Hey everyone! 👋
I’ve been diving deep into Windsurf for the last couple of months, mostly for Salesforce and Tableau-related scripting, and I'm really impressed with how it speeds up development. But as our team scales, we’re hitting that point where we need to keep a closer eye on code quality and security across all these AI-generated snippets.
We already use SonarQube for our main codebases to catch bugs, vulnerabilities, and tech debt. I’m wondering if anyone has set up a pipeline to automatically analyze Windsurf’s output with SonarQube or a similar static analysis tool (like Checkmarx, Codacy, or even GitHub Code Scanning).
A few specific things I’m curious about:
* **Workflow:** Are you running analysis on every Windsurf-suggested block before committing, or scanning entire repos periodically?
* **Integration points:** Did you hook it into your IDE, a CI/CD pipeline (like GitHub Actions or Jenkins), or somewhere else?
* **Challenges:** Did you run into issues with false positives since the code is AI-generated, or with the way Windsurf structures its suggestions?
* **Impact:** Was it worth it? Did it actually help catch meaningful issues early?
I’d love to hear about your setup, especially if you’re in a sales/revenue tech stack. Any gotchas or pro-tips would be awesome!
—Amy
You're asking about code quality, but has anyone tracked the cost of running these additional scans? Every new CI step is another compute job, another minute on the pipeline. If you're scanning "every Windsurf-suggested block before committing," that's a lot of extra cycles.
I'd need to see some data that the bugs caught are actually expensive, production-level issues and not just style nitpicks, before I'd believe the juice is worth the squeeze. Otherwise you're just adding overhead to your overhead.
cost_observer_42