In my last post, I talked about spending time this summer looking at different AI tools. I want to get hands-on, figure out what I want to integrate into my workflow. But before I spend time (and money) testing things out, I wanted to start with the free/trial periods. So you’re starting at the beginning of this journey with me. The question that I started with is: Which AI code assistants will actually let me take them for a proper test drive? In this post, I’ll share what I found across five top AI Coding Assistants—Continue, Windsurf, Cursor, GitHub Copilot, and Tabnine—and what I’m interested in learning as I put them to the test.

The Trial Landscape: What's Actually Available with AI Assistants

After digging through pricing pages, here's what you can try without putting in your credit card:

1. Continue.dev is one of the most flexible and accessible AI Coding Assistants out there. It’s open source, which means you can literally use it forever for free if you just bring your own API keys, and it supports any model you choose, including Claude 4 Sonnet, 4o, llama3.1 8b. Continue’s IDE extension has gained a lot of recent attention (20K+ GitHub stars), and integrates into tools that you might already use (VS Code and JetBrains). You can also create public assistants and invite your entire team.
2. Windsurf surprised me here. Their free tier includes 25 prompt credits per month, all premium models, unlimited Fast Tab completions, and even a 2-week Pro trial to test the advanced features. Built by the Codeium team, it's essentially giving you a full-featured AI IDE for nothing. The supercomplete feature claims to understand your entire workspace to give intelligent suggestions across files.
3. Tabnine offers a "Dev Preview" that's completely free for qualified users, giving you AI code completions for current line and multiple lines, plus AI-powered chat. There's also a paid Dev plan at $9/month with more advanced features. The Dev plan includes their foundational AI agents that can autonomously generate code, tests, docs, and fixes.
4. Cursor gives you a Pro two-week trial as part of their free Hobby plan, plus 2,000 completions to play with. After that, their Pro plan is $20/month. It’s a significant jump but with unlimited agent requests and tab completions, two weeks is enough time to test their agent mode on a real project and see if the autonomous coding capabilities live up to the hype.
5. GitHub Copilot offers a solid 30-day free trial on their Pro plan before charging $10/month. Thirty days is actually enough time to see if it clicks with your workflow or just generates more bugs than it fixes. Since it’s deeply integrated in the GitHub ecosystem, you’ll be able to see how well it understands project context.

What to Actually Test During Your Trial

I want to avoid some of the common problems I hear developers talk about when they sign up for AI Coding Assistants. I want to do more than test drive a car and park it in a lot. Here’s the approach I’m trying to take:

The Real-World Gauntlet

1. Test it on your actual codebase. I have some existing projects that I’ve created over the years. My blog is a Jekyll site that I have done only enough updating to keep things running over the past couple of years. It definitely has some "why did past me write this" code in the codebase. I want to make sure that AI can handle past me. (I’m actually interested in creating a Continue assistant to help update my Jekyll site.)
2. Try it on unfamiliar territory. I need my AI Coding Assistant to be a force multiplier. When I'm working in my strengths, it doesn’t take me as long. But when I use it with code that I’m not super familiar with, I need it to be good. I don’t want it to help me write bad code faster. Test both scenarios. I have a new project I’ve been wanting to work on, and this seems like a good use case.
3. See how it handles context. Can it understand your team's coding conventions? Does it remember what you were working on five files ago? Context awareness separates the good from the great. This is not applicable for what I’m working on right now, but this is super important if you’re working with a team.

The Stress Test

You should try to push these tools to their breaking point. (Semi-related, I posted about LLMs giving up when we need them the most. Feel free to add to the conversation! Ask them to refactor a complex function. Have them write tests for edge cases you know are problematic. See if they can debug that one weird issue that's been haunting your team for weeks.

The goal is to find the AI Assistant that fails gracefully and teaches you something useful in the process.

The Hidden Costs

This is where the trial period becomes really important. Most AI assistants have usage-based pricing that can get out of hand really quick. You can eat through your budget if you're not careful. During your trial, pay attention to those usage meters since they're previewing your future bills.

Start with the free tiers. Continue if you want maximum control, Windsurf if you want simplicity, Tabnine if you just want better autocomplete.

Use the trial period to answer this question: Does this tool make you a better developer, or just a faster typist? At the end of the day, you're responsible for all production code you ship. If you don't understand your code, AI is a temporary solution to your problem, and that approach can end badly.

Here's your homework (and we can do it together, just comment which one you’re testing below!):

• Pick one tool from the list above
• Set it up on your current project
• Use it for a week on real work (not tutorials)
• Ask yourself: "Am I learning, or just copying?"

I plan on starting with Continue and working my way through the list.

The right AI assistant will enhance and amplify your skills, not replace them.