Which AI Coding Assistant Actually Works - September 2025

When AI coding assistants started showing up, I was skeptical as hell. But after GitHub Copilot actually saved my ass on a deadline (it generated an entire Express middleware that would have taken me hours), I figured I should test the rest before my team made me pick one.

The Real Talk on Each Tool

Look, here's what I actually found with each tool:

GitHub Copilot is the one everyone knows because Microsoft shoved it into everything. It works pretty well most of the time, but holy shit does it love suggesting deprecated React patterns. I've lost count of how many times it tried to make me use componentDidMount when I clearly wanted a hook. The free tier has limited usage, which runs out fast during heavy coding sessions.

Copilot is pretty fast for most stuff, though complex refactoring can take a while. The training data from GitHub repositories is both a blessing and a curse - it knows common patterns but also inherits old coding practices from 2019.

Cursor wants you to dump VS Code for their fork. I was resistant at first - who wants to learn a new editor? - but honestly, the AI features are legit better than anything else. Tab completion actually understands what you're building instead of just pattern matching. Cursor's autocomplete feels way snappier than Copilot. The downside? It eats 4GB of RAM just sitting there, and $20/month adds up when you're already paying for Netflix, Spotify, and 15 other subscriptions.

Migration from VS Code isn't as smooth as advertised - some extensions break and you'll spend a weekend fixing your setup instead of shipping features.

Windsurf is the new kid trying to be revolutionary with "AI agents." In theory, you tell it to refactor your entire codebase and it just does it. In practice, I watched it turn a perfectly working React component into a bloated mess that wouldn't even compile. Sometimes it's brilliant, sometimes it generates uncompilable garbage that you spend an hour unfucking.

Codeium being completely free forever seemed too good to be true, but it's held up so far. The completions aren't as smart as Copilot, but for basic autocomplete and "generate this boring function" tasks, it gets the job done. Plus it works in 40+ editors, which is clutch when your team uses a mix of VS Code, IntelliJ, and vim (yes, we have that guy).

Amazon Q Developer is what happens when AWS tries to build a coding assistant. It's great if you speak fluent AWS and want help with CloudFormation, but completely useless for anything else. I tried using it for a React project and it suggested importing from @aws-amplify/ui-react for basic components. Thanks, but no.

It's optimized for AWS services and works well for cloud-native development but struggles outside that ecosystem. Push it beyond its training data and it starts hallucinating AWS configurations that don't exist.

The Money Reality Check

The pricing pages are designed to confuse you, so here's what you'll actually pay:

• GitHub Copilot: $0 for limited use, then $10/month for Pro or $39/month for Pro+ with premium models
• Cursor: $0 for basic features, $20/month for the models that actually matter
• Codeium: Actually free, which makes me suspicious but I'll take it
• Windsurf: Free right now but probably not forever
• Amazon Q: Free for individuals, $19/month for teams (but only useful if you live in AWS)

The Switch Tax Is Real

The hidden cost nobody mentions: switching between these tools breaks your muscle memory for weeks. I tried Cursor for a month, got used to their Tab completion, then went back to VS Code and kept hitting Tab expecting magic that wasn't there. It's like when you switch from iPhone to Android - everything works but nothing feels right.

Also, importing VS Code settings is not as seamless as they claim. Some extensions break, keybindings get weird, and you'll spend a Saturday morning fixing your development setup instead of building actual features.

Budget a weekend to set everything up properly when switching tools, and don't do it the week before a major deadline.

Stop overthinking this. After using all five tools in real projects, here's how to choose without getting stuck in analysis paralysis or falling for marketing hype.

If Money Matters (Spoiler: It Always Does)

Just use Codeium. It's free forever for individuals, works in 40+ editors, and handles basic autocomplete just fine. Yeah, the suggestions aren't as smart as the paid tools, but you know what's really expensive? Paying $240/year for a slightly better autocomplete experience.

If you can swing $10/month, GitHub Copilot is worth it. I've been using it for 2 years and it pays for itself by preventing stupid typos and generating boilerplate. The free tier has limited usage but runs out fast during heavy coding sessions.

For Companies That Aren't Completely Reckless About Security

Amazon Q Developer if you're already living in AWS. The compliance checkboxes are real, and it actually helps with CloudFormation templates instead of suggesting random imports. But seriously, don't bother unless you're deep in the AWS ecosystem.

GitHub Copilot Business has the audit logs and admin controls that make security teams stop bothering you in Slack about compliance. Plus Microsoft's enterprise support actually exists, unlike some of these newer tools where "support" means posting in a Discord channel and hoping someone responds within 48 hours.

If You Want the Bleeding Edge (And Can Handle the Pain)

Cursor has the best AI features, period. Tab completion that actually understands your codebase, access to Claude Sonnet 4 and o3-pro models, and an interface that doesn't suck. The catch? You're basically beta testing someone else's VS Code fork, and when things break, they really break.

I spent 3 hours debugging why my TypeScript wasn't compiling in Cursor when it worked fine in VS Code. Turns out their Node integration was fucked and I had to downgrade some packages.

Another time, Cursor's Composer feature tried to "help" by refactoring my entire Express.js middleware setup. It turned 50 lines of working code into way more complicated than it needed to be - typical over-engineered garbage.

Windsurf is interesting if you like the idea of AI agents doing complex refactoring. I watched it successfully migrate an entire Express app to Fastify in 20 minutes. I also watched it completely destroy a React component by trying to "optimize" it with some experimental patterns. Your mileage may vary.

What I Actually Recommend

For individuals: Start with Codeium (free), upgrade to GitHub Copilot ($10/month) when you get tired of basic completions.

For small teams: GitHub Copilot. It just works, everyone knows it, and onboarding new developers is painless.

For large companies: GitHub Copilot Business. The enterprise features are real and Microsoft support won't leave you hanging.

For the adventurous: Try Cursor for a month. If the RAM usage and occasional instability don't drive you crazy, the AI features are genuinely impressive.

The Hidden Costs That'll Bite You

These tools are more addictive than you think. After using Copilot for a few months, coding without it feels like debugging with print statements instead of a proper debugger. I tried to go back to vanilla VS Code for a week and was constantly hitting Tab expecting completions that weren't there.

Also, if you hit usage limits on the paid tiers, overage charges add up fast. Cursor's Pro tier includes $20 worth of API usage, but power users can blow through that in a week of heavy pair programming sessions.

My Team's Current Setup

We use GitHub Copilot for daily work (reliable, fast, works everywhere) and I keep a Cursor license for experimental projects and complex refactoring. It's not cheap running both, but the productivity boost is worth it when you're shipping features every day.

The junior devs love Codeium because it's free and they're not ready to justify a $10/month subscription. The senior folks prefer Copilot because time is money and better suggestions mean fewer bugs in production.

Recent productivity studies show experienced developers see measurable gains, and our experience matches that data - when these tools work, they really work.