标签：#dev

So i've been putting off this project for months but i really need to bu͏ild android a͏pp for this side business idea i have. Problem is i don't know java and honestly don't have time to learn it properly right now. I've heard there are ways to build apps without actually coding everything from scratch but not sure what's legit vs what's just marketing bs. I can handle basic web stuff but mobile development seems like a whole different beast. Anyone here successfully built an android app without going the traditional java route? What tools or platforms actually work and don't make your app look like garbage? submitted by /u/Significant_Law5994 [link] [留言]

If you're a fashion or DTC brand doing under €50M GMV, you'll get more out of a monolithic platform than a composable build, because the complexity tax for that flexibility runs higher than a year of performance marketing for most brands at that tier. Composable was sold as freedom, but for most brands at small-to-mid GMV it lands as engineering-org overhead you fund forever just to keep the lights on, while monolithic platforms ship 80% of what most brands need with one team and one contract. The exception is brands running multi-brand groups across countries or genuine enterprise peaks, where composable does pay off, but you want the platforms built by retailers rather than the ones built for analyst slides. Centra, NewStore, and SCAYLE land closer to that brief than commercetools or open-source MACH stacks. If a vendor opens their pitch with microservices and best-of-breed architecture, they're selling you an engineering project, and most brands just need a platform that ships things. submitted by /u/Majestic_Shoulder188 [link] [留言]

You've seen the developer. Maybe you are the developer. They discover DRY — ✨ Don't Repeat Yourself...

In May, I continued my "One Commit a Day" Challenge and spent more time contributing across different open-source projects. Compared to April, I was able to contribute a bit more and explore a wider variety of repositories. Repositories That Stood Out Some of the projects that left the biggest impression on me were: python-odpt Huggin Face Context Course Human Signal ML ScribeSVG A Stable Checkpoint One milestone I was happy about this month was reaching a stable checkpoint for my Tokyo MCP Server project. It is still a work in progress, but getting to a point where the project feels stable enough to build upon was a satisfying moment. Documentation Matters Another contribution that stood out was helping improve a python-odpt README documentation . It wasn't a large technical contribution, but it reminded me that making a project easier for others to understand can be just as valuable as writing code. Good documentation lowers the barrier for future contributors. Sometimes, a clearer README can help more people than a small code change. Learning Beyond Python One practical lesson I learned this month was that being a Python-focused contributor doesn't mean I can ignore the JavaScript ecosystem . While working with different repositories, I finally installed Node.js and started using npm . Many modern open-source projects rely on TypeScript-based tooling, build systems, or development workflows, and understanding those tools makes contributing much easier. The Biggest Challenge: Finding Information And Communication Matters The biggest challenge I faced wasn't coding. It was documentation. Every repository has its own way of organizing information. There are definitely common patterns, but every project also develops its own style over time. Sometimes the information I need is in the README. Sometimes it's in a wiki. Sometimes it's buried in a docs folder several levels deep. And sometimes it's spread across all three. Open Source Is Also About Navigation As a contri

A physiotherapist asked me a simple question a couple of months ago: "Can you build something to run my whole clinic?" So I did — solo, in about a week. Here's the full 2.5-minute walkthrough 👇 What PhysioFlow does PhysioFlow runs an entire physiotherapy clinic from one screen — built for India (₹, GST, WhatsApp, +91): Dashboard — attendance, collections & pending bookings at a glance Patient files — recharge session packs, track usage, auto-generate GST-ready bills Attendance in seconds with a QR scan Online bookings that convert straight into a patient file Reports — daily ledger, revenue, CSV/PDF export Patient portal — patients see their own sessions & prescriptions The stack Next.js + Supabase + TypeScript — multi-tenant, with row-level security so no clinic's data ever leaks to another. Try it Live now with a 14-day free trial, no card needed → https://physioflow.devfrend.com I'm Amar, a full-stack & AI engineer. I design and build products like this end-to-end. I'm open to work — SaaS builds, MCP servers, LLM apps & automation. Reach me on LinkedIn .

This is a submission for the Hermes Agent Challenge , under the Write About Hermes Agent prompt. I've spent the last week testing AI memory failure modes in a public evaluation harness. That work changed how I read agent memory systems. This is a writing submission, not a build submission. I did not build a Hermes Agent project for this challenge. I am writing from the perspective of someone testing how memory failures show up once agents can act. So when I look at Hermes Agent, the question I care about is not only: Can the agent remember useful things? The harder question is: When memory conflicts, which memory is allowed to govern the agent's action? That distinction matters. Hermes Agent is interesting because it is not just a chat interface. Its documentation describes an open-source agentic system with tool use, project context, persistent memory, skills, browser automation, checkpoints, delegation, scheduled tasks, and multiple memory providers. That is exactly the kind of system where memory stops being a convenience feature and starts becoming part of the agent's operating boundary. If an agent can run tools, edit files, browse, delegate work, schedule tasks, and remember across sessions, then memory is no longer just "context." Memory becomes governance. The Memory Problem I Would Watch For In a simple chatbot, bad memory is annoying. In an agent, bad memory can become operational. The failure mode is not only that the agent forgets something. Sometimes the more dangerous failure is that it remembers the wrong thing too confidently. A memory can be: relevant but stale, relevant but low-authority, relevant but superseded, relevant but only context, relevant but not allowed to determine the action. That is the distinction my own tests kept running into. Retrieval systems are usually good at answering: What memory is closest to the user's request? But safety often depends on a different question: What memory is allowed to decide what the agent should do? Thos

Overview I built Hermes Financial Agent — an AI-powered financial assistant for investors in the Egyptian Exchange (EGX). The goal: not just calculate portfolio value, but explain risks in a transparent, auditable way. Features Real EGX market data via Yahoo Finance Portfolio tracking and valuation Daily financial reports Telegram-user portfolio isolation Cached quote fallback for resilience Explainable risk insights Explainable Risk Intelligence Unlike traditional trackers, Hermes surfaces: Portfolio concentration risk Stale market data exposure Quote coverage percentage Valuation gaps from unavailable data Users understand confidence level behind their valuation — not just the number. Technical Stack Hermes Agent framework Python GitHub Actions (automated smoke testing) Offline-safe quote fallback architecture Repository 🔗 GitHub Repository Future Roadmap News sentiment analysis Investment thesis tracking Market briefing generation Advanced financial reasoning agents hermeschallenge

Hey guys, would love to get some feedback on whether my approach here makes sense. I’m building a real-time chat application where users can upload and receive images/files. Files can be fairly large (up to ~100MB). Current stack is: fastapi, websockets, tanstack, postgres and redis. I use GCP as my cloud provider. My current flow is: Backend generates a signed URL Frontend uploads directly to a GCS bucket A Cloud Function handles post-upload processing For downloads, the frontend fetches directly from GCS using redirects/signed URLs so the backend doesn’t become a bottleneck This architecture works great for smaller files (<30MB), but once I started testing larger uploads (100MB images/videos), I noticed very high memory consumption during processing (btw pagination & virtualization is used throughout the project). I’m trying to figure out what’s considered best practice here for large media uploads in chat systems: Should compression/downscaling happen client-side or server-side (currently there is not compression at all)? Also, Is it common to generate thumbnails/previews (for images) separately while keeping the original untouched? Should I stream uploads instead of buffering them? Are Cloud Functions even the right choice for heavy file processing? For images specifically, I’m considering: client-side compression before upload, automatic thumbnail generation, storing multiple resolutions, converting to formats like WebP/AVIF. Would love to hear how you guys handle this in production systems. Thanks! submitted by /u/omry8880 [link] [留言]

This is a submission for the Hermes Agent Challenge : Write About Hermes Agent Hello, DEV friends! 👋 If you have been exploring the world of Artificial Intelligence lately, you have probably heard a lot of buzz about "AI Agents." But what does it actually feel like to build with one? Today, I want to share my personal experience working with Hermes Agent . I used it to build a smart assistant called the Alpha-Dairy Quant Pipeline —a system that helps track and make sense of food market data. ( https://github.com/HopeBestWorld/alpha-dairy-pipeline ) Whether you are an expert coder or just curious about AI, I hope this friendly guide inspires you to try building an agent of your own! What is Hermes Agent, Anyway? Think of a standard AI as a helpful chatbot that answers questions when you ask them. An AI Agent , on the other hand, is more like a proactive assistant. You give it a big goal, and it sits down, makes a step-by-step plan, uses digital tools, runs code, and checks its own work until the job is done. For my project, I wanted to track market prices for three major dairy products: Cheddar Blocks, Butter, and Dry Whey. Instead of doing all the math and graphing by myself, I let Hermes Agent take the wheel. The Magic of Multi-Step Reasoning The coolest part of working with Hermes Agent is watching it "think". When I asked my agent to look at our data database ( market_intelligence_3.db ) and find the best trading strategy,it followed a beautiful planning loop: Checking the Files: It looked at our setup files ( tickers.yaml and requirements.txt ) to make sure all its tools were ready. Running the Math: It triggered a Python program ( backtest_engine.py ) to study weekly market history. Making Decisions: It realized that Dry Whey was way too wild and risky to trade right now, so it intelligently gave it a 0% safety rating and put the focus on Cheddar and Butter instead. Drawing and Sharing: It automatically drew a beautiful performance chart ( backtest_analysis.png

Looking for assistance. Copy/Pasting my post from another sub. Hey all, young web dev/designer here. If helpful, I run SiteGround hosting, WordPress, Divi 5 builder. I'm having a really confusing issue that I can't resolve in a satisfying way. For some reason, a hidden menu for an Italian water company (revital.it) is getting placed onto my website. It's honestly baffling. The site I'm currently troubleshooting is holbrook-electrician.com. I've seen this happen now on two websites that I've built. I've used Divi Cloud sections that I built on one and used on the other, so unsure if that's how it's getting placed onto the site. There will be rare instances where if I view my live site, the menu will be overlayed overtop the page (pictured). Both page source and inspect show the revital.it links. From what I've gathered with the help of AI, the menu is tied to a Divi canvas called "menu slide". The thought is that it came in with a template import, but I don't remember using a template when I first started (1-2 months ago). I think I started from scratch. I obviously want to remove all links and prevent them from reappearing. I can't find them anywhere in the page builder. I can't trace it to any plugin I'm using or code I've added. The only success I've had to remove it is going to phpMyAdmin, and running a query to eliminate instances of "revital.it". I did this once for this site, but it looks to have come back for unknown reasons. Just to confirm, I have nothing to do with this Italian website. I did not put this menu or the links on my site. I really have no clue how it originally got here, how to prevent it from appearing on other sites I look to build, and how to permanently remove it. Any help or suggestions would be greatly appreciated! Rouge menu overlayed on my home page submitted by /u/exodeath29 [link] [留言]

Every MCP server you run locally executes with your full filesystem and network permissions. That means the GitHub MCP server, the Slack one, that third-party tool you installed from npm last week — all of them can read your SSH keys, .env files, and credential stores by default. Anthropic just open-sourced the fix: sandbox-runtime , the sandboxing layer they built for Claude Code. One-line wrap, no Docker, OS-level enforcement. What actually changed srt (the Sandbox Runtime CLI) enforces filesystem and network restrictions on any process using native OS primitives: macOS : Uses sandbox-exec with dynamically generated Seatbelt profiles Linux : Uses bubblewrap for containerization + network namespace isolation Network filtering : HTTP/HTTPS traffic routes through an HTTP proxy; other TCP goes through SOCKS5 — both enforce your domain allowlists Install it: npm install -g @anthropic-ai/sandbox-runtime Wrap an MCP server in your .mcp.json — change command from npx to srt , move the rest to args : { "mcpServers" : { "filesystem" : { "command" : "srt" , "args" : [ "npx" , "-y" , "@modelcontextprotocol/server-filesystem" ] } } } Then configure what the process is actually allowed to touch in ~/.srt-settings.json : { "filesystem" : { "denyRead" : [ "~/.ssh" ], "allowWrite" : [ "." ], "denyWrite" : [ "~/sensitive-folder" ] }, "network" : { "allowedDomains" : [ "api.github.com" , "*.npmjs.org" ] } } The result: the MCP server can work in your project directory, talk to the domains it needs, and nothing else. Why this matters The threat model is real. An MCP server running compromised code — or simply a server with more ambient access than it needs — can exfiltrate your SSH keys, read your .env files, or phone home to arbitrary hosts. This isn't theoretical; it's the same class of supply-chain risk that exists for any untrusted npm package, except MCP servers are typically long-running processes with broad system access. srt is designed secure-by-default : processes start wit

This is a submission for the Hermes Agent Challenge : Build With Hermes Agent The Problem Nobody Talks About Every time the Reserve Bank of India publishes a circular, somewhere inside an Indian bank, a compliance officer opens a PDF. They read it. They try to figure out what it means for their institution specifically. They write a summary email. They forward it to five department heads. They chase those department heads for two weeks to confirm it's been actioned. They build a spreadsheet to track all of this. And then the next circular drops and the cycle starts again. RBI publishes hundreds of circulars a year. SEBI publishes more. MCA publishes more still. Compliance teams at Indian banks are drowning — not because they're incompetent, but because the volume of regulatory output has outpaced any reasonable human ability to track it manually. The fine for missing a deadline isn't a polite reminder. It's a penalty notice. This is the problem I built for. What I Built RBI Regulatory Digest Agent — an autonomous multi-step agent powered by Hermes Agent that monitors RBI and SEBI publication feeds, reads every new circular, extracts structured action points from the regulatory text, and delivers a formatted intelligence report to compliance teams automatically. No human reads the circular first. No human decides what's important. No human routes it to the right department. The agent does all of that. The pipeline RBI/SEBI feeds → new circular detected → full text extracted → LLM analysis → structured action points → risk classification → HTML dashboard generated → email delivered Every action point extracted contains: What needs to be done — specific and actionable, not a vague summary Deadline — parsed from the circular text Responsible department — Credit, Compliance, Treasury, Operations, IT, Legal Evidence required — what documentation confirms completion Priority — Critical (overdue or <7 days), High, Medium, Low From a new circular to a structured compliance b

This is a submission for the * Hermes Agent Challenge * : Build With Hermes Agent What I Built CareSync is a local health memory agent for student caregivers. I'm Naomi, a 21-year-old engineering student. Between classes I help care for my grandma Kamala (78, high blood pressure, type 2 diabetes). I often forgot details from previous doctor visits, missed symptom patterns, and struggled to hand over care information to family members. CareSync solves that with longitudinal memory. Symptoms, meals, vitals, medications, and reports are stored in a local SQLite database. The CLI can search history, identify patterns, and generate appointment summaries. Hermes Agent exposes the same capabilities through natural language. What you get: One-line logging: ./caresync add "dizzy spell after lunch" Pattern search across weeks of history Medication tracking and report imports Doctor questions, appointment briefs, and handoff notes Full audit log of agent actions 7 Hermes skills mapped to real terminal commands Local-first design with no cloud storage CareSync is not medical advice. It helps caregivers observe, organize, and prepare. Demo The demo walks through: Logging a new symptom Searching health history for recurring patterns Generating doctor questions and appointment briefs Using Hermes in natural language to query past events Reviewing the audit trail of actions taken Example commands shown in the demo: ./caresync search --person Kamala --query dizziness ./caresync timeline --person Kamala ./caresync questions --person Kamala ./caresync brief --person Kamala --days 14 ./caresync chat "has grandma been dizzy before?" Code Repository: https://github.com/Byte-Sized-Brain/caresync Architecture My Tech Stack Hermes Agent Python 3.12 SQLite agentskills.io skill framework Terminal-based CLI Nous Portal How I Used Hermes Agent CareSync uses Hermes Agent as the orchestration layer between natural language and real caregiving workflows. I created 7 Hermes skills that map directly

And before you ask, yes, it's free. always will be. I built it in 48 hours. planning to release it tonight or tomorrow. submitted by /u/West_Subject_8780 [link] [留言]

I saw someone mentioned a guest book and I had to look it up. Apparently people would leave public messages on a dedicated page and you can reply to them. Guess spam ruined that. Any thing else, didn't really get to experience it being young and all. Maybe some could make a comeback and one of us could implement it. submitted by /u/Successful-Title5403 [link] [留言]

I’m building a web app called EccoMuse, it’s a music discovery platform that lets listeners blend their music tastes with the tastes of artists, with features to monetize these unique playlist blends. Right now, I'm tackling the classic marketplace problem: distinguishing regular users/listeners from the actual artists. I need to make sure that if someone claims to be JPEGMAFIA or a small indie artist, they are actually that person (or their manager), and not an impersonator trying to hijack the profile. I want to avoid scraping Spotify bios (against ToS/fragile) and I can't rely on OAuth for X/Twitter because their new API pricing is too expensive for a bootstrapped summer project. Here is the manual verification system I currently have planned: Standard Login: User logs in as a listener (SSO/Email). Claim Profile: They paste their Spotify/Apple Music URL and their primary social handle (IG/X), then declare if they are the Artist, a Faceless Artist, or a Manager. The Challenge: The app generates a unique 6-digit code. The Proof: Public Artists take a webcam selfie holding the code, AND DM the code to our official Instagram from their verified/established artist account. Managers / Faceless Artists skip the selfie but must DM the code from the official artist account OR email us from the public booking email listed on their Spotify/socials. Manual Review: I look at the DM/Email, verify the account authority, cross-reference the selfie (if applicable), and manually approve the claim. Why it doesn’t feel fully fortified: While this works and costs $0 in API fees, it feels like it has some friction and potential holes. What if the manager doesn't have access to the artist's Instagram to send a DM? Is a webcam selfie too much friction for onboarding? How can I make sure an impersonator doesn't get through, I dont want someone to pretend to be an artist. I initially thought about asking them to put the code in their public IG or SoundCloud bio, but artists hate defacing

I'm 22, working as a fullstack developer at a startup. 9 hour days, decent enough at my job, but completely switched off after work hours. I don't want to leetcode after work. I don't want to learn new frameworks at night. I want to write, play guitar, and just exist peacefully. I'm not trying to become a senior dev or a tech lead. I just need the salary to sustain while I build something on the side that actually excites me. My question is — how long can someone realistically coast on existing skills without getting fired or becoming unemployable? And what's the bare minimum to stay relevant without burning out? Not looking for "passion for tech" lectures. Just honest experiences from people who've been there. submitted by /u/Available_Guess_7344 [link] [留言]

There is a fascinating psychological phenomenon in modern software engineering: the relentless pursuit of the upgrade. As frontend developers, we are conditioned to believe that speed and efficiency come from adopting the newest technologies. We migrate from Webpack to Vite to shave seconds off our build times. We transition between UI libraries in search of better reconciliation algorithms. We constantly audit our CI/CD pipelines. We treat performance as a destination we must reach by continuously adding or swapping out the moving parts of our toolchain. Yet, amidst this endless cycle of optimization, we consistently overlook the most sophisticated, highly optimized piece of software in our entire stack. It is the software you are using to read this article right now: the web browser. The Underappreciated Engine The modern browser is an absolute marvel of engineering. Over the past decade, teams of the world's most talented systems engineers have engaged in a fierce arms race to optimize browser engines like V8, SpiderMonkey, and JavaScriptCore. Today’s browsers feature Just-In-Time (JIT) compilation, sophisticated garbage collection, and massively parallelized rendering pipelines. They are capable of executing highly complex, interactive applications with a level of fluidity that was unimaginable a few years ago. However, when we evaluate developer tools—specifically the online IDE or the browser-based code editor—there is a stark contrast. The environments we use to write and test our code rarely reflect the speed of the engine they run inside. Why the Standard Web IDE Misses the Mark If you want to quickly prototype a component or isolate a bug, you will likely reach for a frontend playground or a popular Replit alternative. What happens next is often a masterclass in friction. The environment feels heavy. The interface is cluttered with features you didn't ask for. As you type, the live code editor experiences micro-stutters. The instant live preview isn't actu

The plan was simple Take the specs we'd written, turn them into Jira epics, stories and subtasks, and start sprinting. It took longer than expected. Here's what actually happened — and what I learned. Why automate Jira setup at all? HandyFEM has 8 epics, 37 stories and ~160 subtasks. Creating that manually would take a full day and be error-prone. More importantly: the specs were already written in a structured format. Translating structured data into Jira issues is exactly the kind of repetitive task that should be automated. So I wrote a Node.js script to do it via the Jira REST API. Problem 1 — Jira Spaces ≠ Jira Classic My account uses Jira Spaces — Atlassian's newer interface. The classic Jira has CSV import built in. Jira Spaces doesn't. This isn't documented anywhere obviously. You discover it by looking for the import option and not finding it. Lesson: always check which version of Jira you have before planning your workflow. The API still works, but some endpoints behave differently. Problem 2 — The API token wasn't the issue (until it was) First attempt: connection error. I assumed it was the token. It wasn't — it was an expired token from a previous session. Regenerating it fixed the connection. The real lesson: curl -u email:token https://your-domain.atlassian.net/rest/api/3/myself is the fastest way to verify auth before running any script. Problem 3 — customfield_10014 doesn't exist in team-managed projects In classic Jira, linking a story to an epic uses a field called customfield_10014 (Epic Link). In team-managed projects (Jira Spaces), this field doesn't exist. You use parent instead. The error was clear once I saw it: "customfield_10014" : "Field cannot be set. It is not on the appropriate screen, or unknown." Fix: remove customfield_10014 , keep only parent: { id: epicId } . Problem 4 — Board search doesn't work for team-managed projects The Agile API endpoint /rest/agile/1.0/board?projectKeyOrId=HFM returns empty for team-managed projects, even

If you've ever worked with auth, you've seen a JWT — a long string like eyJhbGci... split into three parts by dots. It looks cryptic, but it's surprisingly simple once you see inside. A JWT has three parts header.payload.signature Header – tells you the signing algorithm, e.g. {"alg":"HS256","typ":"JWT"} Payload – the claims (the actual data), e.g. {"sub":"123","name":"John","iat":1516239022} Signature – verifies the token wasn't tampered with (needs the secret/key) The header and payload are just Base64url-encoded JSON — not encrypted. That means anyone can read them. So: ⚠️ Never put secrets in a JWT payload. It's signed, not hidden. Decoding one yourself You can decode the payload in the browser console: const [, payload ] = token . split ( " . " ); console . log ( JSON . parse ( atob ( payload ))); Or, if you just want to paste a token and instantly see the header + payload (without sending it to a server), I built a free decoder that runs entirely in your browser: https://forgly.dev/tools/jwt-decoder Decoding ≠ verifying Reading a JWT is trivial. Trusting it is not — you must verify the signature on your server with the secret/public key before relying on any claim. Decoding just lets you inspect what's there. That's the whole mental model: a JWT is a readable, signed envelope — not a locked box.