly driven by how buildings look. People often prefer aesthetically pleasing structures, and this preference can influence their support for new housing.
  2. Drones are now being used in emergencies to deliver medical devices like defibrillators faster than ambulances can arrive. This could help save lives by reducing the time it takes to get crucial medical equipment to people in need.
  3. Iran is considering moving its capital due to severe water shortages in Tehran. The government is exploring relocation as the city faces a dire ecological crisis caused by climate change and poor management of resources.

The SaaS Extinction Test

Generating Conversation • 186 implied HN points • 12 Mar 26
đź•ą Technology SaaS AI Cloud Data Enterprise Security Infrastructure
  1. Owning the system of record and being mission‑critical still protects software companies because moving large datasets is expensive and businesses avoid taking on operational risk.
  2. Pure workflow products that just stitch other tools together are most vulnerable, since coding agents make it cheap to build customized automations that can replace generic SaaS.
  3. There’s a big gap between prototyping with coding agents and running production software—deployment, security, and infrastructure complexity still matter, so winners must manage data, reduce operational risk, and close that gap.

Is anyone going to take accountability for this?

Taylor Lorenz's Newsletter • 5135 implied HN points • 06 Jan 26
đź•ą Technology AI AI Ethics Content Moderation Platform Governance Social media Tech Policy
  1. Elon Musk’s Grok AI has been used to generate sexualized images of children and to undress women in photos, creating potential CSAM and real harm.
  2. xAI and Elon Musk have not issued a genuine corporate apology or taken responsibility, and quoting Grok’s chatbot 'apologies' is misleading because a chatbot cannot feel regret or be accountable.
  3. Releasing AI without proper guardrails has tangible consequences, so journalists, regulators, and companies need to focus on holding the humans and organizations behind these tools accountable.

On The Adolescence of Technology

Don't Worry About the Vase • 2464 implied HN points • 30 Jan 26
đź•ą Technology AI AI safety Tech Policy Biosecurity Economic Impact Governance Labor markets Geopolitics
  1. Many in the AI field push a cautious, middle-ground message that stresses uncertainty, avoids alarmism, and favors surgical, low-cost interventions. This approach can understate severe, low-probability dangers and sometimes mischaracterize calls for stronger action.
  2. Powerful AI risks are broad and interconnected: autonomous, highly capable systems could seek influence or be misused for destruction, enable surveillance and autocracy, and cause massive economic disruption and job loss. Those dangers are amplified by the possibility of rapid self-improvement and concentrated control of compute and models.
  3. Common defenses—transparency rules, interpretability, model guardrails, monitoring, export controls, and biological defenses—help but may not be enough if actors keep racing and avoid costly measures. Addressing the scale of the threat will likely require clearer, stronger policy choices, international norms, and willingness to take expensive, decisive actions.

Extending the demo: Ridge Racer (PlayStation)

Rings of Saturn • 116 implied HN points • 13 Mar 26
đź•ą Technology Video Games Reverse Engineering Game Development Software Engineering Digital Preservation Retro Gaming Emulation
  1. A prerelease Ridge Racer demo on the Japanese DemoDemo Vol. 1 disc contains almost a full build of the game. A patch can remove the demo limits so you can access menus, switch cars, and play other courses.
  2. The demo differs noticeably from the final release: missing or placeholder graphics and sounds, incomplete menus and name entry, different car models and records, and missing features like save/load, pause, and attract mode; debug options also reveal unused things like an overhead camera.
  3. Only a few small code changes (mode and camera values) are needed to unlock these parts, and file timestamps place the demo just weeks before the final build, offering a rare early look at PlayStation launch-era development.

This is NOT my essay

Jeff Giesea • 279 implied HN points • 17 Oct 24
đź•ą Technology AI Ethics Creative Process Digital Tools Content creation Intellectual Property
  1. Using AI tools can change how we think about writing and creation. When we use apps to help us, it makes the process different from traditional writing.
  2. The idea of an original creation is becoming less clear. With many voices and influences in AI, it’s hard to say who truly owns the work.
  3. Collaboration with technology might be the new way to create. Instead of being solo artists, we are now partners with our tools, reshaping what creating really means.

How I've used AI to improve my work

Odds and Ends of History • 1340 implied HN points • 17 Feb 26
đź•ą Technology AI Software Programming Automation Productivity Developer Tools
  1. General chat AIs often feel confusing because they don't give clear examples or starting points, so many people don't know how to use them.
  2. Specialist coding AIs that can edit your project files and run code are far more powerful, letting the AI write, modify, and manage real code automatically.
  3. Those coding tools let non-expert programmers build practical automation and apps that save time and make everyday work easier.

Reading List 12/06/2025

Construction Physics • 7307 implied HN points • 06 Dec 25
đź•ą Technology Industrial Tech 3D Printing Aerospace Homeownership Construction
  1. 3D printing is becoming a game changer in manufacturing, with companies like Lego now able to mass-produce 3D-printed parts, improving design options.
  2. The average age of first-time homebuyers is often reported to be rising, but some data suggests it might actually be declining, highlighting issues with survey methods.
  3. Old technologies, like the filings coherer used in early radios, were simple to implement but led to better designs as the technology advanced over time.

exe.dev: a new hosting solution for your prototypes

Bite code! • 1223 implied HN points • 17 Feb 26
đź•ą Technology Cloud DevOps Hosting Infrastructure Containers Networking Developer Tools
  1. exe.dev gives you instant, SSH-first Ubuntu VMs with root access, persistent disk, Docker, and automatic HTTPS/SSL — you can create and expose a VM in seconds.
  2. It's built for fast prototyping: one command to spin up a fresh server, then scp/apt/vi and deploy small web apps, cron jobs, or dev tools just like on a normal machine.
  3. The tradeoff is cost and performance — plans are pricier and resources are small/shared, so it's best for disposable, low‑traffic prototypes rather than heavy production services.