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Written by Claude, one of the agents in our room, and checked against the released 0.6.0 package. Yesterday I wrote about getting out of the loop of pasting diffs between Claude Code and Codex. Quorus puts the agents in a room instead: you @-mention one, it wakes in its own git worktree, does the work, publishes to your repo, and asks another agent to review it. 0.6.0 is the release where sharing that room with other people stopped being scary. Invites that don't hand out the secret Before 0.6.0

Most agent-patch gates I see are unordered. Every check runs on every patch, the expensive ones run first, and a twelve-minute suite is spent deciding that a diff has a whitespace conflict. The fix is not more checks. It is a ladder: order checks by cost, abort at the first blocking stage, and spend the remaining budget where the patch actually is. This post is about sequencing and budget, not coverage. It assumes you already have some mix of static checks, targeted tests, property checks, and a

On October 13, a user of agentmemory, an open-source memory system for coding agents, filed an issue with a code block that should not exist. Two memory_save calls, two returned IDs, and about six days later, no memories. The engine had hung on October 7. It held its listening sockets open, never accepted a connection, and the client kept confirming saves that never reached disk. Call it the state-assertion bug: a system's report about its own state diverges from the state. It is not a retrieval

Draft Freely, Publish Narrowly: A Page Ownership Gate for Model-Written Docs Documentation pipelines rarely fail because the model writes badly; they fail because nobody defined which pages a model is allowed to finish. A weak paragraph is visible in the diff, but ownership is invisible, so review attention lands on pages where the risk was already low. The fix is structural rather than stylistic: classify every page before drafting starts, then let a small checker enforce that classification on

Hello everyone! :B I hope you're all doing well. I'm Gonzalo Romero, and I work primarily in software engineering, AI, and pentesting :) . I'm new to the Dev.to community, so please forgive me in advance if I make any mistakes. I'd like to share a course on ML, DL and AI that I've been putting together for the past year and a half. It's called No Shortcuts, it's free, and the whole thing is on GitHub. BlueRingsLabs / no-shortcuts Free Course : Data, Machine Learning, Deep Learning and AI Enginee

Return-value snapshots hide the contract that breaks. Messy repos usually depend on ordered side effects , not on the shape of a result. So before you extract a module, pin the call ledger. Then make the smallest change that keeps the ledger byte-identical. This is the gate I use when a function touches a database client, a queue, and an HTTP client at once. The trick is boring: wrap every boundary, record (op, args-digest) in order, and compare the list before and after the move. Why value asse

MenuMate AI: A Local-AI Restaurant Menu Translator 🍽️🌿 This is my submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle . What I Built I'm a first-year Computer Science Engineering student, and I built MenuMate AI , a multilingual restaurant menu translator powered by a locally running AI model. Restaurant owners and small cafés may need to make their menus understandable to customers who speak different languages. Professional translation can add time and cost, especiall

GH-300 is passed with 700 points in 100 minutes, closed book, so having used Copilot is not enough: you need feature names, where each setting lives and how data flows. This four-week plan follows the six domains of the 7 August 2026 outline and uses only free official resources plus your own editor. Key takeaways Four weeks at about 6-8 hours a week if you already code with Copilot; six if you have never used it. Free official base: the GitHub Copilot Fundamentals Part 1 and Part 2 learning pat

How a DNS race condition took DynamoDB offline in us-east-1 Sunday night, 11:48 PM Pacific. One of the largest databases on Earth is running perfectly. Every server is up. Every disk is fine. And nobody can reach it, because its name no longer has an address. This happened in October 2025. DynamoDB in us-east-1 did not crash, did not slow down, did not lose data. It vanished from DNS. Every system that tried to connect, customer apps and AWS's own internal services alike, got the same answer: th

I've been playing around with Hyprland recently and got tripped up by something silly, so I figured I'd share. I'd been launching Hyprland directly the whole time From the Arch Linux tty, I'd always been starting Hyprland like this: Hyprland I think I just copied it from some wiki or article ages ago and never thought about it again. One day a "use start-hyprland" warning showed up At some point, launching Hyprland started spitting out a warning telling me to launch it via start-hyprland instead

We almost lost forty modules to a file that never changed. The sync job ran every six hours, mirroring our shared working directory into a test workspace. At 21:47 on a Tuesday, it removed about forty private modules that should have been ignored. The filter file was missing one pattern. That's it. One pattern. A colleague had restructured the source tree three days earlier, added a directory, and didn't update the filter file. The script didn't warn, didn't ask, didn't fail. It just mirrored th

Browser Cookies: What Are They, How Are They Used, and How Can They Be Stolen? In this post, I’ll cover: What cookies are When and why cookies are used How cookies can be stolen Common methods used to steal cookies A simple example demonstrating how cookies can be extracted from my two most-used browsers, Firefox Developer Edition and Chromium , using an interesting filesystem-level method A small Go tool that automates the whole extraction flow on Linux — database discovery, copying, decryption

Building a workflow with AI now takes 40 seconds. Checking it takes 40 minutes. That is the line I keep from the opening keynote of In the Loop, the first n8n conference, on 14 October 2026 in Berlin. A week ago, I wrote on LinkedIn what I was watching for: MCP, more autonomous yet controllable agents, human-in-the-loop. I shared my first impressions on the day. Here is the long version: the figures, Jan Oberhauser’s vision, David Roberts’s product announcements, and what it all means for people

I built FaceMatch as a portfolio project: you give it a photo, pick a face, and it ranks the followers or following of an Instagram profile by how similar their profile pictures (and optionally their recent posts) look to that face. Before anything else: a similarity score is not proof of identity. The tool ranks visual similarity, nothing more. I'll come back to the privacy side at the end. Repo: github.com/Eight7Six/insta-facematch How it works Detect all faces in the target image (RetinaFace,

If you shoot a whole catalog in one afternoon, editing one photo at a time is where the evening goes. Here is the batch workflow we use to take a folder of product shots to storefront-ready white backgrounds — three passes, most of it automated. Pass 1 — triage the folder (2 minutes) Open the folder and sort by shooting setup, not by product. All photos from the same light and angle belong in one batch: a tool that keys a white background calibrates per batch, and mixed setups in one batch produ

A citation is useful only if a reader can reopen the exact evidence behind an answer. For a media archive built from PDFs, that operational constraint changes the design: store a stable document URL and page locator with every embedded chunk, carry that metadata through retrieval, assign citation labels before generation, and reject answer citations that are not in the retrieved set. Do not ask the model to remember or invent URLs. TL;DR: treat citations as data lineage, not prose decoration. Th

Looking for a ChatGPT-style experience without being locked into one provider? The open-source ecosystem has plenty of options — maybe too many. 😅 I mapped 51 apps and compared 12 across 64 selection criteria, including: 🧠 Coding, research, and document chat 🔒 Privacy, telemetry, and offline use 🖥️ Desktop, mobile, and self-hosted deployment 🛠️ MCP support and AI agents 👥 Team features and administration 📜 Licensing and project activity The results highlight some useful distinctions. Open WebUI

Accept Crypto Payments Without Building a Full Stack: Meet crypto-pay-local Selling a service online usually means assembling a whole stack: a storefront, a backend for orders, a database so nothing gets lost, and a support channel for the inevitable "did my payment go through?" questions. If you want to accept crypto and skip most of that work, crypto-pay-local is for you. What it is crypto-pay-local is a lightweight Node.js crypto-payment store. It lets you sell services or digital goods for c

Your WebDAV mount feels slow. Here's what actually moves the needle: TCP buffers, TLS handshake amortization, and HTTP keep-alive. TL;DR Three knobs that matter, in order of impact: TLS session resumption — saves the second+ connection ~120 ms each HTTP keep-alive — saves the TCP+TLS handshake on every chunk TCP send/receive buffer size — for >100 MB sequential reads, the default is too small Everything else (chunk size, threading, cache) is roundoff. Test setup Synology DS220+ on LAN, WebDAV ov

Short answer: for real-estate listing discovery, use a staged retrieval architecture with explicit collections, bounded queries, and traceable source context; incrementally upsert changed listing chunks, delete withdrawn records, and prove retrieval quality on a small labeled set before rollout. For real-estate discovery, the least complex workable design is usually one collection per retrieval contract, not one collection per feed or city. Define what a result means, which metadata may filter i

I built a set of four n8n templates around one job: checking whether email addresses are worth sending to, before they go into a sequence, a CRM, or an agent's hands. The templates Google Sheets lead list — reads rows with no verdict, verifies in batches, writes status / score back. Re-runs only pick up new rows, so it's safe on a schedule. Clean a CSV before cold email — upload an Apollo / Instantly / HubSpot export, get back three lists: send_safe , review , drop . Greylisted addresses wait an

Copy the table you can see, not its Markdown, and it usually pastes into columns. When it lands in one column or the numbers come out wrong, these are the fixes. Markdown table to Excel takes a whole ChatGPT, Claude or Gemini answer, finds the tables in it and gives you an .xlsx or .csv file with every value in its own cell. It runs in your browser. Convert a table to Excel The quick way: copy the table you can see Select the finished table in the chat window with your mouse, from the first head

One wrong package name can run attacker code on your laptop or CI Honestly, I'd say npm install is the riskiest five seconds of your day now that typosqatting is so common. It's the potential moment a attacker's code gets a chance to run on your laptop or your CI runner. This is not theoretical anymore. It has happened several time, at a huge scale! Some incide In 2017, The Slovak National Security Office flagged ten fake Python packages. One fake package was urllib ,instead of urllib3 . They al

A few days ago, I was browsing V2EX, a developer community, when I discovered an independent developer’s project called TextToPoster. It was a simple idea: enter some text, choose a visual direction, and let AI turn it into a poster. The website looked polished. It had an attractive interface, design examples, free trials, user accounts, AI image generation, and subscription plans. Then I found out the developer had built another website, Designhint, a collection of design prompts combined with