The Setup: Why I Decided to Actually Test Both
Three months ago, I did something that probably made my manager nervous. I decided to spend 90 days treating GitHub Copilot’s freshly announced Agent Mode and Cursor as serious contenders for my primary development environment. Not as side projects or weekend experiments, but as the actual tools I’d use to ship code that would end up in production systems. I’ve been writing software professionally for long enough to know that the gap between a tool’s marketing narrative and its real-world utility is usually measured in disappointment, so I wanted to find out whether either of these could genuinely change how I work.
The timing felt right. GitHub announced Copilot Agent Mode in public preview back at GitHub Universe in October 2024, and it promised something that had previously lived in the realm of science fiction: multi-step autonomous task execution happening directly inside VS Code without ever leaving the editor. Meanwhile, Cursor had just completed a Series B raise at a $2.5 billion valuation in August 2024, which suggested that serious money was betting on AI-native IDEs as a fundamental shift rather than a passing trend. When 76% of developers are either using or planning to use AI coding tools according to the Stack Overflow Developer Survey 2025, it feels less like a prediction and more like a statement of where the industry is already headed.
Agent Mode: Watching the Code Write Itself (Mostly)
Here’s what surprised me most about Copilot’s Agent Mode: it’s genuinely more capable than I expected, and genuinely more limited than the marketing suggests. The feature works by letting you describe a task in natural language, then it orchestrates multiple steps to accomplish it. You can watch it branch out, explore your codebase, make edits, run tests, and iterate. It feels like having a junior engineer at your shoulder who can actually type faster than you and doesn’t need coffee breaks.
The real win is that everything happens inside VS Code with no context switching. You don’t open a separate window, you don’t paste code into a chat interface, you don’t wait for API responses to load in a browser. For experienced engineers, that friction reduction matters more than you’d think. I found myself using Agent Mode for boilerplate work, test generation, and refactoring tasks that would normally require three context switches to get through. The tool uses GitHub’s remote repository graph for indexing, which gives it visibility into dependency trees and cross-repository relationships that a locally-indexed tool wouldn’t have.
The limitation? Agent Mode works beautifully for tasks that fit neatly into its mental model. Generate tests for this class. Add this feature to the API. Refactor this module. But when I tried to use it for exploratory work, for decisions that required me to validate assumptions about system behavior, or for problems where the right answer was genuinely ambiguous, it would confidently charge forward and write code that required my full attention to debug. It wasn’t exactly wrong. It just operated at a lower resolution than my thinking required.
Cursor: The Integrated Alternative That Actually Ships
Cursor arrived with a different philosophy. It’s not trying to be VS Code with a plugin. It’s a purpose-built IDE that treats AI assistance as the fundamental organizing principle of the editor, not a feature bolted on afterward. The Composer mode does something conceptually similar to Agent Mode, but with a crucial difference: it uses local embeddings for codebase indexing rather than hitting GitHub’s remote graph. That means faster queries on large codebases, fewer API round-trips, and a different tradeoff profile on privacy and latency.
What I noticed immediately was that Cursor feels less like a powerful autocomplete and more like an actual collaborator. The Composer interface lets you describe multi-file refactorings, and Cursor walks through the changes with you before applying them. You see the diffs. You can push back. You can say “no, that’s not quite right, here’s what I meant.” It’s collaborative in a way that Agent Mode, despite being more autonomous, isn’t. There’s something genuinely satisfying about working with a tool that invites you to shape its thinking rather than just watching it execute.
That $2.5 billion Series B valuation wasn’t just venture hype. I watched Cursor handle a three-file refactoring on a legacy service that would have taken me an hour to think through and debug. It took Cursor roughly five minutes of back-and-forth conversation. That’s not hyperbole. That actually happened, and I’m still thinking about what that represents across a full year of development work.
The Numbers Worth Knowing
GitHub has been transparent about scale. Copilot had surpassed 1.8 million paid subscribers by early 2025 and was generating over $100 million in annual recurring revenue, making it one of Microsoft’s fastest-growing developer products. Most developer tools plateau at user counts that would be disappointing for a consumer app. That many paid seats suggests teams have already decided the investment pays for itself.
The shift from 44% in 2023 to 76% in 2025 according to the Stack Overflow Developer Survey is the kind of adoption curve that usually precedes a fundamental reshaping of how work gets done. It’s not early adopters anymore. It’s not even early majority. This is becoming table stakes in the same way version control became non-negotiable after GitHub and Git proved their value.
The Honest Assessment: Which One Should You Actually Use
If you’re already deep in the GitHub ecosystem, already paying for Copilot, and already comfortable in VS Code, Agent Mode is a genuine productivity multiplier. It’s not going to replace your thinking, but it will eliminate categories of busywork that have accumulated around the edges of development. You can check out the GitHub Copilot agent mode documentation to get started, and I’d specifically recommend testing it on test generation first. That’s where I saw the most consistent value.
If you’re willing to migrate your environment and you work on large codebases where local indexing makes a real difference, Cursor is hard to dismiss. The privacy model is cleaner for teams with compliance requirements. The UX for multi-file changes feels more thoughtful. The integration with your actual development workflow is tighter because the entire editor was designed around AI assistance from the start. You’ll probably switch back and forth a few times before deciding, and that’s fine. Both tools are good enough that the differences come down to preference and architecture.
The real story is that the 90-day experiment changed how I think about what a development tool can be. These aren’t replacements for expertise. They’re not going to make good engineers out of people who aren’t willing to think deeply about problems. But they do represent a genuine shift in velocity for experienced engineers who know how to direct them. Both tools are well-funded, adoption is accelerating, and the underlying assumption of the entire category, that AI assistance belongs at the center of your workflow rather than the periphery, seems like it’s settled now.
What’s your experience been with these tools? Have you found workflows where one clearly outperforms the other? Drop a note in the comments or find me on your platform of choice. I’m genuinely curious what patterns other senior engineers are seeing in their own experiments.