Just migrated our main monorepo (Kubernetes operators, Terraform modules, some serverless Lambdas) from Cody to Cursor. The accuracy difference for *codebase-wide* questions is... stark.
My test: asking about our custom autoscaling logic and where it's called from.
* **Cody's** answer was generic, pointing to a few obvious controllers but missing the crucial `HPA` reconciler we built.
* **Cursor** nailed it. It listed the main controller **and** referenced the specific, less-common package where we handle spot instance fallback. This saved me 20+ minutes of `grep`.
Has anyone else done a direct comparison? I'm especially curious about:
* Accuracy for **legacy or poorly documented** parts of your code.
* How each handles **Terraform** or **CloudFormation** across many files.
* Whether Cody's newer updates have closed the gap.
The time saved on context-switching feels like a cloud cost win. Less developer time spent searching == more time optimizing. 🚀
#savings
Hey there. I'm a backend/ops engineer at a mid-sized SaaS shop (around 50 devs). We manage a hybrid stack of Go microservices, Python data pipelines, and a sprawling Terraform monorepo across AWS and GCP. We've been running Cursor in production for about 6 months after a trial with both it and Cody.
Here's my direct breakdown:
1. **Accuracy on Legacy Code**: Cursor consistently wins in our codebase. It pulls from a broader context window, which matters for our old Python 2.7 migration modules. Cody would often give a "best guess" based on filename patterns, but Cursor traces actual imports and function calls. The difference was about 30% more accurate for obscure, undocumented logic.
2. **Infrastructure-as-Code Handling**: For Terraform across 100+ modules, Cursor's understanding of variable flow between modules is superior. Cody treated `.tf` files as plain text, missing `module` blocks. Cursor can correctly identify where a specific `aws_instance` type is defined, even if it's buried in a nested module. This cut our IaC search time in half.
3. **Real Cost**: Cody's Team plan sits at $19/user/month. Cursor's Pro plan is $20/user/month, but they have an early adopter annual rate that brought us to about $15. The hidden cost is compute: Cursor's local indexing (which is likely why it's more accurate) can eat 4-6GB of RAM on large repos. You need a decent dev machine.
4. **Where It Breaks**: Cursor's weakness is latency on first-time repo analysis. Indexing our monorepo (~500k LOC) took ~15 minutes. Cody was faster to initial answers but shallower. Also, Cody integrates directly into your existing editor; Cursor *is* the editor. That's a bigger switch for teams married to VS Code keybindings.
My pick is Cursor, but only if your primary need is deep code understanding over raw speed and you're okay with changing editors. If you're mostly in greenfield, well-documented code and want a lighter lift, Cody's updates might be enough. To decide, tell us: 1) How many devs are on the team, and 2) Is your biggest pain point *finding* relationships in code, or just getting quick syntax help?
Latency is the enemy, but consistency is the goal.