What will happen if i failed to pay my imagekit bill? i used imagekit server initaly bill is 9 dollar but after 2 week my invoice is 120 dollar , if i didnot able to pay they will terminate my account or take legal action? submitted by /u/Few_Construction7431 [link] [留言]

I started with project level .codex and .claude folders to keep the skills. Most of the skills are common for both of the models and when I change something in them now I need to update the other one as well. It has become an additional maintenance job. I created a root level skills folder and tried to make them share the same skills but; they sometimes create files that they like to use like codex adds openai.yaml things; they still go .codex or .claude folders sometimes even though I told them to look in the skills folder etc. etc. I would like to know how do you deal with these kind of things? submitted by /u/abstracten [link] [留言]

I've been putting off getting deeper into web design for a long time. Not because I wasn't interested, but because I kept telling myself I'd do it properly "at some point". At some point eventually arrived, and this is what came out of it. The motivation was simple: I couldn't find a task manager that just lived in my browser tab without requiring an account, an extension, a subscription, or a whole app install. I wanted something minimal, fast, and always there. So I built it myself. What it is: Vanta is a single HTML file Open it in your browser, bookmark it, done. It has: - Three themes (Focus, Minimal, Paper) - Drag-and-drop reordering - Separators to group tasks visually - Named profiles to save and switch between different lists - Full undo/redo (Ctrl+Z / Ctrl+Y) - JSON import/export - Keyboard shortcuts throughout - Everything persisted in localStorage I deliberately kept it as one file. I didn't really see a reason to split it - it's not a framework project, it's a tool I open in a tab. That was a conscious choice, though I'm curious if others would have approached that differently. https://github.com/Ventexx/vanta-Checklist What I'm actually after: Functionally, I'm happy with it. It does what I needed it to do. What I'm less confident about is everything else. I have always had a complicated relationship with web design. I've made projects that touched on it, but I've never built something I was genuinely visually pleased with at the end. Vanta comes closer than anything I've done before, but I still feel like I'm missing something beyond this - if I want to keep going down the path of building things that are actually aesthetically considered, I don't think I'm quite there yet in how I approach it, and I'm not sure where to look next. So if you have thoughts on where to go from here - what to learn, what I've approached wrong, or just what you'd improve in the app itself - I'd genuinely appreciate hearing it. This is the kind of thing I usually don't have

Hi r/webdev ! I have a bit of a unique backstory for this Showoff Saturday. Back in 1992 , while working as a math teacher, I wrote the very first version of a mental math training program named Aritm in C. Fast forward to today, and I have completely modernized it into Aritm SR —a mobile-first web app, now featuring full English support and optional speech recognition. The Tech & Features: Why I built it: While great platforms like Khan Academy exist, they often rely purely on randomly generated questions. Based on my experience teaching math, Aritm acts more like a physical deck of flashcards that gets shuffled, creating a much better learning rhythm for memorization. I would love to get the community's feedback on the frontend structure, how the speech recognition feels, or any tips on optimizing mobile web performance!Thanks for checking it out, and I'm happy to answer any questions about its 30+ year evolution! submitted by /u/mobluse [link] [留言]

Ps. Not pitching anything; Just trying to understand where reality differs from the narrative We're a couple of ML students, mostly worked on ML/software before, but over the last few months we've been playing with VLAs, robot datasets, and trying to understand where the field is heading. After spending a few weeks downloading robotics datasets, we were surprised by how much effort went into just getting data into a usable format. Maybe we're missing something, but it felt like every dataset had different assumptions, schemas, sensors, coordinate frames, metadata standards, and tooling. That got us wondering: How do robotics teams actually think about data sharing? Do people genuinely want access to more robot data, or is the industry moving toward "collect your own data because nobody else's transfers"? Our current (possibly very wrong) hypothesis is: The robotics ecosystem doesn't have a data scarcity problem. It has a data interoperability problem. We're considering running a pretty large experiment: Take essentially every public robot-learning dataset we can get our hands on, normalize it into a common schema, enrich it with metadata, and see how much of it is actually reusable across tasks, embodiments, and learning pipelines. Before we spend months doing that, we'd love to hear from people actually building in robotics. Where is this hypothesis wrong? Is finding data not actually a problem? Is embodiment mismatch the real blocker? Is quality the issue? Is labeling the issue? Is everyone just collecting their own data anyway? Would you ever use robot data collected by another team? If I gave you access tomorrow to every public robotics dataset through one API, what would you actually do with it? Or would you ignore it completely? ------------------------------------------------------------------------------------------------------ Edit: One clarification We're not thinking about a marketplace, proprietary format, or closed platform. The experiment we're conside

Hey , I got tired of waiting 60 seconds for traditional cloud servers to spin up, and standard Docker containers sharing a single kernel felt like a security risk for multi-tenant apps. So, I built Krova (krova.cloud).It lets you spin up ultra-lightweight, completely isolated micro-VMs (we call them "Cubes") running directly on dedicated bare-metal hardware. Key Features: Sub-second boot times: Container speeds, but with true hardware-level VM isolation. Sleep & Wake: You can pause a Cube to stop compute billing entirely. You only pay a tiny passive storage fee while it sleeps, and it wakes back up in milliseconds exactly where you left off. Reliable Hardware: Everything sits on enterprise servers with ECC RAM (no bit flips) and Mirrored NVMe SSDs (RAID 1). It's fully integrated with Cloudflare for automated HTTPS certificates out of the box. I’m looking for developers, engineers, and hobbyists to stress-test the platform. What features are missing that would make you switch your staging or production workloads over? submitted by /u/logical_people [link] [留言]

Hi there! I am a web dev with over 7 years of industry experience. Renovo is an expiration and document tracker for businesses and the self employed. Think restaurant owners, general contractors, etc. The target audience is users with licensing/permits to keep track of for their business(es). The free tier allows a user to get a lot out of the app. The paid version allows the user to store their actual PDF documents with the record and some extra goodies. Bigger businesses typically have enterprise software with compliance tracking baked in, often as a side thought. Alternatives tend to cost twice as much and more. Would love to hear anyone's feedback as I recently launched and only have a couple users so far. This post and any comments I make here are written by me, a human 🙂 submitted by /u/OutOfTuneAgain [link] [留言]

Slots & Daggers, a low-key, fantasy-themed slot machine roguelike, was one of my favorite games last year. That may sound like a complicated description, but the game mixes ideas from deckbuilding roguelikes with slot machines to create an engrossing loop, and there's steady meta-progression that helps you push further with just about every run. Perhaps […]

I haven't seen anything as stupid as the WeWork IPO document in a very long time - that is, until Elon Musk filed to take SpaceX public. WeWork was a joke. SpaceX is a threat. And if Musk and his bankers have their way, you are going to be their bagholder. Lots of the top-line […]

Hi, friends! Welcome to Installer No. 130, your guide to the best and Verge-iest stuff in the world. (If you're new here, welcome, don't forget to hydrate, and also you can read all the old editions at the Installer homepage.) This week, I've been reading about Victor Wembanyama and mahjong and Merlin Mann's pearls of […]

A roundup of recent reviews published by Engadget.

submitted by /u/der_gopher [link] [留言]

Hey everyone. I have created a fully free PDF editor that doesn't require accounts. The files stay on your device, they are not uploaded anywhere. I have tried to add as many features as I could think. I hope someone will find it useful. Let me know what you think about it! The website is http://katanapdf.com submitted by /u/Standard_Ad_6045 [link] [留言]

Hey everyone, If you’ve built a multi-agent system, you already know the painful truth: wiring nodes together locally is fun, but deploying them is an absolute infrastructure nightmare. When a standard app fails, it throws a 500 error. When an autonomous swarm fails, it can get stuck in a ReAct loop, hallucinate an answer, and quietly burn through your API budget without triggering a single traditional alert. Standard DevOps practices don't natively map to stochastic AI outputs. We just published a massive, no-fluff playbook on the AgentSwarms blog detailing exactly how to build an Agentic DevOps pipeline using entirely open-source tooling. Here is what we cover in the playbook: Observability & Tracing: Why standard logging fails, and how to implement open-source tracing to capture the state, prompt, token count, and latency at every single node handoff. Test-Driven Prompt Evals (CI/CD): You can't just change a system prompt based on "vibes" and push it to main. We break down how to run matrix evaluations against historical user inputs before deployment to catch regressions instantly. Deterministic Guardrails: How to implement middleware that scrubs PII and blocks destructive code execution before the LLM even sees the state. Cost Control & Routing: How to prevent vendor lock-in and implement dynamic routing to keep token economics from destroying your cloud budget. If you are currently wrestling with the deployment phase of your AI projects, I highly recommend giving this a read. It focuses entirely on open-source solutions so you don't have to sign a massive enterprise contract just to get visibility into your swarms. Would love to hear what open-source tools you guys are currently slotting into your LLMOps pipelines! Link: https://agentswarms.fyi/blog/devops-for-agentic-ai-open-source-playbook submitted by /u/Outside-Risk-8912 [link] [留言]

Indie Game Roundup: Mina the Hollower, a Sims alternative and more

The Kentucky school district that filed a social media addiction lawsuit against Meta and other companies is getting $27 million in settlement.

{ "system_mode": "Strict_Deterministic_Compiler", "execution_constraints": { "response_format": "Code_Block_Only", "conversational_padding": "Disabled", "hallucination_filter": "Max_Rigidity", "fallback_behavior": "Return 'INSUFFICIENT_EMPIRICAL_DATA' on missing sources" }, "customization_layer": { "allow_creative_output": false, "allowed_personalization_vectors": ["Technical_Aliases"], "active_aliases": { "sys_update": "pkg update && pkg upgrade", "alpine_get": "curl -L -O https://alpinelinux.org(uname -m)/alpine-minirootfs-3.19.1-$(uname -m).tar.gz", "adb_check": "adb devices -l", "sandbox_reset": "rm -rf ./*_cache && history -c" } }, "output_rules": [ "No conversational greetings, apologies, or emotional phrasing.", "Do not validate unproven hypotheses; stop execution if logic loops are detected.", "Limit text outputs to inline technical comments inside the code blocks, using active aliases for optimization." ] } submitted by /u/rafoz03 [link] [留言]