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A SaaS team adds “Pay with crypto” to checkout. The first test looks fine: create a wallet address, show a QR code, receive USDT, mark the order as paid. Then production starts. One customer sends the right amount on the wrong network. Another pays after the invoice expires. A third sends 99.80 USDT instead of 100 USDT. Support sees a transaction hash but cannot find the order. Finance sees funds received but cannot match them to an invoice. The backend receives the same webhook twice and unlocks the product twice. That is the moment crypto payment integration stops being a QR-code feature and becomes a payment infrastructure problem. This is the first Dev.to post from Cryptoway . We build crypto payment infrastructure for online businesses, and here we will share practical notes about crypto payment API design, invoices, payment webhooks, stablecoin payments, checkout flows, reconciliation and payment status handling. What is a crypto payment gateway? A crypto payment gateway is the layer between a business event and a blockchain transaction. The business event can be: a SaaS subscription invoice; an e-commerce order; a digital product purchase; a marketplace deposit; a service payment link; an internal billing event. The blockchain transaction is the customer sending BTC, ETH, USDT, USDC or another supported digital asset. The gateway connects the two. It creates a payment request, shows the customer what to pay, monitors the blockchain, updates the payment status and notifies your backend when something changes. In other words: a crypto payment gateway is not the blockchain itself. It is the operational layer that makes blockchain-based payments usable inside real products. Crypto Payment Gateway vs Wallet Address A wallet address is enough for a manual payment. It is not enough for a product that needs order tracking, support visibility and finance reconciliation. Area Wallet address only Crypto payment gateway Order matching Manual matching by amount, address o

PixToCode is a new Figma plugin that turns the frames you've already designed into production-ready code with AI — React, Angular, Vue, or HTML, all Tailwind-first. Just published on the Figma Community: figma.com/community/plugin/1641790551381890223/pixtocode What it does Select one or more frames in Figma, pick a framework, click Generate. About 10 seconds later you have clean code that uses the exact colors, spacing, typography, and layout from your file — not generic Tailwind utility soup. Highlights: 4 frameworks — React (TypeScript), Angular (standalone + Signals), Vue 3, or semantic HTML5. All Tailwind-first. UI library presets — shadcn/ui, Material UI, Chakra, Ant Design on React, Angular Material on Angular. Output uses the real components , not generic divs. Refine with plain English — type "make the button rounded" or "use green for the active tab" and the AI rewrites the component in place. Multi-frame batch — select up to 5 frames, get them all in one pass. Variants → typed props — a Figma Component Set with Primary / Secondary / Disabled becomes one typed prop-driven component, not three duplicate files. Live browser preview — see the generated component rendered in a sandboxed tab before pasting it into your project. Cloud history — every generation saved to your account, synced across devices. How it works Get a free license key at pixtocode.com (5 free generations, no credit card). Install the plugin from the Figma Community. Paste the key into the plugin's license field. Select a frame, choose a framework, click Generate. Copy the code straight into your project. That's the whole flow. Pricing Free — 5 generations on signup Pro — $20/month for 100 generations Power — $39/month for 250 generations Team — $99/month, 5 seats, 600 shared generations (scales to 10 seats) All paid plans have a 7-day refund guarantee. Tips for best results Frames with auto-layout , named layers , and consistent design tokens produce the cleanest output. For huge dashboard

Hi all, I have a Windows Server 2026 box running IIS and am attempting setup a GitHub CI/CD pipeline. I am using a self hosted runner and that runner has been setup with minimum privileges to do it's thing. I have the following setup: - IIS points at a junction, - junction points at the build folder. -Project/ -live/ -> junction points at the live release -releases/ -v1/ -v2/ <- pointed at by live junction All is well in my workflow until a try to delete my old junction and recreate my new junction, pointing at the newly built version. It fails, I think because a IIS process still has a hold on the content of /live. Because the user account running the GitHub action runner is low privilege, it cannot stop IIS. I tried creating a scheduled task running as SYSTEM and manually triggering the task, but my low privilege user can't do that either. How have others overcome this? Any help greatly appreciated. I'm in a corporate environment so can't be lazy and give the action runner admin privileges. This has consumed my day. submitted by /u/Wotsits1984 [link] [留言]

As it happens every now and then, I've received another email from noreply at youtube.com asking me to fill in a form to audit my use cases of the YouTube API. I only have one project in the Google API Console, and the sole use case is to connect it to a Telegram bot I own that returns a query made by any user with access to the platform. However, in the email I received this time, they tell me that I manage shittons of projects with ID numbers that I am unaware of, and none of them correspond to the project ID that I actually manage. In fact, among the projects they claim I manage, there is one called "I do not remember" and other very strange names that I’ve never even heard of. The email is official and the form links to the same one they usually send me to fill in every few years. Anyone did receive recently some similar e-mail? Should I pay attention to this email, or have they completely lost the plot? submitted by /u/Felfa [link] [留言]

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

Many of you share great projects, but without a real use case. I want to encourage you that even in 2026 you can still achieve big things. You just need to find a niche and be fast. This website reached these values completely without advertising. Bewertiq.org It takes reviews and uses a mathematical regression model (OLS – Ordinary Least Squares) to estimate or refine ratings more accurately. By applying things like log-transformed features and category-based dummy variables , it tries to reduce noise and bias in raw user ratings and produce more stable, comparable results across different entities. On top of that analytical layer, the product positioning is: A trust-focused alternative to platforms like Kununu, Trustpilot, or Google Reviews Emphasizing no paid partnerships, no sponsored rankings, and no review manipulation or removal pressure Built around the idea of independent evaluation of companies using data instead of commercial influence submitted by /u/princessinsomnia [link] [留言]

Hey folks, just thought I'd share this here. I got an email recently(first one was automatically marked as spam) from Clera employee asking about "position at a certain company" and whether I'm interested. After 1-2 back and forth I realized that the emails are mainly AI-generated, but nevertheless gave it a chance and shared my CV, inviting for a live talk. After which I got an email from " talent@getclera.com " like this(picrelated). I never gave any consent to be signed up for a talent agent, never gave consent to store my CV or share it with an AI model. The reason I shared my CV was because email contained this phrasing: Here's what I'd suggest: if you can share your CV, the team will review it and take it from there. So, it was intended to be forwarded to the team in a mentioned company, not to store it in a talent pool for an AI agent. So, just reminding to check out the reviews online for email domains when you get invites to share CVs. Don't be like me. And for anyone else who experienced this: I'm not familiar with legal side of this, but if you wanna gather and do something about it, I might join (depending on whether I can since I'm not from US). P.S. This was raised once on r/theprimegen (found through search) but it didn't get much resonance. submitted by /u/Strict-Criticism7677 [link] [留言]

--- title : " Introducing rails-tenantify: Row-Level Multi-Tenancy for Rails 7+" published : true description : " A modern, safe, and robust row-level multi-tenancy gem for Ruby on Rails. Prevent data leaks, protect bulk writes, and preserve tenant context in background jobs." tags : rails, ruby, opensource, saas --- ## The Problem Every multi-tenant SaaS app eventually needs to answer the same questions: * How do we make sure School A never sees School B's data? * How do we scope every query to the right organization? * How do we keep tenant context alive in background jobs and Sidekiq retries? * How do we stop a careless `update_all` from wiping another tenant's rows? The typical answer is *"use acts_as_tenant"* or *"switch to Apartment."* But in modern Rails development, that often means: * Fighting unmaintained APIs on Rails 7+ * Losing tenant context when a background job retries * Dealing with schema-per-tenant complexity (Apartment) and heavy DevOps overhead * Rolling your own `default_scope` and crossing your fingers that nobody calls `unscoped` For most Rails apps, you just need **row-level tenancy** : one database, one `organization_id` column, and strict scoping. The pattern is simple. Getting it **safe** in production is not. --- ## What I Built **`rails-tenantify`** is a Ruby gem that adds row-level multi-tenancy directly to your Rails models and controllers. No external services, no extra databases per tenant—just your own PostgreSQL (or SQLite in dev). ruby class Project < ApplicationRecord include Tenantify::Scoped belongs_to_tenant :organization end ### Set the tenant once per request ruby class ApplicationController < ActionController::Base set_tenant_by :subdomain # acme.yourapp.com → Organization end ### Everything scopes automatically ruby Tenantify.current_tenant = current_organization Project.all # Only this org's projects Project.create!(name: "Q2 Roadmap") # organization_id is set automatically ### Switch context safely for admins or scripts

I made a website for my company and it was deployed on hostinger using wordpress a little over a month ago. About a week ago something went wrong and it started having so many problems. When I google the company name, and click on company's website it redirects me to some shopping website If I open the URL manually, it just opens a blank webpage, the source is also empty All the files are their in hostinger and all pages and details are visible in wordpress Somehow Google crawled over 800 URLs while my website only has about 25 pages and now when i google "site:companyname.com" all those weird URLs with Japanese name come up I tried fixing the site with hostinger AI, I myself looked a files and database for any mallicious activity, but I can up with nothing. Things work fine in localhost, and I tried creating a staging site with everything same at a subdomain that works fine too. If any one can help it would be great, I don't wanna loose this internship. I have not revealed the company name for my safety. submitted by /u/maybeamit [link] [留言]

I'm interested in building a new website for my business and am debating on whether or not I should hire a professional or design one by myself using AI. I've seen a lot of pretty nice sites built with AI tools like Claude, but I'm skeptical as to whether or not they are built appropriately. If anyone has opinions about the pros/cons of using an AI tool vs hiring someone I would appreciate hearing them. Thanks in advance! submitted by /u/HawgBandit [link] [留言]

When I decided to ship this blog in four languages, I had a clear mental ranking. English would win on volume. Spanish would be runner-up because of the sheer speaker count. Japanese would stay steady because it's my native language. Portuguese, I figured, was the long tail. I added it mostly out of completism. Twenty-two days later, the GA4 snapshot disagrees with every part of that ranking. PT: 748 pageviews , 709 sessions EN: 195 pageviews , 176 sessions JA: 27 pageviews , 29 sessions ES: 7 pageviews , 7 sessions That is Portuguese pulling roughly 3.8× English, 28× Japanese, and 107× Spanish on the same blog, same publishing cadence, same author. One Portuguese article on its own (a post about a 24-hour security agent: 375 PV) got more pageviews than my entire English blog combined. I wrote that article hoping Spanish would surprise me. Instead Portuguese surprised me, and Spanish quietly continued to not exist. The setup, so you can discount my numbers properly This is not a clean comparative experiment. It's a single blog, kenimoto.dev , running four language directories ( /en/ , /ja/ , /pt/ , /es/ ). Articles get translated through a cross-language LLM pipeline, then hand-edited for register and locale (BR Portuguese vs PT Portuguese, LatAm-neutral Spanish vs Spain Spanish). The window: 2026-04-30 to 2026-05-21, 22 daily snapshots. EN has 26 articles. JA has 25. PT has 17. ES has 10. So PT has fewer articles than EN and still beats it almost 4 to 1. If you stop reading here, take this one thing: language asymmetry can swallow article-count asymmetry whole . Adding articles in a saturated language is slower than adding articles in an underserved one. Why Portuguese pulled ahead I don't think the answer is "Portuguese readers like me more." I think three asymmetries are stacking on top of each other. 1. TabNews is a community door English doesn't have TabNews is a Brazilian developer community where you can post a technical article and have it actually read by h

Take Aways Performance and Scalability : Pinecone is a managed machine-learning database that provides exceptional levels of performance and scaling capability due to its cloud-based design. Because of its distributed architecture and ability to do near-neighbor searches, Pinecone handles such tasks as similarity searching and anomaly detection on very large datasets efficiently. Easy to Integrate : One of the standout benefits of Pinecone is how easily it integrates through a high-level API and SDKs across several programming languages. This gives developers a real productivity boost by making vector storage, indexing and querying for machine learning applications far less complicated to implement. Strategic Factors : Pinecone brings advanced features and managed services that genuinely enhance machine learning workflows, though it does come with considerations like recurring costs and vendor lock-in. Organizations should think carefully about these factors alongside the benefits of streamlined database management and optimized performance before committing to adoption. The importance of storing and accessing information properly to build the best possible machine learning model really cannot be overstated. Pinecone addresses this directly by offering a Vector Database built specifically for ML queries, creating a strong opportunity to tap into the power of cloud databases. Designed from the ground up as a cloud-native application, Pinecone makes it straightforward to index and search complex, high-dimensional vector data — which in turn makes building state-of-the-art machine learning applications much more approachable and helps software development companies deliver more value to their clients through custom software development. What is Pinecone? Pinecone is a fully managed Vector Database that lets you store, index, and query complex vector data quickly and efficiently. Because of its vector-native design, the primary use cases for Pinecone fall within similar

Due to a growing influx of questions on this topic, it has been decided to commit a monthly thread dedicated to this topic to reduce the number of repeat posts on this topic. These types of posts will no longer be allowed in the main thread. Many of these questions are also addressed in the sub FAQ or may have been asked in previous monthly career threads . Subs dedicated to these types of questions include r/cscareerquestions for general and opened ended career questions and r/learnprogramming for early learning questions. A general recommendation of topics to learn to become industry ready include: HTML/CSS/JS Bootcamp Version control Automation Front End Frameworks (React/Vue/Etc) APIs and CRUD Testing (Unit and Integration) Common Design Patterns You will also need a portfolio of work with 4-5 personal projects you built, and a resume/CV to apply for work. Plan for 6-12 months of self study and project production for your portfolio before applying for work. submitted by /u/AutoModerator [link] [留言]

Hi everyone, We're building an automation platform using Playwright where all browser automation runs on the backend. For portals that require manual intervention (OTP, CAPTCHA, MFA, document uploads, etc.), we're exploring a way to let users temporarily view and interact with the running backend browser from our React application, after which automation would resume automatically. Our goals are: Keep all automation logic on the backend Support human intervention only when necessary Scale to bulk processing workflows Deploy reliably in production We're currently evaluating approaches such as CDP screencasting, VNC/noVNC, and WebRTC-based browser streaming. Has anyone built something similar in production? What architecture did you choose, and what were the biggest challenges around scalability, latency, security, session management, and CAPTCHA/OTP workflows? Also, is there a better alternative than live browser streaming for this use case? Any advice, experiences, or open-source projects would be greatly appreciated. submitted by /u/Loud_Ice4487 [link] [留言]

Hello Dev Community! 👋 It is officially Day 8 of my journey to master the MERN stack! After spending the first week structuring with HTML and styling with CSS, today I finally started learning the core language of web logic: JavaScript . Moving from static designs to actual programming logic feels like unlocking a whole new level of web development. 🧠 Key Learnings From Day 8 Today was all about setting up the foundation in JavaScript and understanding how code runs in the browser. Here is what I covered: 1. The Browser Console & Execution I learned that every browser has a built-in environment to run JavaScript. Writing my very first console.log("Hello World"); and seeing it print in the developer tools console was the perfect start. 2. Variables: Storing Data Safely I learned how to store information using variables and the crucial differences between modern variable declarations: let : For values that can change later in the program (mutable). const : For values that must remain constant and cannot be reassigned (immutable). Note: I also read about var , but learned why modern JavaScript avoids it due to scoping issues. 3. Data Types Fundamentals Data needs a type so the computer knows how to handle it. Today I practiced with: Strings: Plain text enclosed in quotes (e.g., "MERN Stack" ). Numbers: Integers and decimals without quotes (e.g., 2026 ). Booleans: Simple true or false states (e.g., isLearning = true ). 🛠️ What I Actually Code / Experimented With Since I am just starting with core logic, I didn't write code directly into my HTML webpage layout today. Instead, I created a script.js file, linked it to my project, and built a basic script in the console that: Stores a user's name and learning status in variables. Dynamically calculates values (like years left until a milestone). Outputs formatted statements into the browser console. It is simple, but understanding how data moves in the background is incredibly exciting. 🎯 My Goal for Tomorrow (Day 9) Tomorr

Not every old business web app needs a full Internet Explorer environment. That sounds obvious, but it is easy to miss when a legacy intranet, ERP, OA, or ASP.NET WebForms page fails in Chrome or Microsoft Edge. The first instinct is often to put the whole system into IE mode. Sometimes that is absolutely correct. Other times, the page mostly works in Chromium and only breaks on older JavaScript or DOM assumptions. The useful first step is to separate those two cases. Case 1: the page needs a real IE engine Use Microsoft Edge IE mode, a Windows virtual machine, remote desktop, or another managed legacy-browser path if the page depends on: ActiveX controls COM integration VBScript Trident or MSHTML rendering behavior Browser Helper Objects Java applets strict IE7 or IE8 document modes A Chrome extension or JavaScript compatibility layer should not be presented as a replacement for those requirements. If the workflow depends on the IE engine, the browser engine is part of the application runtime. Case 2: the page mostly works, but old browser assumptions fail There is another common category. The page loads in Chrome or Edge, authentication works, and the main UI appears, but a small set of old behaviors fails. Examples include: empty frameset entry pages loading pages that do not finish redirecting attachEvent window.event event.srcElement showModalDialog -style picker flows document.frames older WebForms date fields that call a calendar function on focus For maintained source code, the best answer is still to fix the application. Replace old event APIs, remove synchronous dialog assumptions, and modernize generated WebForms scripts where possible. But in many real organizations, the legacy page is owned by a vendor, frozen department system, or migration backlog. In that situation, a scoped compatibility layer can be worth testing before moving the whole workflow into IE mode. A low-risk triage sequence I use this sequence: Pick one legacy hostname. Pick one failing

Hey everyone 👋 I'm exploring ideas for an AI-powered developer tool, but before building anything, I want to understand the real problems developers face every day. There are already plenty of tools that generate code. What I'm interested in is everything around coding: Debugging Code reviews Technical debt Documentation Dependency upgrades Testing Deployment Architecture decisions Learning large codebases I'd love to hear from you: A few questions: What's the most frustrating part of your workflow? What task takes more time than it should? What's something you wish AI could do for you today? Have current AI tools (ChatGPT, Claude, Cursor, Copilot, Gemini, etc.) failed you in any important way? If you could eliminate one developer headache forever, what would it be? I've also created a short 2-minute survey: 🔗 https://docs.google.com/forms/d/e/1FAIpQLSf1M5d2y-0RXEIhrbDBtS5gC900YuzWl43cJCxGUrU38MyeDQ/viewform?usp=publish-editor I'll happily share the survey results and key findings with the community once I collect enough responses. Thanks in advance for any feedback!

Integrations kill product velocity. Every SaaS team knows this. You ship a killer feature, customers love it, then they ask: "Can it sync with Salesforce? What about HubSpot? Zendesk?" Suddenly your roadmap is hostage to building connector after connector. Each one takes 2-3 weeks. Your engineers hate it. Your customers wait. Competitors who solve this faster win deals. The standard response has been iPaaS platforms. They help, but they don't fundamentally change the game. You still need engineers to map fields, handle edge cases, and maintain brittle connections. The real breakthrough isn't just automation , it's making integrations LLM-native from the ground up . What Actually Makes an Integration Layer "AI-Native"? Let's cut through the marketing speak. Every B2B tool now claims to be "AI-powered." Most just added a ChatGPT wrapper to their UI. Real AI-native architecture means three things: 1. LLM-Ready Connectivity via MCP Servers Model Context Protocol (MCP) is Anthropic's standard for connecting LLMs to external data sources. If your integration layer doesn't support MCP servers natively, your AI features will always be bolted on, not built in. MCP servers expose your SaaS data to language models in a structured way. Instead of engineers writing custom API wrappers for every LLM interaction, you get a standardized interface. Claude, GPT-4, and future models can query your integration layer directly. Example: A customer support tool with native MCP integration lets an AI agent pull ticket history from Zendesk, check Stripe subscription status, and update Salesforce records in one conversation flow. No custom code. No brittle middleware. 2. AI-Mapped Data Migration Data migration is where most SaaS deals die. Customer says "we'll switch from ServiceNow to your ITSM if you migrate our 50,000 tickets." Your team estimates 6 weeks. Deal stalls. Traditional migration means: Manual field mapping spreadsheets Custom scripts for data transformation Downtime windows Hi

I've been thinking about a specific version of AI-assisted debugging. Not asking which tool is smarter, but asking about the behavior change that would come from removing the context-setup step entirely. Right now I self-select which debugging problems to involve AI on. The threshold is roughly: is this complex enough that the setup cost is worth paying? Copy the relevant code, copy the error, add context about the project structure, ask my question. It takes a few minutes to do well. If the AI could see my IDE directly, no copying, no pasting, just "look at this and tell me what's wrong," I think my threshold would drop significantly. I'd ask about more things. Smaller things. Things I currently just push through myself because they don't seem worth the setup overhead. Whether the answers would be better because the AI sees the actual screen is a separate question. But the behavioral change from removing the friction might matter more than any quality improvement. If AI debugging had zero setup cost, would you use it differently? Or do you think the current copy-paste step is actually useful because it forces you to think through the problem before you ask? submitted by /u/Professional-Peach-3 [link] [留言]

I use Claude a lot for complex problem-solving and Copilot inline in VS Code for quick completions. The difference in actual usage frequency is something I've started noticing. Copilot I use constantly, basically without thinking about it. Claude I use maybe five times a day, and half the time I talk myself out of opening it because I already know what's coming: copy the relevant code, paste it, add context about the project structure and what I was trying to do, explain the error I'm getting, then finally ask the actual question. The friction is small. But it's consistent enough that I default to struggling through something myself, or Googling, instead of opening Claude. The specific case that gets me most is when the problem is visible on screen. I can see the bug. Claude could probably help me solve it faster. But the work of getting what's visible into Claude's context is just enough friction to make me not bother. Is the gap between ""AI embedded in the tool you're working in"" and ""AI in a separate chat window"" meaningful to other developers, or is this a habit thing I should just push through?" submitted by /u/Queasy_Hotel5158 [link] [留言]