惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

罗磊的独立博客
www.infosecurity-magazine.com
www.infosecurity-magazine.com
V
Visual Studio Blog
T
The Blog of Author Tim Ferriss
GbyAI
GbyAI
Y
Y Combinator Blog
雷峰网
雷峰网
Last Week in AI
Last Week in AI
Jina AI
Jina AI
月光博客
月光博客
G
Google Developers Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Webroot Blog
Webroot Blog
Google DeepMind News
Google DeepMind News
博客园 - 三生石上(FineUI控件)
Hacker News - Newest:
Hacker News - Newest: "LLM"
N
News | PayPal Newsroom
H
Heimdal Security Blog
Recorded Future
Recorded Future
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
腾讯CDC
AWS News Blog
AWS News Blog
NISL@THU
NISL@THU
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园 - 【当耐特】
P
Privacy International News Feed
I
Intezer
V
Vulnerabilities – Threatpost
The GitHub Blog
The GitHub Blog
L
LINUX DO - 最新话题
S
Schneier on Security
C
CXSECURITY Database RSS Feed - CXSecurity.com
小众软件
小众软件
博客园 - 聂微东
V2EX - 技术
V2EX - 技术
W
WeLiveSecurity
Security Latest
Security Latest
PCI Perspectives
PCI Perspectives
The Hacker News
The Hacker News
T
Threatpost
C
Check Point Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Latest news
Latest news
L
LINUX DO - 热门话题
J
Java Code Geeks
A
Arctic Wolf
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
T
Troy Hunt's Blog

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
medo.dev the good, bad and ugly from my personal experience
fikuri · 2026-05-17 · via DEV Community

So I joined the MeDo hackathon and used their platform for several days. At first, I thought it was just another v0, Lovable, or Bolt. But after building with it, I realized MeDo offers a very different way to prompt, build, and ship a product.

This is my personal review after around two weeks of using it: the good, the bad, and the ugly. I was genuinely impressed by the deep integrations and some unique features that I think many people might miss. But the platform also has rough edges that are worth talking about.

Background

In today's developer world, many programmers use tools like Claude Code and Codex. They are powerful and flexible. You can build almost anything with them, but you still need to manage everything yourself: setup, environment, dependencies, backend, database, deployment, and debugging.

Of course, you can ask Claude Code or Codex to help with that. But if you do not already know what you need, things can get messy fast.

For non-technical users, or developers who do not mainly build web apps, tools like v0, Lovable, and Bolt feel easier. You do not need to set up much. You prompt, and you see the output quickly.

But once you want to build a complete product, you still need more than a frontend. You need backend, database, authentication, AI APIs, image generation, payments, and many other services.

Yes, tools like v0, Lovable, and Bolt can connect to those things. But you still usually need to create your own Supabase account, connect it, manage API keys, register for OpenAI, Anthropic, GCP, or another provider, and wire everything together.

And then there is the classic problem: API keys. The same API keys people accidentally push to GitHub and then get abused by someone else.

That is where MeDo starts to feel different.

The Good

1. You do not need to open another service, mostly

At first glance, MeDo looks similar to v0 or Lovable. But the difference is that many things are already built into the platform.

Need a backend? It is already built in through Supabase.

Want to add an LLM? Just prompt it. It is already integrated.

Want image generation? It is already built in.

Want text-to-speech? It is already built in.

Want a weather API? It is already available.

Want payment? You still need Stripe, and you still need to register your business and get the API keys. So yes, the legal/business side still exists.

But overall, many services that usually require separate setup are either built in or available through plugins. I think this is MeDo's strongest USP. You do not need to manage and pay for many separate services. You mostly manage MeDo.

Imagine your vibe-coded app starts getting traction. If you use v0, Lovable, or Bolt, you may need to upgrade Supabase, top up credits on GCP or another AI provider, and manage other API services separately.

With MeDo, the experience feels more centralized. You pay and top up credits in one place. As a product builder, I think this is very useful, especially for non-developers who just want to build and publish a real app.

2. Deep backend and frontend integration

Because the backend and frontend live inside one platform and one codebase, the AI agent can understand more of the full product.

That makes building and debugging easier.

For example, I had an issue where a service integration returned a 403 error. The problem was not really in the frontend code. The backend had not redeployed with the correct key. The agent checked the Supabase function logs, looked at the backend code, understood that the problem was the backend not restarting, restarted it manually, and the bug was fixed.

That kind of end-to-end debugging is where MeDo feels powerful.

3. Plugins, plugins, plugins

The plugin system is one of the most interesting parts of MeDo.

The available plugins are diverse and keep growing. I saw plugins for exchange rates, global stock data, data analysis, Word documents, PowerPoint, and more.

To be clear, these plugins are not always like traditional third-party integrations where you connect an external service yourself. Many of them feel more like skills or templates integrated into the platform and database.

But because the model can use them inside the same environment, they become very useful. You do not need to manage every integration manually. MeDo handles a lot of that inside the platform.

4. Design direction and starter templates

I still think v0 is stronger for frontend design. That is probably the thing v0 does best.

MeDo is slightly below v0 in pure frontend polish, but I like that it gives starter references and does not always force the same visual style. It gives you enough structure to begin, while still leaving room to push the app in a different direction.

This part still needs more testing from me, but so far the design workflow feels promising.

The Bad

1. It is still buggy

The biggest downside, in my opinion, is that the platform still buggy. Maybe this is because it is new, but sometimes messages fail multiple times and you need to clear the context manually.

this can be frustrating in my personal experience.

2. The platform feels slow

The slowness is not always about the model generation itself. The platform UI can also feel slow.

Opening the plugin list takes a few seconds. Some images seem unoptimized or not cached well, so they load slowly again and again.

This is not a deal breaker, but it makes the product feel less smooth than it could be.

The Ugly

1. Language inconsistency

The platform still feels China-first in some places, with English as a second layer. Some parts of the UI are not translated, or the interface suddenly switches to Chinese.

Sometimes the model also replies in Chinese or uses Chinese placeholder text in the generated UI.

This is probably fixable on their side, but it stood out during my usage.
for example

2. Unclear model identity

MeDo has "fast" and "deep build" models. I assume they use their own proprietary model, although the behavior sometimes feels close to Claude model in my opinion.

The problem is that I do not know what model is actually being used. I do not know the benchmark, the strengths, the weaknesses, or how I should prompt it.

Should I prompt it like Claude? Like Codex? Like another coding model?

That uncertainty is annoying as a builder. I wish the platform was more transparent about what model is being used, or at least how users should think about each mode.

Final Thoughts

MeDo is not just another frontend generator. for me it is feels like the true "full-stack" development platform, you only need this platform to get your app from zero to one from above and beyond

It is still buggy. It can be slow. Some parts still feel rough for English-speaking users. But the core idea is strong.