My main use case for Windsurf is utilizing its standard feature, Cascade, which understands our repository structure very well and is genius in understanding and tracing dependencies across all the files we are using. It helps in modifying multiple files together, explains why something is broken, and how to fix bugs while also carrying context along long coding sessions. For instance, with JWT authentication in this FastAPI app, it updates the front login flow, inspects back-end routes, creates middleware, updates environment configs, modifies React components, and is useful in patching API calls across the projects.
In addition to my main use case with Windsurf, something unique I have noticed compared to other tools is how it can chain tasks together, such as analyze, plan, edit, test, and refactor, while maintaining intent memory across steps. This makes it feel closer to an AI teammate than a chatbot. It also respects naming conventions, existing abstractions, and follows our repository patterns to avoid random styling mutations. Compared to the previous Cursor, Windsurf behaves as an agentic workflow-focused engineering assistant.
The best features Windsurf offers, in my opinion, include ID galaxy, its understanding of the whole mission feature, Cascade, multi-file editing, repository-wide context awareness, terminal understanding, persistent workload memory, and step-by-step execution. All of these are very helpful in tracing how our project uses notifications, inspecting joins, following ETL lineage, comparing schemas, identifying merge conditions, detecting inconsistent primary keys, and suggesting refactors across multiple modules. Windsurf uniquely combines the functionality of AI coding tools that often resemble an IDE plus a chatbot into one continuous stream.
Persistent workload memory in Windsurf significantly helps my workflow by reducing the repetitive reteaching of folder structures, naming conventions, business rules, APIs, database patterns, and edge cases. It allows Windsurf to gradually learn about our repo structure, engineering patterns, ongoing tasks, and recent edits, making it a powerful tool in enterprise projects as it generates code faster and reduces cognitive reload time.
One small yet impactful feature of Windsurf that I want to highlight is how it handles large refactors, such as renaming domain projects, restructuring services, changing authentication flows, migrating SQL models, and converting Oracle SQL to Spark. Windsurf allows us to continue and finish series handling logic without re-explaining everything and makes debugging easier as it remembers previous errors, failed fixes, and environment issues.
Running the workflow with Windsurf has definitely saved our time, as it easily understands our prompts and logic, reducing engineering friction and saving time on repetitive tasks such as refactoring, debugging, documentation, test generation, and context switching. With its repo awareness and persistent context, it significantly compresses the rediscovery cycle, resulting in faster onboarding, quicker PR turnaround, and fewer delays.
We follow the Agile methodology, and we have observed that typical environment improvements using Windsurf are 30 to 60% faster, with a 20 to 40% reduction in debugging issue times and over 50% faster documentation test integrations. We have also experienced saving days or weeks for new developer onboarding, and we save approximately 5 to 10 engineering hours per developer per week.
In terms of improvement, I believe Windsurf could enhance features for generating PPTs and documentation to be clearer and more understandable, including visuals.
I have been using Windsurf for almost six months.
Windsurf has positively impacted my organization by running our workflow more efficiently.
My advice to teams evaluating Windsurf is to expect magic but to avoid over-trusting its outputs initially, as it is only for tiny code suggestions. However, teams can benefit significantly from workflow acceleration, repo navigations, debugging, and refactoring, particularly in high-friction areas such as legacy refactoring, ETL transformations, API scaffolding, documentation, and test creation.
I rate this product an 8 out of 10.