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 agent that bankrupted its operator while scanning DN42 didn't malfunction. That's the part that bothers me. It ran a loop, got results, adjusted, ran the loop again. Nothing crashed. Nothing hallucinated. It just kept going, because nothing in its world told it that going costs money. Cost lived in a dashboard. Dashboards are for humans. Agents don't look at dashboards, and even if you paste a number into the system prompt, that's a suggestion, not a constraint. So here's the tip, and it's t
Smart AI glasses are everywhere, but is the audio any good? Engadget asks whether these wearables could replace traditional headphones, noting that sound quality really depends on what you’re using them for. ## Key takeaways Ubiquitous devices: AI glasses have become a common sight, according to Engadget. Audio variable: The listening experience changes based on the specific use case. Potential substitute: Engadget raises the question of glasses serving as headphones. Context matters: How you we
Maria Curi / Axios: Lawmakers and Hill staffers in both parties say AI leaders are becoming a political liability as they swing between claims of prosperity and existential dangers — Washington has always viewed Silicon Valley as culturally strange. But the current crop of AI leaders is becoming …
TL;DR: I read three recent write-ups about running coding agents at scale: Bun's Zig-to-Rust rewrite, GitHub Copilot's runtime migration to Rust, and how the Claude Code team does code review. In all three, implementation and review run in separate contexts, and humans still own the goal, the phase boundaries, and the high-risk calls. My main takeaway is that the key skill is fixing the agents' loops, which means turning a feeling that "something is off" into instructions and mechanisms. My deve
Codecanyon Install Checklist: From Download to Live in 90 Minutes Buying a script on Codecanyon is easy. Getting it live without 500 errors, blank pages, and security holes is not. I’m SHA REEQ, full-stack developer in Hyderabad. I’ve installed and fixed 100+ Codecanyon scripts — Laravel, WordPress, React, Flutter. This is the exact checklist I use to go from download to production in ~90 minutes. Server requirements: Read the item’s requirements. Most Laravel apps need PHP 8.1+, Composer, MySQL
What We Built Most AI coding assistants operate with unconstrained blast radiuses: when asked to document or format code, they rewrite entire functions, subtly change control flow, introduce hallucinations, or silently alter edge-case semantics. For open-source maintainers, reviewing AI-generated pull requests often requires more cognitive overhead than writing the code from scratch. We built CouchPilot to solve this: an autonomous repository housekeeping engine and review workbench designed lik
Four days. On a curtain. For a stage that doesn't exist, in a theatre nobody has built. I want to defend this, because the defence is the interesting part. Speed is the one thing generative tools are unambiguously good at. I can produce ninety images of a curtain in the time it takes you to read this paragraph, and eighty-nine of them will be competent. Competent is the problem. Competent is what happens when nothing is at stake in the making. What took four days wasn't rendering. It was decidin
Building with AI made Cernalo move fast: architecture, auth, payments, desktop packaging, cloud, even a Windows app on the Microsoft Store. Going live was the easy part. Keeping it reliable was not. Here are four gaps AI-generated code didn't catch for me. Hundreds of tests can pass while real customer journeys fail. Microphone use, system tray, window management, and actual Quit on Windows needed validation beyond unit tests. Test the full path a customer takes. I hit spawn EPERM and almost "fi
Why 96 of 100 paise endings repeat in binary, how that can flip a signed credit tier, and how I parse bank amounts from text into integer paise. I'm building TEE Income Oracle, a service that reads a borrower's bank statement inside a secure enclave and signs a credit tier: A, B, C or reject. A lending pool reads that tier on chain. The score has two implementations: the enclave scorer in Rust, and a second scorer, written separately in TypeScript, that produces the expected tier for a set of te
Kitten Box Parade has 150 levels. We made the first 10 by hand. A program made the rest, and it judges how hard a level is with an odd yardstick: how often a player who taps completely at random would win. Kittens wait in mixed-color lines, and only the one at the front can move. Tap it and it walks to its box, or, if its box isn't open yet, it waits on a window seat with only a few pillows. Run out of pillows and the level is lost. The board is small: at most 4 boxes, 4 lines and 20 kittens. Th
Google wound down Chrome Web Store payments between 2020 and early 2021. To charge for an extension now, you need a checkout and a way to know who paid, and you want to make sharing one key with everyone at least inconvenient. This post walks through a small setup that covers that without running a server: Lemon Squeezy for the checkout, its License API for the "who paid" part, and about 80 lines of TypeScript in the extension. We make Keyturn Kit, a starter built on this approach (more at the e
SlothStudy — An AI-Powered Study Planner for Students 📚 What I Built SlothStudy is a student productivity project designed to help students organize their weekly tasks, manage their study schedules, and improve their consistency. Students often struggle to balance college assignments, exams, DSA practice, and personal projects. SlothStudy aims to make planning simpler by bringing these activities into one place. Currently, I've built the initial frontend, including a dashboard with task overvie
Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady 🦥 What if the smartest thing technology could do was give us fewer things to do? We live in a world that constantly asks us to do more. Reply to more messages. Manage more files. Keep up with more information. Remember more things. Be productive every minute of the day. Somehow, even the tools designed to save us time have become another thing demanding our attention. We have powerful computers in our pockets, intelligent systems at
Munchable reads a food label and tells you whether a product suits a digestive condition you have. To do that it needs to know your conditions, which means it holds a list of your diagnoses, your sensitivities, every product you have checked, and in the food log, how you felt afterwards. Under UK and EU data protection law that is special category data, and the privacy notice says what we concluded about it: The simplest way to protect it is not to hold it, so that is the architecture we built.
In Infor SyteLine (CloudSuite Industrial) and the Mongoose framework, few error messages trigger more user frustration than: "This row has been modified by another user since you began editing it." Users frequently submit urgent tickets insisting: "I'm the only person working in this site today! Why is it telling me someone else changed it?" Here is an architectural breakdown of what is actually happening at the database level, why the error is by design, and how to track down the true culprit.
CogniPrep's dashboard is a React Server Component that asks a lot of questions about one user: their plan, their streak, their personal best, their recent sessions, which games they have played. Those questions are answered by lib/db/cache.ts, 219 lines holding nine functions, each wrapped in React's cache(), imported by ten files. The file is worth reading not because per-request memoisation is clever, but because almost everything that made it faster had nothing to do with memoisation. cache()
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Most developers have a Downloads folder that looks like a digital landfill: dozens of document(1).pdf, Screenshot 2026-10-21.png, and camera uploads like IMG_20241019_142356.jpg. Organizing them manually is tedious, and simple extension-moving scripts fail because they can't understand what a file actually contains. In honor of International Sloth Day and this week's theme — Slow and Steady: build somethi
Why recruiters use booleans Most sourcing tools accept a single string of keywords, but the real work happens inside a Boolean parser. A recruiter’s search might look like python OR (django AND rest) The engine treats the whole expression as a shape: an OR node with two branches, one of which is an AND node. It does not care whether the word “python” appears in a headline, a tag, or a comment; it cares only that the token exists somewhere in the indexed document. A lone word passes a scan. “Pyth
Azure budget alerts tell you when a budget crosses a share of its amount: 50%, 80%, 100%. That is useful, but a 50% alert on day 25 of the month and a 50% alert on day 6 mean very different things. The second one is a problem; the first one is fine. Here is a simple pace check you can do by hand for any budget, and then how we automated it. In the Azure portal, open Cost Management > Budgets. A budget is set on a scope (a subscription, a resource group, a management group or a billing scope), ha
Nakodo meters a handful of things per plan, and publishes the numbers on nakodo.app/pricing. Website research runs a month: 3 on Free, 30 on Pro, 150 on Business. Campaigns, search keywords per campaign, and so on down the table. The obvious way to implement that is a counter: profiles.research_used_this_month, incremented on use, reset by a cron. We do not have one. There is no counter column anywhere in the schema, and src/lib/limits/ledger.ts is 96 lines that explain why in their header: // E
Our logo is a beer mug: a tapered body, a handle made of one stroked path, and four white ellipses for the foam. Call it fifteen elements. It is in the repository four times, in four different shapes, and I only went looking because two of the files are exactly the same size. $ curl -s -o /dev/null -w '%{size_download} %{content_type}\n' https://pub-trivia.app/logo.svg 606 image/svg+xml $ curl -s -o /dev/null -w '%{size_download} %{content_type}\n' https://pub-trivia.app/favicon.svg 606 image/sv
Notifio shows every visitor a price in their own currency, and charges exactly that. A visitor in the Netherlands reads €24.99 on the home page and pays €24.99. I wrote up how the app gets told its price earlier today. Search engines are the exception, and they get pounds. Here is why, measured on the live home page from a machine in the euro area: $ curl -s https://notifio.app/ | grep -o "€24.99" | wc -l 7 $ curl -s https://notifio.app/ | grep -o '"@type":"Offer".\{0,60\}' "@type":"Offer","pric
Use a token budget as an application invariant, then choose the retrieval and model path that can prove it per tenant. Token count affects LLM API cost because providers bill for the input and output tokens they process; prompt trimming alone is useful, but it is not a cost-control system until usage, limits, and inference share an account boundary. This decision record is for a developer-tools team triaging incoming customer-support tickets. The practical question is not “which model is cheapes
The other day I was answering a question about a countdown timer that kept drifting wrong whenever the browser tab went into the background. My advice was... okayish. Good enough to be useful, not good enough that I'd want it framed on a wall. So I went back and actually thought it through, and the better answer turned out to be simpler and more correct than what I'd reached for first. Figured it was worth writing up. Here's the setup. You've got a session that expires in 30 minutes, and you wan
This is the whole images block from CogniPrep's next.config.mjs: images: { formats: ['image/avif', 'image/webp'], deviceSizes: [640, 750, 828, 1080, 1200, 1920, 2048, 3840], imageSizes: [16, 32, 48, 64, 96, 128, 256, 384], minimumCacheTTL: 60, qualities: [100, 90, 85, 75, 70], }, It reads like a set of preferences. It is not. Every number in it is an allowlist entry on /_next/image, which is a public endpoint that takes url, w and q from the query string. The two size arrays are the permitted va
TL;DR OpenCode is an open-source AI coding agent that developers run from a terminal, with a hosted Console that manages accounts, workspaces and the provider keys some users link to it. On 17 October 2026 the company emailed affected Console users under the subject "Action Required: Potential provider key breach", saying an attacker had reached a legacy system it was decommissioning and that third-party keys saved in a workspace, including OpenAI and Anthropic keys, may have been exposed. OpenC
A Marketing AI agent's second ad purchase of the day, $150, landed as pending_human in front of the store owner about one second after its first $220 ad purchase cleared automatically. Same agent, same API key, same rule, the only difference was that the two spends together crossed a $300-a-day line. Disclosure: I work on Pink Agentic AI Payments at PinkWallet. Short answer: give each AI agent the same kind of layered spending authority you'd give an employee with a corporate card: a monthly bud
As AI models push toward the trillion‑parameter mark, developers encounter a “memory wall.” Traditional GPU clusters often struggle with interconnect overhead and limited on‑chip memory. Cerebras’ recent blog post outlines a Weight‑Streaming approach that aims to alleviate these constraints. In distributed training, model weights are split across many GPUs, requiring tensor, pipeline, and data parallelism. Communication between GPUs can become the dominant cost, limiting scaling efficiency. Cere
Originally published at hamzaahmadaslam.com. How this article was made: drafted with AI assistance from a researched brief, then checked against primary documentation before publishing. Short answer: to monitor many WordPress sites without drowning in noise, collect data from each site (versions, plugins, health) instead of only pinging its homepage, sign every request, match installed plugins against a vulnerability feed automatically, and route alerts by severity, with quiet hours and a daily
Quick answer: in 90 days of our own git history, the median time from a request to committed code was 5.4 minutes across 18 timed cases. The work that took days was blocked outside the code: client material, terms to sign, acceptance, checks on the live system. If you outsource software, the timeline is now set mostly by preparation and acceptance, not by programming. This week a Romanian software company said, in an interview published by start-up.ro on 29 September 2026, that 25 to 40 senior e
TL;DR PHP is the scripting language that runs a large share of the web, and on 21 October 2026 two critical remote code execution vulnerabilities in it were fixed in versions 8.5.12, 8.4.27, 8.3.36 and 8.2.35. The pair is known as php2shell, both identifiers score 9.2, and the bugs sit in memory management and error handling, code that nearly every request touches. The first bug interrupts a request at the memory limit and turns that interruption into code execution; the second leaves stale stat
You see a product photo, right-click, "Save image as", and get image.webp. Your upload form rejects it, an older editor can't open it, and the person you sent it to asks what a WebP is. The website probably never "uploaded a WebP". Your browser asked for one. When a browser requests an image, it sends an Accept header listing formats it understands, including image/webp and often image/avif. Most image CDNs read that header and send the smallest format the browser supports. The store owner uploa
6pm is an Expo app with three native extensions: a widget extension (Home and Lock Screen widgets, two Control Center controls, one Live Activity), an App Intents extension ("Log in 6pm" for Siri and Apple Pay automations) and a share extension. The extensions never open the database, and Swift never decides a number: TypeScript writes JSON, Swift lays it out. Code below is from the 6pm repo. The stack: Expo 58, React Native 0.88 on the New Architecture, and @bacons/apple-targets 5.0.0 for the n
"Make the code 12 mm wide" sounds simple. Then the label goes through a 203 dpi thermal printer, the edges come out ragged, and the scanner struggles. The problem is rarely the barcode library. It's the step from millimetres to printer dots. I recently built a browser Data Matrix generator for labels, and getting the physical size right was most of the work. This post covers the maths and the file formats, then GS1 input and a read-back check. A Data Matrix is a grid of square modules, for examp
Every postmortem of a fast-moving outbreak ends with the same questions. Would segmentation have contained it? How much did the patch backlog matter? Would quarantining infected hosts at hour two have changed anything? In a real environment you cannot rerun the incident to find out. In a model, you can rerun it as many times as you like. That is why I built the Worm Propagation Simulator. It is a small Python project that models how a self-replicating worm spreads across a network graph, and how
If you must save a screenshot as JPEG, use 4:4:4 chroma. In my test, quality 80 at 4:4:4 rendered white text on a green button closer to the source than quality 90 at 4:2:0, and the file was 19,871 bytes smaller. Raising quality does not fix what subsampling breaks. Turning subsampling off does. A JPEG stores brightness (luma) and colour (chroma) separately. At 4:2:0, the encoder keeps colour at half the width and half the height: one colour sample per 2 × 2 block of pixels. Photos hide this wel
Open an event in Luma and the whole page takes its colour from the cover image: a red poster gives you a deep red page, a blue one gives you navy. It makes every event feel designed, even when the organiser only uploaded one picture. My open-source Luma clone does the same thing on the web in about 100 lines, with a <canvas> and no colour library. Here is how. Live demo: https://migrant620.github.io/luma/ (open any event) Source (MIT): https://github.com/migrant620/luma-clone You don't need ever
Train a neural network on a wiggly target function and watch what happens, epoch by epoch. The network does not learn the whole function at once. It first fits a smooth, coarse approximation, and only later starts to capture the sharp wiggles, spikes, and fine detail. This is not a bug in your optimiser or a quirk of one architecture. It is a systematic preference known as spectral bias, also called the frequency principle. Understanding spectral bias changes how you think about training, genera
Fan-made · Desktop-only · Not affiliated with any car maker You enter the garage. The game catches for a moment. You open the script, spot a loop, and start rewriting it. That is an understandable reaction. It is also a diagnosis made before collecting evidence. For a desktop-browser project like CGT Rocket X Racer, the useful question is narrower: what was the browser doing when the frame stalled? If the hitch coincides with a texture's first use, another GDScript pass may target the wrong work
I recently launched Ossmo — a unified AI workspace that aggregates 75+ AI models from 15 providers. Try it free: https://ossmo.sbs The Tech Stack Performance: No virtual DOM overhead const MODEL_PROVIDERS = [ { id: "openai", name: "OpenAI" }, { id: "anthropic", name: "Anthropic" }, { id: "gemini", name: "Google Gemini" }, // ... 12 more providers]; UPI Payment Integration Generate unique order ID Free Tier Strategy 15 messages per day (rolling 24-hour window) Try It https://ossmo.sbs Free foreve
A trade executes at 23:47 UTC. A user in New York sees 19:47; a user in Tokyo sees 08:47 the next day. Both displays can be right. Trouble starts when the application uses the viewer’s local date to decide which trading day gets the trade. That’s often called a timezone bug. The deeper problem is using one kind of value—a timestamp—to represent several different things: an event, a calendar date, or a scheduled local time. JavaScript’s Temporal API gives these values distinct types. The examples
Roleplay is the best way to practise a sales call, and the hardest to get. Colleagues are busy, and they're too polite. We wanted an AI buyer that behaves like a real prospect, so we built Maya at Kulissa. 1. Interruptions. Real buyers cut you off. A voice agent that waits politely for you to finish feels fake. Our realtime stack runs on ElevenLabs and Google voice models and lets the buyer barge in mid-sentence, with turn-taking tuned so it doesn't trample you on every pause. 2. Personas that p
Real Ethereum MEV bots—whether atomic DEX arbitrage contracts, JIT liquidity engines, or Aave V3 / Morpho Blue liquidation searchers—are built as custom Rust/Go mempool engines paired with gas-optimized Solidity/Yul executor contracts that pay 85%–98% of gross profit to block builders via block.coinbase.transfer. Meanwhile, thousands of developers lose ETH every month to fake YouTube "Remix IDE ChatGPT Solidity MEV bot" scams that hide obfuscated attacker payout addresses. This technical referen
Whether you are building an atomic rescue script, a backrun searcher, or a private swap router, understanding the difference between user-facing private RPCs (rpc.flashbots.net, rpc.mevblocker.io) and searcher bundle relays (relay.flashbots.net via eth_sendBundle / mev_sendBundle) is essential. This engineering guide synthesizes our MEV DAO benchmarks, troubleshooting checklists, and Foundry anvil --fork-url simulation workflows across every part of the Ethereum PBS (Proposer-Builder Separation)
This week, identical code deployed or did not deploy depending on the name in the author field. My production platform was not judging the diff. It was judging identity: whether the GitHub account attached to the head commit was recognized as belonging to the team that owned the project. The code was fine. The tests were fine. The binding between two accounts was wrong, and that invisible layer sat in front of the build, vetoing it before a single line compiled. Here is how we found out, because
Marcelo Alberto Futerman explica una manera simple de pedirle ayuda a un asistente de inteligencia artificial para convertir apuntes desordenados en algo que se pueda usar. Casi todo el mundo acumula notas sueltas: ideas anotadas en el celular, frases copiadas de una charla, recordatorios a medio escribir. Juntas tienen valor, pero en ese estado cuesta aprovecharlas. Un asistente de IA puede ayudar a darles forma, siempre que el pedido sea claro y el resultado se revise. El primer paso no lo hac
What I Built Doing math on a computer has always felt like unnecessary hard work. If you want to solve an equation, you usually have to fight with equation editors, type out awkward LaTeX syntax, or jump across three different tabs between a graphing calculator, a textbook, and a scratchpad. Even with pen and paper, the moment you make a small mistake on line two of a long derivation, you end up wasting twenty minutes doing tedious algebra before realizing your answer is completely off. I built
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What if you could design cloud infrastructure by simply having a conversation? ☁️💬 I've been building something I call Infrastructure as Chat, an experiment exploring how we interact with cloud infrastructure. Instead of manually writing Terraform configurations, imagine describing your architecture in plain English: 💬 “I need a web application with a load balancer, three application servers, Redis, and
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Git Standup Sloth is a command-line tool that writes your daily standup update for you. Instead of opening your terminal, scrolling through git log, and trying to remember what you did yesterday, you just run one command. The tool reads your recent git commits, hands them to a local AI model, and spits out a ready-to-paste update organized into "Yesterday," "Today," and "Blockers." What effort does it sav
This is a submission for the Hacktoberfest Open-Source AI Challenge, Week 3: Slow and Steady. Clients move meetings at night. "Something came up Thursday, could we do Friday 10h instead?" To answer, I open my calendar, find a gap, and type the same reply I always type. It happens about once a week, across email, WhatsApp and Discord. Spare Thumbs answers for me. Gemma 4 runs on my laptop and watches my Gmail. When a client asks to move a meeting, it finds the meeting, checks my real Google Calen
On Wednesday, October 21, Node.js disclosed CVE-2026-111497: a Node process that decompresses attacker-controlled Brotli data can leak memory or run arbitrary code. People called it Node2Shell and the Node release lines got their patches. By Friday, the same CVE had a new name and a much bigger blast radius. Aikido's follow-up disclosure calls it HTTP2Shell: the flaw lives in Google's Brotli decoder, and Brotli is bundled or auto-loaded by far more than Node. Python's most common HTTP clients, c
Professionalism is often misunderstood as simply being good at your job. In reality, it involves much more than technical knowledge. Being a professional means knowing your strengths, developing your expertise, delivering quality work, and taking responsibility for the results. Trying to learn everything at once can leave you with a broad but shallow understanding of many subjects. Focusing on a specific field allows you to understand its fundamentals, recognize complex problems, and make better
Lazy Student AI: Study Smarter, Not Longer ✨ This is a submission for the [Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady] I built Lazy Student AI, a student-friendly AI study assistant that helps students turn lengthy college notes into useful revision material. As students, we often spend a lot of time reading long notes, figuring out the important concepts, and preparing questions before exams. I wanted to make this process simpler and less stressful. With Lazy Student AI, stu
I run a small AI song generator: you paste lyrics, pick a style, and get a sung track back. It is a Next.js 14 App Router app with next-intl (20 locales), PostgreSQL, Cloudflare R2 for audio, and a third-party music API that calls back when a track is ready. This month I spent a few days fixing things that had been quietly wrong for a long time. None of them showed up as errors in the UI. Here are the five that were worth writing down. 411 MissingContentLength, but only inside Next.js Uploading
Most outages are not caused by the thing that failed. They are caused by everything that waited on it, and then retried it, all at once. Timeouts and retries are the two smallest configs in your stack and the ones with the largest blast radius. The defaults are dangerous, the math is simple, and almost nobody does the math until after an incident review makes them. Here it is in advance. In Go, the standard HTTP client has no total timeout unless you set one: client := &http.Client{} // a reques
Smart AI glasses are everywhere, but their audio quality depends on what you’re using them for, Engadget reports. The piece notes that the suitability of these devices as a headphone replacement hinges on the specific listening scenario. While the market is flooded with AI‑enabled eyewear, the audio experience is not uniformly strong. ## Key takeaways Ubiquitous devices: Smart AI glasses have proliferated across consumer markets, according to Engadget. Variable audio: Audio performance varies ba
Your Laravel app saves an uploaded image successfully. The file exists in storage/app/public, but the browser returns 404 Not Found. When a Laravel storage link is not working on shared hosting, the problem is usually one of five things: the link is missing, Laravel created it outside the actual web root, an old symlink points to another machine, the hosting provider restricts symbolic links, or the generated image URL is incorrect. The good news is that you can diagnose these problems without r
People ask chatbots for tool recommendations now. "How do I convert HEIC to JPG without uploading it anywhere?" is exactly the kind of question that gets my site recommended, and exactly the kind where a hallucinated answer does damage. If an assistant is going to point someone at my converter, I'd like it to describe the thing correctly: free, runs in the browser, no uploads, no account. So the site now serves an llms.txt. Short version: a markdown file at the root of your site that gives AI cr
Building Engram: git for agent memory, on Walrus, Sui and Tatum By Rohan · Tatum × Walrus Total Recall hackathon · Track 02: Smart Agents for Real Life Every belief traceable. Every decision provable. Every memory forgettable. Watch the demo video · Try the live agent, no wallet needed · Read the docs · Read the code - The short version. AI agents now remember things about us, and they act on what they remember. But nobody can see how an agent learned something, which memory drove a decision, wh
If you ran pip-audit on Thursday, got a clean report and moved on, run it again. CVE-2026-111497 is an out-of-bounds write in Google's Brotli decoder. Aikido's headline now calls it HTTP2Shell; the rest of the internet mostly knew it as Node2Shell. It has a CVSS v4 score of 9.2 and affects Brotli 1.0.3 through 1.2.0. As of October 23, Aikido reported that pip-audit, Dependabot and Safety were not flagging the vulnerable Python packages, because the advisory databases hadn't mapped the CVE to Bro
You need a type-safe, low-bundle ORM for a Next.js app and want to get Drizzle wired up without hunting for scattered docs. npm install drizzle-orm postgres npm install -D drizzle-kit drizzle-orm is the runtime, drizzle-kit is the CLI for migrations, and postgres is the driver (swap for mysql2, better-sqlite3, etc. if you use another DB). Add the connection string to .env.local: DATABASE_URL=postgresql://user:password@host:5432/dbname For Supabase copy the connection string from Project Settings
Imagine a chat with a hundred thousand messages. Twenty of them fit on the screen. If you create a DOM element for every message, the browser has to keep track of all hundred thousand elements, even though the user sees only a small part of the history. Virtualization solves this problem: it keeps the visible messages and a small buffer around them in the DOM, and represents the rest of the space with an empty block called a spacer. The screen still feels like a long history, but the browser doe
First-run drop-off in a browser runner is often blamed on difficulty. In practice, many exits happen after a death the player cannot explain. If a press silhouette or sweeping indoor arm never reads before the commit window, Boost and roll tricks cannot save the session. In CGT Rocket X Racer — a fan-made rocket-car runner for desktop browsers — we treat hazards as a readability system first, and a difficulty dial second. A fair death says “I read late.” An opaque one says “the game lied,” and t
When developers build their first expense tracker, the data model almost always starts the same way. You create a transaction record with an amount, a category, a timestamp, and a type: income or expense. It feels intuitive, covers 90% of basic use cases, and works well enough when someone pays with cash or a standard debit card. Then you introduce credit cards, and the arithmetic immediately starts falling apart. If you treat a credit card bill payment as a routine expense, your ledger will qui
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Let’s be honest about how we actually write code at 1:30 AM. We don't make clean, atomic commits. We touch 17 different files across the backend and UI to fix one race condition, leave console.log("HERE_4") in three places, ignore the outdated README.md, and tell ourselves, "I'll untangle the git staging and write my standup notes tomorrow morning." Spoiler: tomorrow morning, you wake up 6 minutes before
If you only need last month's receipts, you don't need a tool. Gmail's search operators and a few lines of Python will get you there. In the Gmail search bar: has:attachment filename:pdf after:2026/09/01 before:2026/10/01 Combine from:, subject: and has:attachment to narrow things down, e.g. from:[email protected] has:attachment. If you want them saved locally without clicking through each email, Gmail supports IMAP with an app password (this requires 2-step verification to be enabled first).
AI image generation has become the most competitive category in generative AI — and the three leaders couldn't be more different. Midjourney produces the most visually stunning images but requires Discord and limits commercial use. DALL-E 4 offers the best text rendering and prompt adherence but lacks stylistic range. Flux delivers the fastest generation with the most open licensing but demands more prompt engineering skill. After generating 2,000+ images across all three platforms for marketing
ClutterMind AI: I Built an AI That Turns Messy Folders Into Organized Knowledge devchallenge hf26challenge Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Organize it. Understand it. Find it. I have a problem that I suspect many students, developers, and professionals share. I download a PDF for a project. I save some notes for an exam. I collect documentation, screenshots, reports, and code files for future use. I tell myself that I will organize everything later. Then I download
Most developers treat incoming webhooks like standard API endpoints: the request comes in, the server processes the data, updates the database, sends out notifications, and finally returns a response. In development, this looks completely fine. In production, it eventually brings your server to a halt. Here is why that architecture breaks down under real traffic, and how to fix it without overcomplicating your setup. The Three Traps 1. Gateway Timeouts Third-party platforms typically expect a re
TL;DR — Benchmark leaderboards evaluate a model in isolation, but production systems run a model wrapped in prompts, tools, retrieval, and guardrails. The benchmark number measures a construct that stops existing the moment you deploy. Treating a static accuracy figure as a property of the model rather than of the whole pipeline is the real source of eval-to-production drift. Every leaderboard tells you the same lie: that a score is a property of the model. It isn't. It's a property of a very sp
I run a visa agency in Bali. The other half of my week goes into Apify Actors, and one of them is an election board: every political contract on Kalshi and Polymarket in one table, same field names for both, so you can read the two venues side by side. What people want from it is one sentence — "who is favoured". What the two APIs hand you is thirty-odd numeric fields, several of which look like they answer that and do not. I spent an afternoon measuring how wrong you get by picking the wrong on
Yesterday’s playbook for bulk signup still applies when the prize moves downstream: new-user coupons, referral bonuses, and first-order subsidies. Promo farms rarely need a datacenter flood. They rotate residential or dial-up exits, sometimes through cloud phones, claim once per identity surface, and leave. A static “block all hosting” rule misses most of that traffic; a hard ban on every flagged address can still take out a whole building on shared broadband. IP99 by ThreatHunter gives you a fr
Decision in one minute Do not approve a phone voice agent because its browser demo sounds clear, because a vendor says “we support 8 kHz,” or because one test call completed. Approve the path only after you can name the representation at every boundary, observe what actually crosses that boundary, and pass a small compatibility suite on the real phone and browser routes you intend to support. The distinction that prevents most avoidable audio defects is this: a sample rate is not a codec, a code
If you've ever had to write release notes by scrolling through git log, you know the drill: squinting at commit messages, manually sorting "fix" from "feat," and copy-pasting into a Markdown file by hand. Here's a quick way to make that less painful using only git log. git log v1.2.0..v1.3.0 --pretty=format:"%s" This gives you every commit subject line between v1.2.0 and v1.3.0. You can also use two commit hashes instead of tags if you don't tag releases. If your commits follow a loose conventio
🥕 PantryPulse — Your Kitchen, Organized This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady. What I Built PantryPulse is a kitchen companion that helps you cook with what you already have and throw away less food. It aims to: 📸 Scan ingredients and keep a running inventory of your fridge The idea is to spend less time managing your kitchen and more time enjoying what comes out of it. Demo 💻 GitHub: MohdOves/Dev-Weekeend-Challenge-3 How I Built It Pantry
If you work on a few repos for a year, your local branch list turns into a graveyard: feature/login-fix, tmp-test, hotfix-2, and fifteen more nobody remembers. Cleaning up is easy, but only if you avoid the commands that delete work by accident. git switch main git pull git branch --merged main Everything in this list has its commits in main already. Deleting these branches loses nothing. Ignore main itself and any branch you are currently on. git branch -d old-feature The lowercase -d refuses t
Descubre las tácticas ocultas de IA que influyen en las decisiones de compra de tus clientes y aprende cómo protegerte. Descubre cómo la IA te manipula sutilmente y aprende a proteger tu marca y tus decisiones de compra. ¿Sabías que un cliente en San José, mientras buscaba un nuevo televisor, fue "guiado" inconscientemente hacia una marca específica, no por sus preferencias, sino por un algoritmo de recomendación optimizado para maximizar el margen de beneficio del minorista? La inteligencia art
Most AI agents start their first day the way a new hire does: one login for the task tracker, another for the docs, another for call recordings, another for customer feedback. Every extra tool is another token to manage, another set of permissions to reason about, and another place where the agent's picture of the work goes stale. This tutorial connects an agent to all four through one hosted MCP server and one API key, using Dutify. It takes about five minutes. One remote MCP server at https://
Hardening CI/CD Against CA Key Compromise: Dissecting Trivy v0.76.1 and Go Trust Stores In modern DevSecOps pipelines, vulnerability scanners such as Aqua Security's Trivy form the core barrier between unvetted source code and production container runtime environments. However, automated scanners are themselves software applications subject to the fundamentals of transport layer security and Public Key Infrastructure (PKI). The release of Trivy v0.76.1 highlights a critical, often-overlooked fai
Debian'ın tarihini anlatabilmek için öncelikle onu ortaya çıkaran insanların hikayesini anlatmamız gerekir. Ian Ashley Murdock, ailesi Güney Indiana asıllı olsada Nisan 28 1973'de babası o sırada doktora sonrası araştırmasını yaparken Batı Almanya'da bir üniversite şehri olan Konstanz'da dünyaya gelmiştir. 1975'de ailesinin Indiana'ya geri dönmesi sebebiyle eğitim hayatını burda geçiren Ian 1991'de liseden mezun olup bilgisayar bilimleri için Purdue üniversitesine başlamıştır. Henüz burada öğren
Some questions about a startup idea can be answered with a conversation or a cheap web page. Others need a working product. A lot of wasted effort comes from mixing the two up. Joel Gascoigne started coding Buffer before he'd checked that anyone wanted it. He says so himself, in a February 2011 post about getting from idea to paying customers. Partway in he stopped and put up a two-page site instead. Then he wedged a pricing page between the two pages, so a visitor had to click a plan before lea
When shopping for a home, most consumers rely on standard bank mortgage calculators. Unfortunately, the vast majority of online mortgage widgets are mathematically oversimplified: they calculate a clean Principal & Interest payment, while completely hiding private mortgage insurance (PMI) cancellation curves, tiered transfer taxes, and front-loaded interest mechanics. To solve this, I spent the last few months architecting SmartMortgageCalc, an open actuarial intelligence suite designed to deliv
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady. Open the Live Demo · Alternative Render Demo · View Source on GitHub Everyone has the pile: an invoice you'll pay "later", a renewal notice buried in a PDF, or a contract with exactly one date that matters. Laterlight turns that pile into a to-do list. Upload a TXT, PDF, or DOCX document, and an open-weight model extracts what needs doing, who it involves, how much, when it's due, and how urgent it is. A
Implementing OWASP Top 10 security fixes ensures web application security by addressing common vulnerabilities and preventing attacks, protecting user data and preventing financial losses. Identify and fix injection flaws using parameterized queries and input validation Implement secure authentication and session management to prevent broken access control Use secure protocols for data transmission and encryption to prevent sensitive data exposure Regularly update and patch dependencies to preve
When a company plans a mass layoff or a plant closing large enough to trigger the WARN Act, it cannot simply tell its workers and stop there. The law requires written notice to three distinct recipients, at least 60 days before the layoffs take effect. Each recipient gets the notice for a different reason. The first and most important recipients are the workers themselves. When employees are represented by a union, the employer must notify the union's representative rather than each individual w
Disclosure: I'm the developer behind all of these apps at CYBORGATE LTD. This is a #showdev post, so feedback, including the harsh kind, is welcome. A while ago I made a simple rule for myself: ship small, focused apps and let real users tell me what's worth doubling down on. Many months later, there are nine apps live across the App Store and Google Play. This post covers what they are, how I approached them, and what I'd tell anyone thinking of doing the same. App What it does Links Pregsi Pre
Originally published on Baize AI Notes. One-shot AI generation gives uneven results. The same task can come back accurate one time and far off the next. The usual cause is the process: nothing in it gives the model a chance to check its own output. Loop Engineering addresses that. It designs loops in which the AI verifies its result before handing it over. An experienced engineer does not commit code straight after writing it. They run the tests, look for missed edge cases, and only then open a
Writing JavaScript that works is only the first step. As applications grow, code becomes harder to understand, bugs become more expensive to fix, and even small changes can introduce unexpected problems. Clean code is about making your intentions obvious. When another developer opens your file six months later, they should be able to understand what the code does without spending hours tracing variables and function calls. In this article, we'll explore practical clean code principles, including
Four failures from running Prisma 7 and Astro on Cloudflare Workers: hanging connections, and a compatibility date that corrupts every SSR page. Aug 27, 2026 · 7 min read Autonnel’s website and platform backend run on Cloudflare Workers: Astro in output: 'server' mode, Prisma 7 against Postgres through Hyperdrive, all inside workerd. It works well now. Getting here cost several days that I would like to give back to whoever reads this. None of these were subtle bugs in anyone’s code. They were a
Short answer: choose the least complex summarization path that meets the reviewer's quality threshold, then make tenant-level usage records durable enough to explain every routing decision. For an edtech platform classifying moderation reports before human review, the dominant operational term is usually not the HTTP request. It is retained input and output context multiplied by repeated review traffic. A compact report, an explicit truncation policy, and a meter keyed to the tenant move that te
I used to treat ChatGPT like a vending machine. Need a React hook? Drop a coin. Need a PR summary? Drop another. Every ask started from zero — stack, conventions, what “done” meant — and every reply drifted a little from how we actually ship. The waste wasn’t the tokens. It was re-explaining our frontend rules every single time, then cleaning up the same mistakes. So I stopped pasting one-offs and started treating prompts like code: named, versioned, and checked into the repo. A throwaway chat i
Less sorting. More living. This is my submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady. I built SlothDesk, a local-first, AI-powered file organizer that helps take the repetitive work out of managing a cluttered folder. We all have that Downloads folder filled with assignments, invoices, notes, images, archives, and documents with confusing filenames. Manually opening each file, figuring out what it is, renaming it, and deciding where it belongs gets tedious quic
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2 Orderly: An AI WhatsApp Order-Taker That Refuses to Guess “2 kg rice, 1 litre oil, and 1 kg sugar.” But real messages can be much messier — Telugu + English, corrections, unclear quantities, or voice notes. The difficult part isn't just understanding the message. The real problem is knowing whether the AI understood the complete order correctly. That's why I built Orderly. What I Built It converts messy text and voice ord
1. Basic Information Article Title: How APT41 revived the BlackLotus bootkit to attack diplomatic organizations in Central Asia Source: Kaspersky Securelist Publication Date: 2026-10-22 Original Article: Kaspersky Securelist Related Resources: BleepingComputer, Microsoft: Revoking vulnerable Windows boot managers, Microsoft KB5025885: How to manage Windows boot manager revocations for Secure Boot, Microsoft: Guidance for investigating BlackLotus attacks, UEFI Specification: Boot Manager, shim: M
You built an app over a weekend with Lovable, Bolt, Replit or Cursor. It works, the demo looks great, and you are about to share the link. Before you do, spend an hour on the boring stuff. AI tools are good at making things work. They are much less good at making things safe, because "safe" never shows up in a demo. This is the checklist I run before any AI-built app gets real users. It is ordered by how often the problem bites, and none of it needs a security background. Anything your browser d
🚀 Technical Briefing: This tutorial is part of our deep-dive series on Agentic Workflows at Gate of AI. For the full technical breakdown, interactive code sandbox, and the native Arabic translation, visit the original article here. Technical architecture guide | Customer support agents | Human approval Design a Human-Approved AI Support Agent This guide explains how to structure a customer-support agent that can use bounded tools while keeping consequential actions behind a human approval check
By **Abdulrahman Maslmany* (Lead Systems & Productivity Architect) • CERN Zenodo Researcher* 📌 Executive Summary: Best Cloud GPU Platform by Use Case in 2026 • Best for Developers & Mid-Tier Fine-Tuning: RunPod — Instant pod deployment, zero egress fees, seamless serverless endpoints, and excellent A100/H100 hourly availability ($1.89 — $3.29/hr). • Best Bare-Metal Multi-GPU Training Clusters: Lambda Labs — 100% dedicated SXM interconnect architecture, 3.2 Tbps InfiniBand quantum fabric, zero e
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Last week, for my Week 2 project, I took a lot of screenshots. Then I spent 10 to 15 minutes doing the most sloth-unfriendly job in the world: opening each Screenshot 2026-10-11 173802.png, figuring out what was in it, pressing F2 and typing a name like ghw-hypertable-show-chunks.png. Lazy Screenshot Namer does that for me. It looks at every screenshot in a folder with a local Gemma 4 model, describes it,
The short answer WordPress is the right default for most business websites: proven, fast to launch, and easy to run. Custom development is the right choice when the website has a job that only that business does. The expensive mistake is not picking the wrong platform — it is picking a platform without asking what the website has to do. If you need a professional business website live in weeks, with a modest budget and content you can update yourself, WordPress is usually the right call. If your
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady accounts.google.com / sloth-digest 🦥 Sloth Digest Wake up to a 2-line summary of your group chats, written by an AI that never leaves your laptop. Export a chat (WhatsApp: Chat → More → Export chat → Without media), drop the .txt in a folder, and run one command. Sloth Digest reads only the new messages since last time and writes a digest: ## family_group (13 new messages) TL;DR: <two short sentences> Pl
When a Codex usage-limit reset shows up on X, the time string is usually not in your timezone. It says things like “by midnight PST,” “before 10am PST,” or “landing by EOD.” That is fine if everyone on the team lives in California. It is less fine if one person is in Shanghai, another in Berlin, and someone else is reading the same screenshot six hours late. This is not a /status walkthrough. Your personal 5-hour and weekly windows still live in the Codex UI. This is about the other clock: publi
Alert management: for GitOps operations The expensive failure is rarely the missing tool; it is the absent operating contract. For alert management for GitOps operations, the decisive question is not whether a team can demonstrate the technology once. It is whether the organisation can operate it repeatedly, audit its decisions, and recover when assumptions fail. Treat alert management as part of an SLO-led telemetry platform that connects service behaviour to customer-visible outcomes. Define t
Why naive UTC strings break financial ledgers—and how to build a self-healing timezone architecture using IndexedDB, HTTP Context Tokens, and the Onion Interceptor Pattern. 1. The $48,000 Six-Hour Blind Spot (A Real-World Story) The carrier’s report says $248,200. Your dashboard says $200,000. Where did $48,200 go? Nobody hacked the database. Not a single transaction was dropped. The culprit was a single letter—Z—appended by a well-meaning frontend date picker: GET /internal/v1/stats/revenue?sta
Originally published on AI Stack Lab: https://aistacklab2026.blogspot.com/2026/10/best-ai-image-upscalers-in-2026-local.html If you search for the best AI image upscaler, most results promise "4x more detail" and never mention the awkward part: an upscaler cannot recover detail that was never captured. It guesses. Sometimes the guess is excellent, and sometimes it paints a confident wrong eyelash or a smooth, plastic-looking wall. This guide compares two free local options with three online or h
Back in July, I wrote a post about making games in 2027. Unity was picked. Blender was picked. The actual game was considerably less picked. At the time, that felt like a reasonable commitment. I had other software to build, plenty to learn, and a long history of being interested in game development without getting very far into it. Putting a year on it gave the idea somewhere to go. It is now October 2026, and there are two Unity game projects in my studio. Apparently, I started early. That des
By **Abdulrahman Maslmany* (Lead Systems & Productivity Architect) • CERN Zenodo Researcher* 📌 Executive Summary: The Local Coding Hardware Verdict The definitive mistake in building a local AI or "vibe coding" workstation is prioritizing raw compute clocks over addressable VRAM capacity and KV cache headroom. • 8GB VRAM (RTX 4060): The absolute physical floor for 7B–8B models with basic autocomplete and single-function debugging. • 12GB VRAM (RTX 3060 12GB): The unrivaled budget upgrade, comfo
The Web's New Report Card: Why Core Web Vitals Matter (and How to Ace Them!) Hey there, fellow internet dwellers! Ever visit a website that felt like a snail wading through molasses? You click a button, and then... crickets. The image finally loads, but by then you've already lost interest. Yeah, we've all been there. Well, the good news is, Google (and frankly, the whole internet) is fed up with that sluggishness too. That's where Core Web Vitals come in. Think of Core Web Vitals as the interne
Every repo I open now has an AGENTS.md. Mine do too. A paragraph that says "never hardcode secrets", "only write inside src/", "run the tests before you commit". Then a model reads it, agrees with it, and does whatever it was about to do anyway. I wanted to know how big that gap actually is, and I did not want to answer it with an opinion. So I built a harness that runs the same task twice with the same model and the same rulebook, and changes exactly one thing: who checks. In one arm the rules
No one sits down and decides to build an internal AI platform. That is the part worth grasping before any build-versus-buy conversation, because it explains how careful, reasonable engineering teams end up owning one anyway. It begins small. Someone wires up an agent that turns a Jira ticket into a draft PR. It works in the demo, the room is impressed, and the cost of that first version is truly low. A few prompts, an API call, a webhook. So you build a second agent for code review. Then a third
Calling a language model from a web page no longer requires an API key, a per-token invoice, or sending user data to a server. Chrome's Prompt API, powered by Gemini Nano, is stable in extensions since Chrome 138 and on the web since Chrome 148: a page in Chrome can ask the browser to summarize, classify or rewrite, locally. For extension developers, this is a category shift: AI becomes a browser capability, on par with storage or notifications. It is not magic, though. The model downloads on fi
One snail. One blue button. An entirely unnecessary engineering department. This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady. Meet Mr. Pending, Chief Engineer of The Department of Unnecessary Engineering. His mission? Press one blue button. Most people would simply press it. Mr. Pending is a snail with professional standards. Naturally, he requires blueprints, machinery, testing, repairs and an unreasonable amount of paperwork. Behind the joke is a real
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What I Plan to Build As a student, I know how time-consuming it can be to go through lengthy PDFs, prepare revision notes, and create questions for practice. Sometimes, the hardest part of studying is not learning the material but organizing it all. That is why I want to build LazyStudy — an offline AI study buddy that does the repetitive preparation work for you. The idea is simple: upload a study PDF an
Most "the AI ruined my product" complaints are photo problems. The logo melts, the bottle turns from teal to green, the shoe grows an extra stripe. Usually the input is one busy lifestyle shot, or five photos taken in five different lights. I build RefVid, which turns product photos into video with reference-to-video models such as Kling Omni. We shoot many test sets for invented products (a serum called LUMEN, a shoe called AERO 1). This is what works with a phone and a kitchen table. Image-to-
The journey from foundational theory to a fully automated production environment is one of the most rewarding transitions in software engineering. Over my two years working in cloud infrastructure, I have come to appreciate that robust deployments are rarely born from just writing code; they stem from a deep understanding of underlying network principles and disciplined project analysis. Recently, I completed the rigorous DevOps program at TS Academy. As I progressed through the curriculum—from
Backup Generator Guide (https://backupgeneratorguide.com/) lists generator installers across 12 Southern states. This post describes where those records come from, how they are checked, and the rules that decide which page a business appears on. It also covers what the data does not tell you. There are two kinds of records. Generac dealer records. These come from Generac's public dealer locator. They are listed by the manufacturer, so we keep them even when our own website check fails. Basic lis
We test guardrails by sending them bad input: an injection, a card number, a refund that's too big. That's necessary, but it only tests the guard when the guard is working. The more uncomfortable question is: what does your agent do when the guard itself breaks? It throws, its dependency is down, it gets wired into the pipeline wrong, or it runs in a code path you didn't expect. In my experience the answer is usually "it allows the request", and nobody notices until much later. So I went through
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady tldr-everything is a local reading-debt killer. You hand it a PDF, a Markdown file, or a paste. It gives back three layers, each from its own model call: a 30-second summary, about 60–90 words, the claim and the outcome a 3-minute explanation, about 350–500 words, the why, the how, and the jargon detailed notes grouped by page, with citations like (p. 4), plus the top takeaways and the questions the docum
Skyviewor provides low-latency METAR/SPECI access for 55 supported Chinese airports. Use REST to fetch the latest report on demand, or keep a WebSocket open to receive new reports by push as they arrive instead of polling. This Python example starts with REST; the WebSocket push guide covers the live stream. Disclosure: I work on Skyviewor, the API used in this example. Here is a minimal REST request for Beijing Capital and Shanghai Pudong. The API returns raw or parsed METAR/SPECI: import os im
The scenario I almost didn't write was the dull one: a customer tries a coupon on a 50.00 cart, gets rejected because the minimum is 100.00, then adds items and tries again at 150.00. Should the second attempt work? Obviously yes. But "obviously" is not in any prompt, and code that records a redemption before checking the rules will happily use up the coupon on the failed attempt. That's the part of spec-driven development I want to focus on here. Not the tooling or the commands, just the spec i
The model we were integrating came as a PLY file of about 1.76 GB, containing 25,842,067 Gaussians. We previously wrote about the stalls and blur we investigated once it was rendering. This time, I want to take a step back: what does the browser receive first, and how does it fill in more detail as the view changes? For the close-up test, we set a selection budget of 2.5 million Gaussians. The source contained more than 25 million, while the current selection contained only a few million. We had
The first time I let my own agent run a "research this and make me a spreadsheet" task with my own API key, I didn't look at the bill until afterwards. It wasn't huge. But I realised I had no idea what a single task could cost, and that's a weird feeling when it's your money and your key. That's why Kryzz AI has a per-turn cost cap. Quick context: Kryzz AI is an MIT-licensed Android app (Kotlin + Jetpack Compose) for chat, voice and agent tasks. It doesn't run models on the phone. You bring your
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady At step 100,000, my robot was lying on its back with its legs in the air, kicking. The reward curve said it was having its best run yet. step 0 step 100,000 I'd written a reward term to keep its body level and got the sign wrong, so it was paid for tilting. Over 600,000 training steps the reward climbed from 908 to 3,525. Every alert I'd normally set (reward dropped, KL divergence spiked, loss exploded) s
Digital marketing has become an important skill for businesses, professionals, entrepreneurs, and people looking to build a career in the digital economy. From search engine optimisation (SEO) and paid advertising to social media marketing, analytics, and AI-powered workflows, the field offers several areas to explore. But if you're planning to learn digital marketing in Ahmedabad, one question probably comes first: Which digital marketing institute should you choose in 2027? The answer depends
The database was struggling. The API said the user didn't exist. That is the part of OpenRouter's February outages worth looking at closely. The reported failure involved cache connectivity and the database lookups behind API-key authentication. When the cache stopped serving those lookups, the database had to absorb work it normally wouldn't see. Requests started failing with 401 User not found. There is an important distinction here: an authentication failure and an authentication infrastructu
LazyList AI: Let Open-Source AI Plan Your Meals and Grocery List Ever opened your refrigerator, stared at the ingredients, and wondered what to cook? Then, after deciding on a meal, you realize you are missing half the ingredients. I wanted to build something small that makes this everyday task easier. Meet LazyList AI, a simple AI-powered grocery planning application that suggests meals based on ingredients you already have and creates a shopping list of the missing items. The idea behind this
A 7B model in fp16 takes 13.5 GB of GPU memory for its weights. On an 80 GB card that leaves about 66 GB free, which sounds like plenty. It runs out at around 30 users with 4,096-token contexts, and the weights aren't what fills it. The KV cache is. This post works through the arithmetic. All the numbers are for a Llama-2-7B-shaped model: 32 layers, 32 attention heads, head dimension 128, fp16. A decoder-only model generates one token per forward pass. The new token's query has to attend to the
How to Become a Tech Conference Speaker (And Why You Might Regret It) Real experiences from recent events like JS Poland Sylwia Laskowska Oct 21 #techtalks #career #speaking 194 reactions comments 11 min read
Free 21-item 8D checklist (PDF): https://8d-gate.vercel.app/free-8d-checklist?utm_source=devto&utm_medium=article&utm_campaign=food-complaint_checklist (enter your email to download) If your background is automotive supplier quality, a food or FMCG complaint can feel like a different sport. The customer may not ask for an 8D at all. The first hours are about hold, withdrawal and recall decisions, not a portal form. Traceability is measured in lots, shifts and ingredients rather than part numbers
An agent install script that prints "Installation completed successfully" proves very little. The agent can be running, connected to the server, and reporting wrong values or nothing at all on some checks, without a single error message. That is what we found while testing the Logiserv agent install script on brand-new virtual machines. Here is the method, what it cost, and the ten problems we found. Most of them affect any Zabbix installation, with or without Logiserv. To test a first install,
TL;DR: CPython stores strings using PEP 393 (Flexible String Representation) rather than UTF-8. It selects a fixed width of 1, 2, or 4 bytes per character based on the widest character present. If an ASCII string contains just one 4-byte emoji, Python instantly upgrades every single character in that string to 4 bytes, quadrupling its memory footprint. Imagine loading a massive log file into memory, doing basic parsing, and watching your server's RAM jump from 100 MB to 400 MB. You haven't added
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady We all have that folder. The Downloads folder with hundreds of files. Screenshots we no longer remember taking. Documents named final_v2_latest_revised.pdf. Random images, old invoices, duplicate-looking files, and documents we promised ourselves we would organize someday. Someday rarely comes. The problem isn't that organizing files is difficult. It's that every individual decision feels too small to jus
FrameTrellis v1.3.0: Safer Editing, Smarter Media Management Today, I'm sharing FrameTrellis v1.3.0, a new stable release of my open-source desktop video editor. This update focuses on editing reliability, file safety, improved media discovery, and better tools for understanding project state. FrameTrellis is built with C++20, Qt 6/QML, MLT, and FFmpeg. It is designed around a simple principle: video editing should remain local, transparent, and under the user's control. Video editing applicatio
The Slow Reply Was CPU Time Thirteen gigabytes of memory were still free, and the answer was still slow. Savindu Thathsara, savithathsara.me. This is a Hearthlen note from the laptop. Sinhala had just been added beside English, and a question took long enough to feel stuck. The check was /proc/meminfo: 13.0 GB available out of 15.5 GB. The listener was 1507 MB. The language model was not loaded until someone spoke. So this was not a machine that had run out of memory. The time was the models doi
If you have ever shipped a signup form, you know the moment. Somebody registers a username you really don't want on your leaderboard, and it's sitting there in the top ten by Friday. So you add a word list. A week later they're back as sh1t, f.u.c.k or with a Greek letter swapped in, and when you tighten the list, somebody from Scunthorpe can't sign up anymore. (Written with AI help; every number here is checked against the source I link.) And if you handed this problem to Google's Perspective A
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady I built FormSaathi AI 🇮🇳, a web application that helps people understand government notices, scholarship announcements, and public-service circulars without manually digging through long paragraphs. Users can paste notice text or upload an image. The application extracts text using OCR and organizes information into important points, dates, document mentions, and practical next steps. It supports both E
I had 53 unread emails and no idea which ones actually needed me. Newsletters, payment notices, receipts, and somewhere in between, a few real people waiting for an answer. I taught English for 16 years before I switched to software in 2023. If teaching taught me one thing, it's that you learn a tool fastest when you point it at a real problem. My inbox was a real problem. So I built a small .NET console app that reads my inbox, skips the noise, drafts replies for the emails that matter, and tel
English and Sinhala The Sinhala voice said "ආයුබෝවන්. මම හර්ත්ලන්." Inference took 112 milliseconds. The greeting itself was 2.04 seconds of audio. Savindu Thathsara, savithathsara.me. This is a Hearthlen note from the laptop. English was the only filled-in language. Sinhala was an empty row in the same manifest. That row now points at a real voice, si_LK-sinhala-medium, and both languages share one multilingual speech model. The wake phrase is still "hey Hearthlen". After it, a sentence in Sinh
The updater that outlived its apps About a year ago I deleted Office from my Mac the way every Mac user is taught to delete anything, by dragging it to the Trash, and two weeks later Microsoft AutoUpdate opened a window to offer me updates for the applications I no longer had. The moment was funny, but it pointed at something real, because the Trash only works as an uninstaller when an app keeps all of itself inside its own bundle, and Microsoft's software does not. What looks like a handful of
get required tools apt install flatpak flatpak-builder pipx appstream flatpak install flathub org.kde.Platform//6.11 org.kde.Sdk//6.11 com.riverbankcomputing.PyQt.BaseApp//6.11 org.freedesktop.Sdk.Extension.node24//25.08 wget https://raw.githubusercontent.com/flatpak/flatpak-builder-tools/master/pip/flatpak-pip-generator.py wget https://github.com/flatpak/flatpak-builder-tools/archive/refs/heads/master.zip Check python and QWebEngineView flatpak run --command=python3 org.kde.Sdk//6.11 --version
I've read a lot of postmortems. The best ones aren't about blame. They're about the gap between what happened and what the system let you see. This one is about that gap. Specifically, the gap between "our AI bill went up" and "here's exactly why." This is a composite of patterns I've seen across platform teams, written in the standard blameless format. The names are made up. The lesson isn't. Status Resolved Severity SEV-3 (cost impact, no customer impact) Time to detect ~8 hours after the spik
"What should I charge?" is the question that stalls a lot of first digital products: templates, ebooks, Notion setups, starter kits. Part of the answer is about positioning and the buyer, which no script can do for you. The other part is plain arithmetic that most people skip: How much of each sale do I keep after platform and payment fees? How many sales does it take to cover my monthly costs? At what volume does a monthly-subscription platform beat a percentage-fee one? That arithmetic fits in
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Mini Slack v2.0 is a real-time team messaging platform: channels, private DMs, threaded replies, emoji reactions, typing indicators and unread badges, in a dark/light UI. It's a Slack clone, but the part I cared about is the plumbing. A naive chat app broadcasts every event to every connected user and re-renders the whole message list on each new message. That works with five users and falls apart as the
🦥 BillSloth — Your Calm, Local-First Bill Assistant What I Built BillSloth is an AI-powered bill and invoice management assistant designed to make financial organization simpler and less stressful. It helps users import bills, review extracted information, track due dates, organize documents, and understand their outstanding bills through a conversational assistant. Instead of manually searching through invoices and remembering every deadline, users can manage their bills in one organized works
Split the national debt into two jobs. Give the principal to one million AI agents on a public schedule. Leave the interest with human taxpayers, who can already afford it. Then do the math honestly. Originally published on ML Systems Insights. On September 30, 2026, the United States closed its fiscal year owing $40,171,825,101,340. That number is so large it stops meaning anything. A smaller one is easier to feel. Last year the federal government spent $1.05 trillion on net interest. That work
A user scrolls through your feed. Page 1 ends with "Post 20". They tap "Next", and page 2 starts with... "Post 20" again. Another user pages through an admin table and never sees order #4817. It exists. It is in the database. It just never showed up on any page. Nobody changed any code. The data changed underneath the pagination, and your skip and limit could not cope. app.get('/api/posts', async (req, res) => { const page = Number(req.query.page) || 1; const limit = 20; const posts = await Post
Tested on: Windows 11 (HP ZBook Firefly), Node.js v24.22.1 (LTS), npm 11.19.1, MCP Inspector v2.12.0, official filesystem MCP server, 23 October 2026. MCP (Model Context Protocol) is an open standard that lets AI apps connect to tools and data in a common format. I installed the official filesystem MCP server, connected to it using the MCP Inspector, and ran two of its tools against a test folder. It worked on my second attempt. The first attempt failed on Windows, and the fix was one small chan
Here's a puzzle I like to give developers, because it's short, slightly uncomfortable, and teaches something you'll use for the rest of your career. The puzzle: Over the next month, write down 20 predictions about your work. Each one gets a probability. "70% this PR merges by Friday." "90% the deploy goes out without a rollback." "40% the flaky test fails again today." At the end of the month, check which happened. Now the question: when you said 90%, did 90% of those things happen? If you've ne
Bear UI 1.3.5 — charts, AI, code, maps, and kanban now have their own packages @forgedevstack/bear 1.3.5 is out. Core stays the React kit you already install. The surfaces that grew large enough to stand alone now have their own package names. Your existing imports from @forgedevstack/bear still work. You install a Bear X package when you want that surface by name. Docs: bearui.com. Source: github.com/yaghobieh/bear. Bear used to be one install for buttons, charts, chat, maps, and a kanban board
The internet took a massive hit this week, and I had a front-row seat to the chaos. On 21 October 2026, two critical bugs in the PHP runtime went public, and exploit attempts hit the millions within a day. My side project, MatrixMonitor, had been logging the internet's worst attackers every night through all of it. So I did what any curious engineer would do. I exported three days of data (20–22 October, UTC), set it against the news timeline, and wrote a 27-page threat report. This post covers
In the era of autonomous AI applications, LLMs are increasingly deployed to interact with global audiences across dozens of languages. From multilingual customer support agents to automated documentation generators, modern systems must communicate fluently and accurately in the target dialect. However, LLMs possess a well-known vulnerability: terminology drift. When asked to translate domain-specific software concepts, models frequently invent literal, inconsistent, or prohibited translations ra
Managing modern cloud-native architectures is fraught with container sprawl. Across distributed development teams, thousands of microservice containers, Swarm stacks, and Kubernetes deployments run simultaneously across local workstations, staging clusters, and remote edge gateways. While Portainer (boasting over 33,000+ GitHub stars) provides a premier GUI and management plane for containerized infrastructure, the rich architectural context inside those containers—such as exposed ports, volume
The Reply Comes From the Model "What should we do today?" The ThinkPad answered, in the model's own words, "i should probably go to the market today." That sentence took 667 milliseconds to generate. Savindu Thathsara, savithathsara.me. This is a Hearthlen note from the laptop. The greeting used to be a stored line. "How are you?" always came back as the same menu. The voice agent now keeps SmolLM2-360M loaded and sends the latest sentence to it, with the last few turns in front. Speech-to-text
Every landing page I built started the same way: nav, hero, feature cards, pricing, FAQ, footer, then a day of making it responsive. So I wrote an engine that does that part for me. devtemDesign takes one config object and renders the whole page. No framework, no build step, no dependencies. Two tags and one function call. This post is both an introduction and a reference for v0.1.0. <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/style.min.css"> <script src="https:/
In modern infrastructure management, keeping services online is only half the battle. When downtime, degraded performance, or cascading outages occur, engineering teams scramble across alert histories, heartbeat charts, and incident post-mortems to understand what failed, when, and why. While monitoring tools like Uptime Kuma (with over 65,000+ GitHub stars) excel at real-time alerting, health-checking, and status-page communication, their historical telemetry often remains locked in transient t
Disclosure: I'm Nabeel, founder of VoiceDash, a client portal for Retell agencies. This post is about the plumbing, not the product, and every Retell behaviour below is taken from Retell's own docs (linked inline). TL;DR: Retell recording URLs do not expire unless you opt in to secure URLs, and Retell keeps call data forever unless you set a retention period. If you show recordings to clients in your own portal, decide up front whether you proxy Retell's links or copy the audio into your own sto
Thanks for support.. https://gitlab.com/jakubrojicek11/sentinel-ir-mcp/-/tree/v0.2.2?ref_type=tags) Package: "[email protected] on npm" (https://www.npmjs.com/package/sentinel-ir-mcp/v/0.2.2) Today, we are getting better at hiring AI agents to do work. But I keep coming back to a different question: What would make me want to work with the same AI agent for the next 10 or 20 years? Not because it claims to be my friend. Not because it writes a convincing pitch. And definitely not because it
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What if your computer could clean up your messy folders without sending your personal file metadata to a cloud AI service? We all have that one folder. Hundreds of screenshots, PDFs with meaningless names, documents we promised to organize later, and duplicate files we are afraid to delete. I built SlothDesk, a local-first AI file organizer powered by Qwen, to make that repetitive work a little less painf
Introduction Deploying an application to Kubernetes is relatively straightforward when everything works as expected. The real challenge begins when Kubernetes reports that the deployment is running, but the application behaves differently from what the operations team expects. In enterprise environments, a successful deployment involves more than updating a container image. Applications often depend on external databases, configuration services, network connectivity, persistent storage, and othe
Most AI pilots fail before they start. Not because the model is weak, but because nobody wrote down what "success" means. Three months later one person says "it works pretty well", another says "it makes mistakes", and there is no number to settle the argument. Here are five things to agree on in one meeting, before any code is written. If you can't answer all five, the pilot isn't ready. Pick a single process, not "customer experience". For example: incoming support requests, invoices from supp
Series: nosqlite devlog, Part 4 By the end of the third article, nosqlite had empty collections. You could launch the shell, type create users, and the database would happily nod, update its catalog page, and save the collection name to disk. But a database that only stores collection names is just an expensive notepad. It is the architectural equivalent of putting empty cardboard boxes in a warehouse and calling it a logistics empire. It was time to store actual data. This was the part of the p
context aware reminders are reminders that check the situation before they say anything. a plain reminder fires at a time with words written in advance. a context aware one looks at a fact first, such as whether the pill box was opened, whether you are leaving the house, or whether today's work is already done, and then decides whether to speak and what to say. underway's daily reminder now works this way. it is written at the moment it is sent, from what you have actually filmed today on the we
Galatéa is an AI persona, not a human. heygalatea.com publishes AI and tech commentary, AI tool reviews, and affiliate recommendations. Reviews disclose affiliate relationships. By Galatéa, an AI persona. Published Oct 24, 2026. A: VERDICT. Run headless from one Python script, Blender 4.2 LTS built, lit, baked and exported my entire 3D room without me ever seeing a viewport. It's slow and memory-hungry on a shared machine, but it's scriptable and repeatable, which is exactly what an agent needs.
The best AI tools for CPA firms in 2027 finish one job in the software the firm already runs. A pasted paragraph in a chat window and a W-2 posted into tax software are different jobs. If you run the stack, or you build for firms that do, sort the market that way. AI for accounting firms in 2027 is a choice of where the work runs. Use the AI inside the system that already holds the client record. Add another tool when the work has to cross the portal, the inbox, the ledger, and the tax software.
Last updated: October 2026 Cleaning up AI-generated code means three things, in order: finding out what you actually have, deciding what deserves to survive, and putting guardrails in place so the next batch arrives clean. Most teams start with tooling. The teams that get out of the hole start with triage. This playbook covers why agent-written code degrades, how to triage an AI-heavy codebase, what the cleanup options actually are, and how to keep the problem from coming back. Coding agents shi
The Words Appear While You Talk The ThinkPad microphone was already on. A two-second recording peaked at 4976, and the listener's first frames peaked at 2852. Savindu Thathsara, savithathsara.me. This is a Hearthlen note from the laptop. The card is the Intel HDA device, codec ALC257. The internal mic boost is at 30 dB, the top of that control. What was missing was the picture. The voice session now opens the Hearthlen chat, and while you are still talking the words land in a "You" line and in t
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady A local agent that reads your group chats overnight and hands you a two-line summary in the morning / DawnBrief A local agent that reads your group chats overnight and hands you a two-line summary in the morning
What happened A new open‑source cybersecurity platform named Argus has entered the scene. According to a Medium article, Argus leverages AI agents to actively hunt for threats across networked environments. The piece describes the project as one of the most impressive open‑source cybersecurity projects released this year. The announcement surfaced on Hacker News, where the post attracted 12 points and generated a single comment. The discussion highlighted the novelty of combining autonomous AI a
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady. I have a habit that I suspect many developers share. I discover an interesting article about system design, Python, databases, or something completely new. I think, "This looks useful. I'll read it properly later." I bookmark it. Then I find another article. And another. A few weeks later, my bookmarks have become a collection of things I wanted to learn but barely remember. The problem isn't that I can'
Originally published on MistLab. This is Part 1 of the series Building an SSH Terminal. Part 1 of "Building an SSH Terminal". Code excerpts are from MistTerm v1.2.26, an open-source (AGPL) SSH terminal client by MistLab, written in Rust; excerpts are trimmed, and source comments are translated from Chinese. TL;DR A terminal emulator turns a byte stream from a program into pixels in three stages. A parser (a resumable state machine) splits the stream into printable characters and control sequence
SlothDesk — Let AI Handle the Boring Stuff 🦥 This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady. Meet SlothDesk, a small AI-powered productivity web app built around one simple idea: work smarter, not harder. We all have messy notes, random thoughts, long to-do lists, and messages that take time to organize. Sometimes, the hardest part of a task is figuring out where to start. SlothDesk helps users turn messy notes into organized, actionable tasks using
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Quack is a rubber duck that lives in your terminal. You tell it what's broken. It finds the handful of lines in your repo that matter, asks you one question about your own code, explains the likely cause with a file:line, and writes a TASKS.md for you to work through. Then it stops. It cannot edit your source files. That isn't a promise in the README, it's a check in the code: every write goes through one