I Spent 6 Months Testing AI Coding Tools - Here's Which Ones Don't Suck

Let me cut through the bullshit marketing speak and tell you what these tools actually are:

The Reality Check

Traditional AI platforms like GitHub Copilot are basically fancy autocomplete that sometimes works. They'll suggest the right function name 60% of the time and completely hallucinate non-existent imports the other 40%. I've been using Copilot for two years - it's helpful for boilerplate but will confidently suggest deprecated APIs from 2019.

Cursor

Cursor is what happens when someone builds an IDE specifically for AI instead of bolting it onto VS Code. It actually understands your codebase instead of just looking at the current file. The AI can refactor across multiple files without breaking everything. When it works, it's legitimately impressive. When it doesn't, it crashes and takes your unsaved work with it.

The official docs explain the core features, but don't tell you about the memory usage issues in recent 4.x versions or how the indexing can break on large TypeScript projects. The pricing page makes the Pro plan look reasonable until you realize the free tier gives you maybe 60 suggestions per day - which lasts about 30 minutes of actual coding. Check the Reddit discussions for real user experiences, not the polished marketing bullshit.

Windsurf

Windsurf claims to be "agentic" which is fancy talk for "the AI does stuff automatically." Sometimes it's brilliant - I watched it fix dozens of TypeScript errors across multiple files in one shot. Other times it decides to refactor my working authentication system into something that doesn't compile. The results are... unpredictable.

The Windsurf docs are comprehensive but don't mention the random crashes on M1 MacBooks when indexing large projects. Their editor features look impressive until you hit the memory usage wall - I've seen it consume 12GB just sitting idle. The download page doesn't warn you about the WiFi dependency issues that make it useless for remote development.

Replit Agent

Replit Agent is for people who want to describe an app and have the AI build it. It's amazing for demos and prototypes. I built a working todo app in about 10 minutes just by chatting with it. But try to build anything with real business logic or third-party integrations and you'll spend more time fixing the AI's mistakes than writing it yourself.

The Replit pricing will shock you - the free tier is basically unusable and the paid tiers rack up costs fast. Their AI billing docs explain how credits work but not how quickly you'll burn through $40/month. Check Reddit for complaints about unexpected bills that can hit hundreds of dollars. The brand kit looks professional but doesn't mention the compute costs that make real development prohibitively expensive.

Lovable

Lovable is Replit Agent but specifically for web apps. It's surprisingly good at generating functional React components and even handles state management decently. Perfect for landing pages and simple CRUD apps. Anything more complex and you're better off coding it manually.

Their documentation is actually decent, and the video tutorials show real examples instead of marketing fluff. The pricing page is more transparent than most, though you'll hit limits faster than expected on real projects. Read the Contrary Research analysis for a realistic assessment of their business model and technical capabilities.

The brutal truth? Each one excels at specific things and fails spectacularly at others. None of them are the "one AI tool to rule them all" that their marketing teams want you to believe.

I tested each platform on real projects for months. Here's what actually broke, what worked, and what made me want to delete everything and become a farmer.

The Enterprise Reality

Cursor is the only one that doesn't feel like a toy when you're working on a 500k+ line codebase. The AI actually understands context across files, which is mind-blowing after years of Copilot suggesting imports that don't exist. But it crashes randomly on my M1 MacBook Pro when indexing large TypeScript projects. Memory usage goes completely insane - I've seen it hit 12GB just sitting idle - and then it crashes and takes your work with it.

Enterprise teams love the privacy features until they realize half their VS Code extensions don't work. The SSO integration took our DevOps team 3 weeks to configure properly, mostly because the documentation assumes you know how SAML works. Check the enterprise pricing - it's basically "call us" which means expensive. The changelog shows active development but also reveals how many breaking changes they push monthly.

Windsurf has this "agentic" thing where it automatically fixes problems. Sounds great until it decides your working authentication middleware needs "improvement" and refactors it into broken garbage at 2 AM while you're debugging something else. The JetBrains plugin actually works, which shocked me - I've been using it with IntelliJ for Java work and it's probably the best AI experience I've had with enterprise Java.

Read the Windsurf docs for setup instructions, but don't expect them to mention the performance issues on large projects. The editor download is straightforward, but the brand guidelines won't tell you about memory leaks. Check GitHub issues for real user problems that the official channels ignore.

Traditional platforms like GitHub Copilot are what most enterprises actually use because they integrate with existing workflows without breaking everything. But holy shit, the suggestions are inconsistent. One day it's generating perfect error handling, the next day it's suggesting jQuery patterns in a React project.

Startup and MVP Development

Replit Agent is legitimately impressive for prototyping. I described a URL shortener service and it built a working Flask app with Redis caching in about 15 minutes. The deployment "just works" which is refreshing after years of Docker hell.

But here's the catch - try to add OAuth, database migrations, or any real-world complexity and you'll spend more time fixing the AI's code than writing it yourself. The generated TypeScript often has type errors that the AI insists are correct. I've hit the "rebuild from scratch" button more times than I care to admit.

Read the Replit Agent docs for setup instructions, but they don't mention how billing credits get consumed faster than advertised. The AI platform overview looks impressive until you see Reddit complaints about surprise billing costs. Check out Medium's analysis for a realistic view of agent limitations.

Lovable is basically Replit Agent but it only does web apps and does them better. Built a functional e-commerce site prototype in about an hour by describing what I wanted. The React code it generates is actually decent - proper component structure, reasonable state management, even handled form validation correctly.

The limitations hit when you need anything backend-specific. API integration beyond simple REST calls becomes a nightmare. It generated a Stripe integration that looked right but had the webhook handling completely wrong.

The Ugly Truth About Performance

Here's what nobody tells you and it's complete bullshit:

• Battery Life: Cursor and Windsurf will drain your laptop in just a few hours. The constant AI processing is brutal on battery life.
• Network Dependency: Cloud platforms become useless when your internet hiccups. I've lost hours of work when WiFi goes down and Replit can't sync.
• Error Messages: When these AIs generate broken code, the error messages are often cryptic because the code structure doesn't match what the compiler expects.
• Version Conflicts: AI-generated package.json files love to use incompatible dependency versions. Different Node.js versions break in different ways and the AI doesn't keep track of these issues.

The most frustrating part? They all struggle with modern framework patterns. Try to use Next.js 13 app router or SvelteKit's latest features and you'll get suggestions based on outdated documentation.

None of these tools understand the difference between "working in a demo" and "working in production with real traffic, error handling, and security requirements." That gap is where most of your debugging time goes.

For deeper technical analysis, check the Builder.io Windsurf vs Cursor comparison, Bito's feature analysis, and AugmentCode's enterprise comparison. The Wikipedia article on GitHub Copilot provides good historical context, while Stack Overflow AI programming discussions show real developer struggles.