Windsurf Enterprise FedRAMP

I used Windsurf  for about three months. Once our Cursor  license expired, we were given Windsurf  to use.

I used Windsurf to generate test cases and update my test cases in Jira . I made an MCP connection with Windsurf and Atlassian Jira  so that I could make test cases there, update them, and update the statuses. My second use case was to execute those test cases by using Playwright MCP and browser execution. My third use case was to write the automation of those test cases from Windsurf.

The process was smooth. I would copy-paste my test case into the chat option and tell Windsurf to write the automated test case for it. I would also give Windsurf the XPath, the browser name, and the credentials. I would write the detailed steps for my test case and Windsurf would write the test cases very smoothly.

I am using Windsurf for these three use cases: making the test case, automating them, and executing them.

Windsurf is very similar to Cursor . The feature I admired the most was its integrating capabilities. It can be integrated with Playwright MCP and Atlassian MCP very easily. The user interface was smooth and I really appreciate the types of themes they provided. There was also auto-complete functionality in Windsurf which helped me a lot. Windsurf gave a concise conclusion of what it did, the steps it took, and the conclusion of it. Instead of reading all the chat, I could rely on the conclusion part which is small, crisp, and very nice.

The auto-complete functionality helped me complete sentences automatically. It gets the instinct of what I am going to write and does that in a very smooth manner. A lot of times Windsurf hallucinates and completes it in a wrong way, but overall I like this functionality. In about 70% of the cases, it thinks the right thing that I was also thinking.

We were able to complete our deadlines and meet them before the scheduled time. If a project was for 15 days, we could complete the same project in 10 days by using Windsurf to automate the test cases, execute them, and make those test cases. Meeting the deadlines became really easy. It also automated a lot of our manual tasks.

Windsurf helps me fix flaky cases very easily. I would run my test case and it would start executing. Whenever there was an issue or the test case was failing, it would identify that place and Windsurf would fix it on its own.

Windsurf can be improved by increasing the context awareness. It sometimes loses context across files. If it had better repo-wide understanding and smarter navigation across test suites, APIs, and services, that would be great. Debugging  and failure analysis is another area for improvement. Windsurf helped in writing the code but debugging is still a weak point. Stability is also something that should be improved. Most AI tools hallucinate and Windsurf also hallucinates. When it is given a larger amount of data, it hallucinates a lot and gives syntactically correct but logically wrong code sometimes.

I have been working here for the last 3.5 years in the same field of testing.

Windsurf is quite stable, but it is a little slower than Cursor.

Currently, one license is given to three users and we use those licenses very much. I haven't seen it slowing. Windsurf runs at its own pace, but we haven't tested it in a scalable manner. I haven't tested what would happen if one license were given to nine people. With one license for three people, it was going smooth.

I haven't had a chance to talk to customer support because I haven't had any sort of issue using Windsurf.

Previously, we were using Cursor but it was really costly, so our team moved to Windsurf.

Time saved is very evident. Because time has been saved, if I am completing a task in five days rather than ten days, I can pick another task in the remaining five days. The product team can now delve into many more features based on the feature flags and test them a lot. Previously, we would test one feature. Now, we can also experiment. For one feature we can have two builds and test them on the same timeline. This helps us choose better.

I wasn't given the opportunity to choose because these things were just given to us by my managers. I was not given a chance to explore other options.

I want to tell people that they should start using an AI-assisted IDE , whether it is Windsurf or Cursor. Windsurf is better because the price difference is really huge. Windsurf always provides a boilerplate for writing the code and test cases. As testers and automation testers, we can refrain from doing repetitive work. If one is really good with prompts, then they can have really good results. Prompts should be explicit and provide clear context around the use case. Always review your test cases and automation scripts before merging them because a review is a non-negotiable thing in AI tools. I would rate this review a 7 out of 10.

I have been using Windsurf  for a few months now, mainly as part of my development and productivity workflow. During this time, I explored its capabilities for code assistance, faster debugging, and improving overall development efficiency. It has been particularly useful in speeding up routine tasks and helping me to focus on problem-solving rather than repetitive coding.

Our main use case for Windsurf  is to make code changes and we are mainly focusing on development and productivity enhancement. We also use it to speed up coding, debugging, and understanding complex codebases, especially when working across multiple tools and systems. In my day-to-day work, I rely on Windsurf to generate code snippets, troubleshoot issues, and explain existing code logic.

Our main focus is generating code snippets, troubleshooting issues, and creating code logic. When dealing with errors or unfamiliar implementation, it helps quickly identify solutions and suggest improvements. This significantly reduced the time spent on debugging and research, allowing us to focus more on building optimization and workflows.

The best features in my experience include AI-driven code generation, which does not just autocomplete lines but understands the intent and can generate full functions and logic based on the context. Another standout feature is Cascade, an AI agent workflow tool. This allows the tool to handle multi-step tasks such as writing code, modifying files, and even running commands, almost like a junior developer assistant. I also find its deep codebase understanding and local indexing very powerful. It can analyze the entire project and give context-aware suggestions. Additionally, inline AI editing, built-in terminal support, and memory system make workflows smoother.

The feature I use the most is deep codebase understanding combined with AI code generation. It is incredibly helpful when working on existing projects or unfamiliar code because it can quickly understand the context and suggest accurate changes or additions. This saves a lot of time that would otherwise go into reading and figuring out the code manually. I also frequently use the code generation for writing functions, fixing bugs, or speeding up repetitive tasks. It helps me move faster without compromising quality. While Cascade is powerful, I use it more selectively for multi-step tasks.

One small but really valuable aspect I appreciate is how seamlessly it fits into the development workflow. It does not feel like a separate tool. I can interact with AI directly inside the editor without breaking my flow, which keeps productivity high. Another nice detail is its context memory. It remembers what I was working on and gives more relevant suggestions over time, so I do not have to repeat myself or re-explain things constantly. Additionally, the inline editing and quick fixes are very smooth. Instead of jumping between tools or rewriting code manually, I can apply changes instantly, which makes day-to-day development much faster and less disruptive.

The bigger improvement is faster development and debugging. Tasks that used to take hours, such as unfamiliar code or fixing issues, can now be done much quicker with AI assistance. We have also seen better efficiency and reduced repetitive work. Developers spend less time on boilerplate code and routine tasks and more time on solving real problems and improving systems. Another impact is faster onboarding. New team members can understand the codebase more easily with AI explanations.

We have seen around 30 to 40% reduction in development time for routine tasks such as writing boilerplate, debugging, and understanding existing code. Tasks that used to take hours can usually be done in minutes. We have also noticed a 20 to 30% decrease in debugging time since the AI helps quickly identify issues and suggest fixes, reducing trial and error efforts. Overall developer efficiency has improved by 25 to 35% as less time is spent on repetitive work and more on actual problem-solving. Additionally, new developers can become productive much faster, around 30% quicker, by using it to understand the codebase.

Overall, Windsurf is a powerful tool, but one key area is the accuracy and consistency of suggestions. While it is very helpful, sometimes the generated code or fixes need manual validation, especially for complex or production-level logic. Another improvement would be better control over AI actions, especially in agent workflows like Cascade. More transparency and fine-grained control would help developers trust and use it more confidently in critical tasks. Performance can be improved slightly.

One area for improvement is around context limits and memory handling. Sometimes when working on very large codebases or long sessions, the context can feel limited. Improving how it retains and prioritizes context would make suggestions even more accurate. Another area is documentation and onboarding guidance. Since Windsurf is a relatively new tool, having more structured documentation, best practices, and real-world examples would help teams adopt it faster. Additionally, enterprise-level controls could be enhanced, such as better security, audit logs, and usage tracking.

One additional area for improvement is offline and limited connectivity support. Since Windsurf relies heavily on AI capabilities, having a more robust fallback or partial offline functionality would be useful in restricted environments. Another point is the customization of AI behavior. It would be great to have more control over how the AI responds, such as tuning it for specific coding standards, project styles, or team preferences. Additionally, integration with more developer tools and ecosystems could be expanded. While it already fits well into the workflow, deeper integrations with CI/CD pipelines, issue tracking, and monitoring tools would make it more powerful.

I have been working for the past two years in my current field.

Windsurf is stable.

Scalability is very good. As of now, we have a team of 50 developers where we provided Windsurf to all of the teams and they are using it very well. When it comes to scalability, it is very easy for the integration as well. Windsurf is scaling very nicely.

Customer support is very good. Whenever we have any query, we can raise a simple ticket and the following up is very nice.

Onboarding is quick and straightforward.

We are using GCP.

From a practical standpoint, the biggest ROI comes from time savings and faster delivery. We have seen around 30 to 40% improvement in developer productivity, which directly translates into quick feature releases and reduced development cycles. This aligns with industry insights showing AI coding agents significantly improve speed and efficiency. We have also reduced development cycle time by 20 to 25% and increased throughput by 12%. The developer time saved with AI assistance handling repetitive tasks is also notable. The ROI is visible through faster feature delivery, reduced manual effort, improved developer productivity, and better utilization of the engineering team.

The pricing is fair and flexible. It offers a free tier which is great for getting started and testing the tool without any upfront cost. The Pro plan is around 15 dollars per month which includes access to premium models. It is very minimal since it is a cloud-based tool and does not require any infrastructure or heavy installation.

Overall, Windsurf is a very good tool for engineering productivity and coding sessions. It also enhances the time productivity of the SRE as well. Windsurf is a very good tool to work with.

It is a powerful tool for handling repetitive tasks so that the engineer can focus more on high-value work such as system design and optimization. Tools such as Windsurf even provide analytics to track time savings and productivity improvements across the team. Making Windsurf a part of your team is a good investment. I gave this review a rating of 8 out of 10.

My main use case for Windsurf  is to write code and to optimize the code in my day-to-day tasks.

I worked with a database like SQLite  on the mobile app side, where I had many queries. I wrote one query for selecting data from one table and I used Windsurf  to optimize that. After that, Windsurf suggested optimizations for all the queries, and when I type a method name, it suggests everything inside that. I used it that way to accept the changes from Windsurf.

The best features that Windsurf offers, in my opinion, include optimizing the code, and I can also use it for documentation, in the sense that it explains the code.

When I mention documentation, I am talking about Windsurf's ability to help understand the code, rather than automatic documentation generation.

Windsurf has helped me a lot by reducing the development time. By using Windsurf, I have reduced my time by 30% to 40%.

I do not have anything to suggest for improving Windsurf at this time.

I have been using Windsurf for about two years, as I started working with Windsurf two years ago when it was Codium.

I rate Windsurf a perfect 10 because I used it extensively when I was working on a task, and I completed it before the deadline, earning some recognition from my organization.

Currently, I am using Windsurf in my VS Code. I did not purchase Windsurf; I just added the extension in VS Code.

I recommend that you check Windsurf based on your requirement to see if it is useful for your needs. My overall rating for this product is 10 out of 10.

My main use case for Windsurf  is creating scripts that move data from Python scripts to transfer data from Teradata  to Snowflake . I also used it for automating all the data loading processes, which pull data from the landing area of the data warehouse and push it to the integration layer. From there, it schedules an email to create a report from those integrated data, creates a view on a different semantic layer, and generates a chart—either a pie chart or bar chart report—to send to required stakeholders.

I have two other cases with Windsurf . The first one is an AI chatbot that we are in the process of building with the help of Windsurf. Basically, that will connect to Tableau.

The best feature Windsurf offers is the ability to plan the job or task first and then create an executable model. This gives us a clear picture of what I am going to do, what I will receive, what the outcome will be, and how it can benefit the end user.

The planning and executable model feature helps my team day to day by saving a lot of rework. Most of the time when you ask a particular question to Windsurf, you miss bits and pieces of where to begin and what to end, and what to skip and what to add. However, during the planning phase, you can collaborate with Windsurf to make your plan accurate. When execution happens, you get the desired result without going through the rework of returning to planning after getting the result. It breaks that chain. If your planning is perfect, execution does not need a lot of rework.

Windsurf has positively impacted my organization by helping us achieve at least ten to twenty percent improvement for each individual working in the data warehouse to use Windsurf instead of looking for help from any other team. For example, if a business stakeholder wants to get data about any report or any updates about any report, instead of asking a resource for an update, a business user can ask Windsurf to look into the tables and provide the report. This reduces the dependency on the front-end reporting team.

Windsurf can improve by making sure to ask the user if they are talking about the same context where the request started. Request number one might be related to creating a report, and request number two might be related to writing an email. Usually, Windsurf mixes those two requests because it does not ask the user if they are talking about the email or the first request. Windsurf takes it by default that both requests are related and continues. This sometimes creates rework.

I have been using Windsurf since one and a half years ago.

Windsurf is stable.

Windsurf's scalability is quite good. I think we went from a few hundred users to maybe four to five hundred users in our organization. There was no glitch or any issues while scaling across two different time zones and two different organizations.

I do not have any insight on customer support. However, whenever licensing is required, we always got a quick response from them. I am not directly involved in the communication with Windsurf support.

We have not used any other solution before now. Windsurf is our first starting point for AI.

At this point, I am not in a position to share the metric on return of investment. However, I can tell you right now the return of investment is mostly based on time and some part of money saved. At the employee level, we have not yet reached the point where we can purely say that we have actually gotten returns from Windsurf instead of an employee.

I do not have a clear understanding of how Windsurf pricing is set up in my organization. I am not part of the committee which took care of licensing across the organization. Right now, I think Windsurf is costing our organization differently than it started. We initially went with a bulk buy where the entire organization was available to use. Now it is ADFS login related, so every user can see their own number of ACUs, hours used, resources used, or credits used by Windsurf.

I am not in a position to give this answer because I am not a leader who decided on Windsurf. There might be a team which went through many other tools and compared them with Windsurf. That was my organization's management decision.

I give Windsurf a nine out of ten because you get automation done by Windsurf all the time. Not only automation, but whether writing an email, writing a document, or creating detailed information, it gives you detailed insights. I deducted one point because of the rework and training that needs to be provided to the Windsurf agent to make sure it is useful for your job. I feel a nine is already a very high number.

I can advise that Windsurf has almost all the available agents, starting from Claude or any other AI tool or AI LLM model being used. We have the highest level of agent to the lowest level of agent which can help you in day to day activity, whether writing an email, looking into PDF files, looking into an Excel sheet, or creating a Python script. Windsurf has a vast variety of AI models available, and that gives a lot of flexibility and cost savings.

My overall rating for Windsurf is nine out of ten.

My main use case for Windsurf  is coding, unit test case creations, and debugging for front-end Angular. For debugging in Angular, if I need to check the code with issues, template issues, or any lint issues, I can ask Windsurf  to check the specific file or related things, and it analyzes and provides me the solution. For unit test cases, I will ask Windsurf to create that test case for a specific file or function.

I find that Windsurf is a good tool to use, as it automates many things in coding, development, and analysis. Windsurf offers features such as auto suggestions. When comparing Windsurf's auto-suggestions to other tools I've tried, I notice that a few suggest irrelevant content or don't match the syntax, while Windsurf analyzes the code and provides suggestions that match the code or functionality accurately.

Windsurf is a good tool that everyone can use, as it has many features that reduce the time required for coding. Windsurf positively impacts my organization by reducing the efforts required to depend on more critical technologies, as it provides everything within itself and offers many latest technologies. Both time and productivity are saved by using Windsurf, making it a recommended tool.

Windsurf can improve its analytical solutions and inbuilt features, as I currently have a dependency on external third-party tools that could be introduced into Windsurf itself to reduce that time or dependency. The only improvement needed for Windsurf is to reduce dependency on third-party tools.

I have used the solution for around ten months.

Windsurf is almost stable.

Windsurf's scalability is almost good.

I hear that Windsurf's customer support is good, but I haven't reached out to customer support since I haven't faced many issues.

Before Windsurf, I used GitHub  Copilot as another solution.

I see a return on investment with Windsurf, as it reduces effort and allows for a decrease in the number of developers needed.

The pricing, setup cost, and licensing for Windsurf depend on the customer only and are not specific to developers, as this is decided by management and upper teams.

I evaluated other options such as GitHub  Copilot before choosing Windsurf.

Windsurf is already in development and is almost fully developed, and it keeps improving. For those looking into using Windsurf, I advise them to understand all the features that can be utilized in Windsurf, which reduces their effort and time. Everything is good with this interview, and all questions are relevant to the feedback. I would rate this review experience a 9 out of 10.