Programming
The latest Programming headlines, aggregated and deduped from public feeds across the web. See the sources.
The latest Programming headlines, aggregated and deduped from public feeds across the web. See the sources.

The exact circumstances surrounding the changes aren't clear, but Meta execs have accidentally tagged the band instead of their AI agent.
Matt Mullenweg, the founder and CEO of Automattic, best known as the parent company of WordPress.com, has been put on a leave of absence by his board against his will, according to a Slack message seen by TechCrunch. Earlier Wednesday, Mullenweg posted in a Slack channel visible to all employees that the company’s Chief Financial […]
TL;DR If you import Hls from 'hls.js', you are probably getting the ESM build, and the ESM build does not bundle the transmuxer worker. Transmuxing runs on your main thread until you set workerPath. We are going to verify which mode you are in, fix it, and add a long-task observer so you can tell main-thread stalls apart from network stalls. Two short facts before any code. hls.js 1.4 introduced the ESM build (dist/hls.mjs), and that build ships the worker as a separate file rather than inlining
Ghosts of Electricity: A look at why the oft-discussed predictions that AI will deliver double-digit GDP growth in advanced economies are extremely unlikely over the next 10-15 years — The following post represents the personal views of the author(s) and does not reflect or represent the positions of their employers.
TL;DR A fetch() upload dies when the OS suspends your app, and your JS context is recreated with no memory of it. We are going to build an upload that is a persisted record plus a state machine, hand the actual transfer to a native background session, and reconcile against the server when the app comes back. About 150 lines. Versions this was written against: Expo SDK 54 (React Native 0.81) and SDK 55 (React Native 0.83). Relevant because SDK 54 is the last release with legacy architecture suppo
Tim Bradshaw / Financial Times: The AI boom is fueling a resurgence in VC bets in “moonshot” sectors such as BCI; Dealroom says non-AI deeptech funding has topped $150B since the start of 2024 — Tech investors are rediscovering the kind of long-shot sci-fi bets that helped build Silicon Valley.
TL;DR Banding arguments go in circles because everyone tests on different footage. We are going to generate a synthetic gradient, encode it four ways (naive 8-bit, 8-bit debanded, 10-bit filter graph with explicit dither, and 10-bit AV1), and build a small harness so you can run it on your own ladder. Everything runs locally with FFmpeg, no assets to download. Written against FFmpeg 7.x/8.x. Check yours with ffmpeg -version. Real footage has sensor noise, and that noise dithers away banding by a
Bloomberg: Sources: Grab is in talks to buy a majority stake in Advance Intelligence Group's Singapore-based BNPL platform Atome Financial at a $2B+ valuation — Grab Holdings Ltd., the biggest ride-hailing and food-delivery firm in Southeast Asia, is in talks to buy a majority stake in Singapore-based buy …
OWASP Cornucopia Mobile App Edition v2.0 Johan Sydseter for OWASP® Foundation Sep 10 #cybersecurity #mobile #security #software Add Comment 8 min read
Emmy Martin / New York Times: How Amazon's Zoox, which has ~100 AVs in its fleet, is utilizing social media influencers, community events, and ad campaigns to compete with Waymo in SF — The Amazon-owned driverless car company is a distant second to Waymo. Its pitch to riders? Wine pop-ups, festival sponsorships and a car built to be filmed.
We are happy to announce the release of the OWASP Cornucopia Mobile App Edition v2.0. The latest edition is compatible with MASVS v2.1, MASTG v2.0, and MASWE v1.0, and features 80 threats that cover all the requirements, tests, and weaknesses of the OWASP Mobile Application Security Project. At Admincontrol, the OWASP Cornucopia Mobile App Edition is used to implement mobile application security by design. Before building mobile apps and features, OWASP Cornucopia helps the team identify threats
I have a small Node server — Express, a WebSocket hub, about 2,000 lines. It's a MeghXL. Running npm install, npm start. That's fine for me and a wall I wanted a double-clickable app for macOS, Windows and Linux, where the user has no Electron would have been the boring answer, and boring answers are usually right. I went with Tauri for one reason: size. My finished installers are 28–41 MB. The The cost is that Tauri is Rust and uses the OS webview, so the Node server can't Tauri has a mechanism
Viola Zhou / Rest of World: Chinese tech giants are hiring skilled professionals as specialized AI trainers to build high-quality datasets, mirroring efforts by US platforms like Mercor — Squeezed by a stagnant economy and state directives, China's underemployed lawyers, architects, and engineers are taking cheap gig work …
Adding a second agent creates a coordination problem before it creates a capability gain. Someone must define the assignment, preserve the relevant context, reconcile the result and decide whether another attempt is allowed. Those obligations exist even when the second agent produces nothing useful. The title describes that architectural asymmetry, not a universal measured growth rate: extra capability is possible, but it has to earn the machinery introduced to obtain it. Start with a working si
Maxwell Zeff / Wired: Q&A with AI researcher Jacob Coxon, who quit Anthropic, on the need for industry-wide, international coordination to limit recursive self-improvement, and more — Jacob Coxon talks to WIRED about the “mini Manhattan project” inside Anthropic, the problem with alignment …
In February 2021, security researcher Alex Birsan published a paper describing how he had successfully deployed malicious packages to the internal build systems of Apple, Microsoft, PayPal, Shopify, and 32 other companies. He did it without hacking a single server, exploiting a single CVE, or phishing a single developer. He published packages to npm, PyPI and RubyGems with names matching internal packages those companies used — and their build systems installed his public versions automatically.
Reuters: Sources: Chinese AI chipmakers Huawei, Cambricon, MetaX, and Iluvatar CoreX have raised prices for current and next-gen chips by 20%-50% due to rising HBM costs — Chinese AI chipmakers including Huawei Technologies [RIC:RIC:HWT.UL] and Cambricon (688256.SS) have sharply raised prices …
One executor, one pass, one commit - and the work can be dropped at any boundary. 👋 I'm Anton - a software engineer working mostly in PHP/Symfony and Go, currently carving a live PHP monolith into Go services. Earlier parts of this series were about what an executor must know, how small a unit of work has to get, and how to write a task with nothing left to interpret. This part is about the thing I only learned by having to stop in the middle: the unit at which work becomes droppable. Notes: gi
Océane Herrero / Politico: Sources including French public officials detail how Mistral's rise over the past three years owes much to the privileged relationship it built with Macron — Mistral has forged unrivaled ties with the French presidency. Now, Emmanuel Macron is departing. — in Paris
UOB polled business owners across the region and found something most vendors will not put on a slide: 65% of businesses have adopted AI in some form, but only 15% have reached what the study calls advanced capability. Read that again. Four out of five companies using AI are stuck somewhere between "we tried it" and "it changed how we work." The barriers the respondents named are where it gets interesting. Data and system readiness: 47%. Funding: 47%. Talent: 39%. Funding and talent are the answ
Paul Christiano / @paulfchristiano: OpenAI Foundation board member Paul Christiano says the AI industry is currently not on track to reduce the acute loss-of-control risk to an “acceptable” level — I am excited to be joining the OpenAI nonprofit board, serving on the Safety and Security Committee to support safety oversight.
An observability-first approach for building an AI agent, and what it bought me. A couple of weeks ago I started implementing Kept, a self-hostable post-purchase support agent for e-commerce, with reliability as its core offering. Besides the product itself, my objective in building it is to delve into the depths of agentic system design, and see what it actually means to build an agent with "reliability at its core". I started from a theory my experience validated again and again throughout the
Bloomberg: Sources: Alibaba is set to lead a $300M round in AI model testing startup UniPat AI at a $2.5B valuation; UniPat founder Li Kuan worked at Alibaba's Tongyi Lab — Alibaba Group Holding Ltd. is slated to lead a $300 million investment in AI training and benchmarking startup UniPat AI …
Two different logs, and teams keep shipping the first while believing it's the second. The first records that at 14:02:11 UTC, decision d_8f21 ran through model v2.3.1, took this input, produced this output, and a human approved it. Complete, timestamped, retained for six months. It satisfies most audit-trail checklists. The second proves the answer came from paragraph 4 of manual_A2131.pdf, retrieved at rank 2 with a score of 0.81, and that the sentence in the response is supported by that span
Annie Palmer / CNBC: Amazon names Mandiant founder Kevin Mandia to its board of directors, noting his extensive experience “combating cyber threats” in public and private sectors — Amazon said Kevin Mandia, the founder and former CEO of cybersecurity company Mandiant, is joining its board of directors.
Trello is one of the simplest project management tools and its API is one of the most straightforward to call. Yet CF7 to Trello integrations fail constantly, usually for the same handful of reasons that are never clearly documented anywhere. This post covers every cause of CF7 submissions not creating Trello cards, with direct API calls you can use to verify each piece before connecting your form. Trello uses a two-part authentication system that trips up most developers on first setup. You nee
Mikella Schuettler / Associated Press: New Mexico, the only US state taking the Cambridge Analytica case to trial, accused Meta of failing to protect Facebook user data in its opening statements — Attorneys representing the state of New Mexico told jurors that targeted political ads, attempting to lower Democratic turnout during …
I wanted a calculator site that behaves like a document, not like a web app. Type three numbers. Get the number of paint cans to buy. No account, no dashboard, no round trip to a server, no analytics watching you type. The page, the arithmetic, and the answer. That one constraint decided almost every technical choice below, and it is also why the numbers are small enough to print in a table. Here is a cold load of wallmath.com, measured in a headless Chromium on 2026-09-10 against the live build
Tim Fernholz / TechCrunch: Paul Christiano, an AI researcher and advisor at CAISI, is joining the OpenAI Foundation board of directors and its Safety and Security Committee — Paul Christiano, an influential AI researcher focused on keeping AI systems aligned with human interests and under human control …
Virtual machines, containers, serverless. Three ways to run your code, endless articles comparing them, and yet a lot of people still cannot say clearly why you would pick one over another. The confusion comes from comparing them on the wrong axis. Here is the mental model that made it click for me: each one is a different answer to "how much of the machine do you carry with your app," and once you see them that way, when to use which becomes obvious. Think of running your code as packing for a
Lauren Goode / Wired: Kepler Computing, which claims its 3D stacking and new material can increase HBM and SRAM density without relying on EUV, emerges from stealth with $468M — Kepler Computing claims a new approach to chip design—and a proprietary material—can help end the supply bottlenecks that have sent memory prices surging.
A year ago, adding AI to an app meant one API key and a few calls to one provider. Now most teams call several models across several providers, from several features, and the whole thing is a tangle: keys scattered in code, no idea which feature spends what, no consistent rate limits, no shared safety checks. The pattern emerging to fix this is the AI gateway, and if you are running AI in production, it is quickly becoming as standard as an API gateway or a load balancer. Here is what it actuall
There's a new visitor in your logs: the AI agent, acting on someone's behalf. Right now it "uses" your site by reading the DOM and guessing which button does what. WebMCP replaces the guessing with a contract — your page declares structured tools an in-browser agent can call directly. It's a draft W3C standard (Google + Microsoft) that shipped as an early preview in Chrome 146. Here's how to add it, step by step, with copy-paste code. A WebMCP tool is three things: a name a description the agent
Tim De Chant / TechCrunch: Massachusetts Gov. Maura Healey signs an EO requiring data centers above 25MW of peak demand to bring their own power and meet 100% of demand with clean energy — Massachusetts became the latest state to force data centers to bring their own power, but this time there's a twist.
The shift toward autonomous AI agents has exposed a critical gap in modern web infrastructure: the interface gap. For years, browser-based AI agents have had to navigate web pages the way humans do...parsing visual layouts, guessing CSS selectors, and attempting to mimic clicks. Connecting in-browser agent tools directly to modern cloud backends requires an architectural shift. By combining WebMCP on the frontend with Google Cloud Run on the backend, engineers can build a deterministic, resilien
New York Times: Sources: DOJ is investigating whether Nvidia tried to skirt antitrust scrutiny of its 2025 Groq deal, described by Groq as a “nonexclusive licensing agreement” — The Justice Department is examining whether the tech giant sought to sidestep antitrust scrutiny.
Security infrastructure looks clean in architecture diagrams. Production is messier. Stale data, delayed events, service failures, and emergency exceptions all affect real access decisions. This is Part 1 of Security Infrastructure in Practice, a series about what happens when security design meets production systems. The policy looked correct. Employees in the support function could view customer cases. Contractors could view only the cases assigned to them. Unmanaged devices were blocked from
Madison Mills / Axios: AI researcher Jacob Coxon says he quit Anthropic after four months, two months before his equity would have vested; he still has equity in prior employer OpenAI — Anthropic researcher Jacob Coxon quit his job due to concerns about the safety of AI two months before his equity would have vested, he told Axios.
I was closing out a throwaway repo from an agent-workflow experiment. I had treated experiment repos as cheap to delete once the hypothesis felt answered. The prototype had to go because leaving both checkouts live gave later agents two competing sources of precedent. Deleting it meant deciding what had been validated, writing it down somewhere durable, and removing experiment surfaces only after that record was complete. Standing up the narrow prototype had been genuinely fast. Portable agent p
Christine Mui / Politico: California Gov. Gavin Newsom signs into law two bills, backed by Anthropic and OpenAI, regulating how outside groups evaluate AI for safety — SAN FRANCISCO — California Gov. Gavin Newsom on Wednesday signed two bills regulating how outside groups evaluate AI programs for safety after warnings …
Firebase configuration embedded inside a mobile application is not the actual security boundary. The real risk begins when production services treat that configuration, an authenticated user, or the application interface as sufficient authorization. Attackers can reproduce legitimate requests outside the Android or iOS app. If Security Rules allow broad access, hidden buttons, navigation restrictions, and client-side validation cannot protect the underlying data. Checking only that request.auth
Hartley Charlton / MacRumors: Apple unveils AppleCare One Family, extending AppleCare coverage to every eligible device in an Apple Family Sharing group of up to 6 people for $49.99/month — Apple today announced AppleCare One Family, a new option for U.S. customers that extends AppleCare coverage to every eligible device across …
Die XZ-Backdoor: Ein Albtraum, der die Open-Source-Welt wachrüttelte Ende März 2024 hielt die Tech-Welt den Atem an. Ein Microsoft-Entwickler, Andres Freund, entdeckte durch Zufall eine der raffiniertesten und potenziell verheerendsten Backdoors, die je in einer kritischen Open-Source-Komponente gefunden wurden. Der Zielort: xz, ein unscheinbares, aber weit verbreitetes Komprimierungswerkzeug, das auf fast jedem Linux- und macOS-System zu finden ist. Der Vorfall, bekannt als CVE-2024-3094, war k
The Information: Sources: Jeffrey Katzenberg, ex-OpenAI Sora head Bill Peebles, and ex-Dropbox CFO Sujay Jaswa plan to launch a startup to train AI video models for filmmakers — Hollywood mogul Jeffrey Katzenberg is teaming up with the former head of OpenAI's Sora app to launch a new AI startup that would train …
Choosing between software licensing models is one of the most consequential strategic decisions founders make when building enterprise applications in 2026. Pick the wrong contract format and you can limit your distribution reach, restrict SaaS scaling opportunities, or accidentally force yourself to share proprietary code. Founders therefore need to weigh how to protect their core intellectual property (IP) while keeping operational margins clean. This guide explores the legal structures, open-
Sarah Perez / TechCrunch: Apple unveils a new Health app with Apple Intelligence, featuring an Insights tab, “readiness” and Health Age metrics, and more, rolling out later in 2026 — Alongside the new Apple Watch Series 12 and Ultra 4, Apple on Wednesday introduced a redesigned Apple Health app …
One of the biggest changes I've experienced in software development recently is how AI changes the process of building software. At first, AI coding feels like: "Give me the code." But that isn't where the real productivity comes from. The bigger advantage is being able to use AI throughout the development lifecycle: 🧠 Brainstorming architecture The developer still needs to understand why something should be built and whether the generated solution is actually good. AI can produce code incredib
Jason Shubnell / The Block: Consensys plans to split into two companies: MetaMask, with Joe Lubin as CEO, and a new Consensys focused on Ethereum and institutional infrastructure — - Consensys Software Inc. will split into two independently operated companies, separating its consumer-facing MetaMask business …
Open WebUI is one of the first tools that appeared in conjunction with Large Language Models. Initially intended as a tool for chatting with a connected local Ollama instance, it evolved to work with any OpenAI API provider and succinctly extended its features to support agentic chats. Following the setup of Open WebUI in my previous post, this article explores its core features. Learn about conversation essentials, see how notes and knowledge bases are created, and understand the different opti
Hi everyone! 👋 I’m excited to finally be part of the DEV Community. I’m a Software Engineer, WordPress Developer, and SEO Specialist with a passion for building websites that are not only functional and visually appealing, but also fast, accessible, and easy to find in search engines. I joined DEV.to because I want to connect with other people in the tech community, learn from their experiences, and share some of the things I’ve learned throughout my journey. Technology is constantly changing,
Artificial Intelligence is one of the fastest-growing skill areas in tech, but there is a problem. A lot of learners are spending more time collecting certificates than building things. They complete a Python course. Then a Machine Learning course. Then a Generative AI course. Then another prompt engineering course. At the end, they have several certificates but still struggle with a simple interview question: “What have you built?” That question matters. Because AI becomes much easier to unders
The longer I use AI, the more conversation history I accumulate. At first, that feels reassuring. More history should mean more useful context to return to later. But after enough ChatGPT, Claude, and Gemini conversations, I started noticing the opposite: the more conversations I had, the harder it became to find the moments that actually mattered. I could often remember that an important decision had happened. I just couldn't remember where. Search helped when I remembered the exact words. But
I ship a small Cloudflare Worker (a Claude Code status line that pays users a cut of disclosed sponsor revenue -- not the point of this post, just context for where the traffic pattern came from). Every install polls /line every 10-20 seconds while the user is coding. That's a lot of requests hitting one Worker. Rate limiting a Worker endpoint by install ID looks like a one-liner with KV: async function checkLineRateLimit(env, installId) { const key = `ratelimit:${installId}`; const raw = await
People think reputation The rescue. The outage you fixed at midnight. The demo that landed. It is not. It is made of the sentence "I will send you that link." "I will look at it this afternoon." "I will let you know either way Nobody writes those down. Everybody remembers them. Not consciously, He said he would, so it is handled. Or: he said he would, That second sentence You just notice, years later, The trap is that small promises They cost nothing at the moment of speaking. You say yes becaus
LeetCode problems 3870 and 3871 clearly show the transition from a simple case to a generalized one depending on the constraints. I would say this is a good example of why you should always ask about the problem constraints. The problems are very similar, but different constraints lead to completely different solutions. Both problems have the same description: You are given an integer n. total number of commas used when writing all integers from [1, n] (inclusive) in standard number formatting.
The demo is a text box. The product is the bad day. A model is a service Every rule you already hold You keep forgetting Time it out. Not the vendor default. Yours. Decide how long a user will wait Know what happens when it fails, If your answer is You have hoped. Degrade into something. The cached answer from yesterday. The dumb deterministic path An honest line saying Validate the output It is a form. It is the least predictable form Parse it, check it, reject it, Watch the money A retry loop
GPT-6 Astra shipped on September 3, and it arrived with an asterisk no model has carried before: it is the first model OpenAI has ever rated Critical for cybersecurity, because it can find zero-day vulnerabilities in hardened systems and turn them into working exploits without a human guiding it. The rest of the model is generally available. That specific capability is not, it ships gated, behind split access rather than open to everyone. That decision is a precedent, and if you defend infrastru
Ruby を書いていると必ず出てくる「ブロック」と「yield」。 「処理を渡す」「渡された処理を実行する」 だけです。 メソッドに渡す「処理のかたまり(コードの切れ端)」 のこと。 { } か do...end で囲みます。 [1, 2, 3].each { |n| puts n } # └──────────┘ これがブロック .each に「各要素で puts n してね」という指示書を渡しています。 1 2 3 { } と do...end は同じもの。長いときは do...end を使うだけです。 [1, 2, 3].each do |n| puts n end メソッドの中の「yield と書いた場所」で、渡されたブロックを実行する命令。 def あいさつ puts "こんにちは" yield # ← ここで渡されたブロックを実行 puts "さようなら" end あいさつ { puts "元気ですか?" } こんにちは 元気ですか? ← yield の場所にブロックが差し込まれる さようなら yield は好きな場所に置け、何回でも呼べ、値も渡せます。 def 数える y
A few months back I sat in a meeting where someone said, dead serious, "we should fine-tune the RAG." Nobody blinked. Everyone just nodded, the way you nod when a doctor says a Latin word and you'd rather die than ask what it means. Thing is, that sentence didn't mean anything. Fine-tuning and RAG aren't even the same species of tool. Nobody in the room knew that. Including, I'm pretty sure, the guy who said it. That's where we're at with AI right now. Everyone's using the words. Almost nobody k
The Question That Started It All "Hey Siri." "Okay Google." "Alexa." I kept asking myself: why? Your ears don't wait to be called to hear. Your brain doesn't wait to be called to remember. So why should AI? That question became Karl. What Karl Is No wake word. No button. Just presence. What it does: Listens in the background. Always. Remembers everything. Forever. Opens apps, makes calls, sets reminders. Privacy first. Everything stays local. No cloud. The idea: Your brain is for thinking. Karl
Entering the third week of my startup adventure has been a deeply rewarding time of solidifying foundations. Things come together to form an official brand, I put together tools to help with financial discipline, and I finished off the week by practicing my own Documentation-as-a-Contract (DaaC) framework. While I have an idea that I truly believe in and know exactly the components I need to build, I have been feeling excited about this venture before starting. But one question that would keep e
The Problem with Static Blocklists Malicious ads on Google Ads rarely land directly on a known bad domain. Instead, they route through a chain of redirects that rotates domains faster than blocklists can update. When attackers register a fresh domain, let it sit for a few hours, and then point users to it via a series of 302 redirects, even legitimate ad platforms can abuse this technique. Static blocklists fail because they only check the final destination. An attacker can create a new domain,
LinkedIn is going to be one of my direct integrations, if it's possible, so that I can write an article once and publish it on my own platform and do external distribution. Who has a non-svg logo available in 2026? I don't so I need to fix it. It would be easy to use some ad-ridden page to convert my svg-logo to a png for LinkedIn's consumption, but no, we're not doing that. We're doing it the only way we should, which is via cli. 1st we encountered an esoteric err: ffmpeg -i logo.svg -width 192
A developer runs pip install. Nothing crashes. No ransomware appears. No antivirus alert fires. Thirty seconds later, a Python process makes an outbound connection to infrastructure nobody on the team recognizes. Recent 2026 incidents show how quickly this can become a compromise. Malicious PyPI packages have been downloaded and executed by real systems, proving that developer workstations, CI pipelines, and security environments can themselves become targets. Typosquatting is an attack techniqu
I corrected the same Claude Code mistake more than five times. It never stuck. Then I replaced the correction with a 46-line shell script, and the mistake has not come back once. Some background: I started freelancing in college at around ¥100,000 a month, stacked side gigs until I reached ¥600,000, got laid off and dropped to zero, and spent the next six months building an autonomous Claude Code environment that now does ¥1.2 million a month in revenue. The single strongest lesson from that who
A step-by-step guide to pairing spec-driven development with stacked pull requests — from specify init all the way to a fully merged feature. AI coding agents are fast. Dangerously fast. Point an agent at a feature request and ten minutes later you're staring at a pull request with 180 changed files. Nobody reviews that. It sits for days, goes stale, and gets merged with a LGTM and a prayer. The fix is two tools working together: Spec Kit (specify) gives the agent structure — a spec, a plan, a t
In a simple probabilistic model, posterior inference sounds straightforward: observe some data, compute the posterior distribution over hidden variables, and use it to answer the question you care about. In complex models, that computation is often the hard part. The latent space may be high-dimensional, the posterior may have a complicated shape, and expectations under that posterior may be difficult to compute analytically. The practical question becomes: If the exact posterior is difficult to
FlatBB 0.1.70 (2026-09-09) turns community points into a first-class core feature — not a bolt-on plugin. Admins get one table for what each action pays: new topic, reply, like received, like given. You set how many times a day an action can pay a member, and whether the rule is on. Plugins can add their own rows. A post pays once, no matter how often it is edited or re-liked. The user menu shows the balance and a /points page with: this month’s earnings and spending history split into All / Ear
What happens when you stop treating your portfolio as just a website and start treating it as a searchable representation of yourself? Recently, I searched Google for: “Rishikumar Yadav Portfolio” The result was interesting. My existing portfolio appeared on the first page, along with multiple pieces of my online presence: Portfolio DEV.to article documenting the portfolio rebuild LinkedIn profile Images associated with my online presence This isn't a claim that I've "mastered SEO." It's simply
A backend engineer closed a laptop lid on a crowded commuter train and expected a local coding agent to keep working. The agent had been halfway through summarizing a public GitHub issue while a .env file sat two directories away. Local inference stopped the moment the kernel suspended the GPU, and a naive webhook to a hosted model would have uploaded the entire workspace. That gap between host sleep and unfinished public work is the actual design problem, not another routing slogan. Local-first
The table says 2,431 rows. You export it and get 50. Nothing errored. This is almost always virtualisation, and it is worth ten minutes of your time Rendering thousands of rows is slow, so grids render a window: the rows you can So at any moment the page contains fifty rows. Not fifty visible out of 2,431 Paste this into the DevTools console: const g = document.querySelector('[role="grid"],[role="treegrid"],table'); console.log({ claims: g.getAttribute('aria-rowcount'), inPage: g.querySelectorAl
The hard part of sharing an HR onboarding packet is proving what left the tenant. A watermark helps a support agent recognize an external copy, but it does not prove that the bytes were rendered from the approved template. For a US/EU SaaS, I would choose a Node.js PDF endpoint only after it can produce a signed receipt, a stable output hash, and a deletion record that survives a privacy review. Short answer: make the endpoint an evidence-producing job, not a file download. Render with a pinned
A coding-agent percentage remains marketing until protocol, canaries, and a cost ledger freeze beside it. Teams still quote a lonely pass rate as if that number could travel without a suitcase of hidden choices. Prompt text, tool allowlists, sandbox images, and grader prompts often move the score more than the model does. The honest unit of publication is therefore a registered protocol rather than a percentage standing alone on a slide. The protocol resembles a flight plan much more than a souv
Short answer: use the smallest realtime surface that can moderate a participant, then make reconnect, expiry, duplicate delivery, and authorization outcomes explicit in the test. For a property-management team sharing a stock-trading watchlist, that usually means treating the room as a state machine and reconciling by stable participant and event identifiers, rather than sleeping for an arbitrary number of milliseconds. The workflow is easy to describe and surprisingly easy to test badly. A brok
Multi-channel selling sounds simple on a slide: one product, listed everywhere, more customers. In practice, it's a distributed systems problem wearing a retail costume — multiple sources of truth, eventual consistency, third-party APIs with their own rate limits and quirks, and real money on the line when it goes wrong. Here's what actually breaks, and the patterns that hold up. The moment you list the same product on your own store, Amazon, and Etsy, you have three systems that each believe th
When I joined Synapsis Medical Technologies as the founding engineer, the roadmap was daunting: we needed to build a HealthTech AI platform that integrated wearable data, handled FHIR/HL7 standards, and maintained a HIPAA-aligned RAG pipeline with 99.9% uptime. To execute this, I had to scale the engineering team from 0 to 21 engineers in just 13 months. The standard industry approach to hiring—grinding candidates through LeetCode puzzles and red-black tree inversions—was never an option. We wer
We created 5,000 independent Kooboo websites from one fully dynamic site package, placed them on a small Tencent Cloud server, and sent 90,000 HTTPS requests from a separate Alibaba Cloud server across the public Internet. The Kooboo server had 2 vCPUs and 4 GB of memory. The load generator targeted 150 request starts per second for ten minutes, visited every hostname repeatedly, downloaded each complete HTML response, and verified that every response came from the correct numbered site. The res
A green check is a local fact. Merge is a promotion. If you let an agent-written diff jump from “tests passed on my laptop” to main, you skipped three decisions you still own: what was frozen, what CI re-ran, and what you will revert if the next hour is worse than the last. Copy the path below. Do not copy a feeling. You should not merge because a required check is green. You should merge because the patch survived a promotion sequence you can replay. That sequence has four stages. Each stage wr
What happens next is the pattern that shows up on almost every team that adopted agents seriously. Review turns into skim. The reviewer reads the PR description (written by the agent), checks that CI is green (on tests written by the agent, against a spec the agent summarized from the ticket it was handed), scrolls past the longest file because it's mostly generated boilerplate and approves. It looks like review. It's a signature. I'm not saying that to shame anyone, it's rational. Reading every
আপনার tour শেষ হয়ে গেছে এবং আপনি এখন বাড়িতে আছেন। আপনি বিকালে বসে বসে একটা জিনিস ভাবতে লাগলেন যে, অনেক কিছুই তো করলাম, এর মধ্যে এই এই কাজগুলো না করলেও হতো। আমার খরচটা একটু কমে যেত। যেমন ধরুন, flight-এর ticket না কেটে bus-এ করে গেলেই হতো, খরচ কমে যেত। আবার বড় কোনো 5 star hotel-এ না উঠে, ছোটখাটো normal একটা hotel-এ উঠলেই হতো, খরচ অনেক কমে যেত। কিছু কি relate করতে পারছেন? একটু কষ্ট হচ্ছে। আসুন অন্য একটা বিষয় নিয়ে কথা বলি। আপনি যখন backend নিয়ে কাজ করছেন তখন microservice নিয়ে আপনার মোটামুটি idea হয়ে
The Problem: The Modern Internet Feels Exhausting If you spend any significant time on mainstream social platforms today, you've likely felt the fatigue. Most modern platforms are tuned around a single metric: maximizing screen time at any psychological cost. Their algorithms deliberately amplify sensationalism, outrage, and polarizing debates because rage drives engagement. Meanwhile, genuine discussions get buried under bot farms, aggressive advertising, and synthetic noise. As an independent
The most expensive bug in the game I just shipped could only fire on 1.01% of rounds. Here is the shape of it. Replay is a betting game where the final score is public before you bet — the game ended 8–5, and what you buy is which of the 1,287 orderings of those 13 points actually happened. It runs on a casino platform whose host contract caps what a game may pay out: maxAllowedPayout = escrowedStake + reservedProfit Zero slack. The game quotes its own numbers up front — quoteCaps declares how m