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I am a software developer with over two years of experience. I have been using Windsurf  for approximately one to one and a half years since its introduction into my organization. I primarily work in enterprise application development and use Windsurf  on a daily basis as my AI-assisted IDE  to improve my development productivity and reduce the time required to understand large codebases.

Windsurf has been in use at my organization for one to one and a half years. Previously, we used GitHub  Copilot as our AI assistant, but given the features that Windsurf brings to the table, my organization shifted to Windsurf, and I have much to share regarding its features and how it has made my life easier as a developer.

Windsurf is available as a separate IDE  and also comes as a plugin. Developers use IDEs such as IntelliJ, and we can use it as a plugin there, but it is recommended to use Windsurf IDE itself, which provides many features. Understanding large codebases was a big time saver for me. Instead of opening forty Java classes, fifteen Angular files, and configuration files and APIs, I simply ask Windsurf to explain a module, how a request flows, or which classes are involved. It understands the relationship between files and explains the architecture.

Another feature I use on a daily basis is Cascade chat, which has two modes: Ask mode and write mode. I use the write mode seventy percent of the time because I can ask it to explain an implementation and also implement it side by side.

A favorite feature I find in Windsurf that is not present in other tools is Code Maps. As a developer, I sometimes need to understand the whole architecture and determine where to fit in a new feature or fix existing bugs. Understanding the architecture usually takes considerable time, but this feature allows me to visualize the current architecture of a very large codebase visually. When I click on the architecture, it takes me to the particular code where it is written. I can relate the architecture and the code side by side and understand the whole picture. This is one of my most favorite features because previously, I needed to rush through code in every file to understand what was happening behind the scenes. The overall architecture and that link with the code is a huge boost for developers.

Windsurf also has rules, which allow me to guide how AI generates responses. For example, if my organization follows a particular set of rules, I do not have to write them every time in the prompt. If we use Java seventeen and follow Spring Boot  conventions, naming conventions, and should not use deprecated APIs, all of these repeating items can instead be written as rules inside Windsurf, and it will automatically take them into account in every response.

Similar to rules, there is another feature called skills, which allows me to use reusable prompts or workflows. For example, if there is a testing skill that generates test cases or edge cases using the Mockito framework, or a documentation skill that generates documentation or explains an API using something like Swagger, I can summarize a module. Instead of typing everything, skills make development much faster by allowing me to reuse prompts. Workflows is the bigger version, the superset of both these things. It helps me combine multiple AI actions together. For example, starting from requirement gathering and understanding, designing, coding, and then pushing to GitLab  or GitHub , I can follow these procedures and later push to a specific branch. Rather than doing this every time, I can write these workflows separately and simply call them out in Windsurf. These are very specific features that Windsurf offers that I did not find in other AI tools such as GitHub Copilot.

Room for improvement is actually associated with every AI that exists. One thing is that if there is a very large codebase, such as a legacy codebase, sometimes the context window is a hindrance. There is a particular context window for every model, and for Windsurf in particular, if it is a very large legacy codebase, then you might have to pull in all of that code and only then maybe you will get the whole context. For very large projects, getting the context together intact is one thing that needs improvement.

Another thing that I feel needs to be improved is hallucination. Whenever the context is not set, AI occasionally needs validation. It is always recommended that human reviews are also required when Windsurf generates code. You need to review it always. Performance with large indexing operations or when using very large models and efficient models such as Claude Opus  takes a lot of time. There is nothing much that can be done about it as it is all about the model, but sometimes large indexing operations do take time.

One more improvement that I feel is about documentation. There are a few other features I have not mentioned so far. There is one more feature called MCP, which is Model Context  Protocol, present inside Windsurf. Instead of just chatting and asking it to generate code, I can use MCP to integrate it with external tools, whether it is Splunk, Veracode , or SonarQube . I can integrate it with all the external tools as well as internal tools and documentation, and it will do the work for me. It is not just that it will search in public and get details, which sometimes may hallucinate. MCP is one thing, and for advanced features such as MCP and workflows, sometimes I feel that documentation is not in detail. Windsurf could have better documentation for MCPs and workflows, and there are other niche and specific features that are present only in Windsurf.

I have been using Windsurf for one to one and a half years.

Stability is quite good. Only when the network is off or very rarely, Windsurf is almost 99.999 percent available and stable. I have no issues with that.

Windsurf works well for small projects, medium projects, and large enterprise repositories. The value actually increases as the project complexity grows. Features such as Code Maps prove to be of great value when project complexity increases, allowing me to make use of the features that Windsurf provides.

I have not had the need to contact customer service in my experience because the onboarding was smooth and the details and features that Windsurf provides are all good. We did not have any technical issues so far. Sometimes if there are any hiccups or if Windsurf does not respond, I simply quit it and restart my system, then start working again.

We had GitHub Copilot earlier, which we were using as our AI assistant.

The onboarding to Windsurf was easy because we had an internal document explaining how to onboard it into my organization. It was just adding a plugin to IntelliJ IDE and then downloading Windsurf from our own self-service portal. Once we downloaded it, we just had to set the proxy and we were all set and ready to go.

From the developer's end, maintenance involves the token allocation. There is a specific amount of tokens allotted to every developer monthly. I just have to make sure that the models I use in Windsurf, I do not keep using high-value and high-performance models every time so that I do not consume all tokens and be left with no credits. This is the only thing that developers have to take care of, but the maintenance is actually taken care of by the platform and the management.

Regarding pricing, I am a developer, and the pricing is handled by my management team and the platform team. As a developer, I was mainly focused on using the product rather than the procurement side.

I have also worked with SonarQube , and if that is an active product, I can provide a review for that as well. I have also been using Microsoft Teams  very frequently.

A favorite feature I find in Windsurf that is not present in other tools is Code Maps. The onboarding to Windsurf was easy because we had an internal document explaining how to onboard it into my organization. From the developer's end, maintenance involves the token allocation, and there is a specific amount of tokens allotted to every developer monthly. Windsurf works well for small projects, medium projects, and large enterprise repositories. Room for improvement is associated with every AI that exists. My overall review rating for Windsurf is nine out of ten.

Our main use case for Windsurf  is accelerating the development for all the client projects that we handle, especially when we are building websites, AI agents, and automations.

For example, when we need to create a landing page or a workflow for a client, we use Windsurf  to quickly generate and refine the code, test ideas faster, and then reduce the time spent on repetitive development tasks.

We majorly use Windsurf to speed up the coding for client work and especially for all the websites that we design day in and day out. For the AI agents and automation projects, we use it extensively.

Windsurf has positively impacted our organization by helping us work faster and more efficiently.

Since we started using it, we have been able to move from an idea to implementation more quickly, reduce the repetitive coding, and spend more time on higher-value work such as refining client solutions and testing different approaches.

This has helped our small team stay productive across multiple projects.

The main improvement has been time savings, and we can move faster on websites, automations, and AI agent workflows so that we can take on more work and spend less time on repetitive development.

In terms of metrics, we are an eight-person team, and we were earlier handling a couple of projects because we had to do a lot of coding from scratch.

Now that Windsurf is in place, we are able to handle 14 different projects.

The prototyping has been remarkably quick.

When it comes to time-saving, it has saved a significant amount of time for us, and the initial effort has been substantially reduced.

The best features Windsurf offers for us are the fast code generation and intelligent suggestions.

They help us build faster, reduce repetitive work, and keep momentum.

The code it generates is of high quality.

With fast code generation and intelligent suggestions, I find the suggestions generally accurate enough to be useful and the code it generates usually gets us most of the way there.

We still refine it, but it reduces a lot of time and a lot of initial effort that we had to do previously.

What I appreciate the most about the features is that it keeps us moving.

For agency work, where we juggle multiple projects, that smooth workflow is really valuable because it reduces context switching and helps us stay productive.

The main improvements I would suggest for Windsurf are stronger context handling for bigger projects and a bit more control over the code it generates.

This would make it even smoother and faster for our agency work.

I would also appreciate a cleaner UI for larger projects, especially when there are many files and moving parts.

That would be a valuable addition.

Better integrations with our existing tools would help too, so we can move between coding, testing, and deployment more smoothly.

Overall, these improvements would make it even better for agency-style work where speed and clarity matter the most.

Regarding Windsurf's AI capabilities, it seems solid for general use, but because we work on client projects, we stay cautious with sensitive information.

More visibility into security controls, permissions, and data handling would make it even better for us.

It is adequate for our current needs, but stronger governance controls and clearer security options would be beneficial.

Beyond what we have discussed, a small improvement would be more consistency in the output on complex prompts and better context retention across longer tasks.

I have been using Windsurf for about 15 months now, mainly for development and AI-related workflows.

Windsurf has been stable for our agency work overall, with no major reliability issues.

In our experience, Windsurf has been scalable for day-to-day use cases and larger tasks.

It should support growth reasonably well, though performance and consistency would need to be monitored as usage increases.

It has scaled well for our current needs and appears suitable for large projects as well, with some attention needed as usage grows.

We have not needed to reach out to support very often, but when we did, the experience was generally positive and responsive.

We did use other tools before Windsurf, but we switched because Windsurf fit our workflow better and felt more efficient for day-to-day use cases.

The onboarding process was smooth overall.

New team members usually became very comfortable with Windsurf very quickly, and we only needed a brief introduction to get them started.

Windsurf integrated reasonably well with our existing tools and workflows.

It fit into our development process without much disruption, and we were able to use it alongside our normal setup.

It has improved collaboration by making work more consistent and reducing back and forth during the development.

We have seen a lot of positive return on investment, mainly through the time savings and improved productivity.

Earlier we were handling two projects, but now we can handle 14 projects.

It helped us reduce a lot of manual effort and speed up the development and support of multiple projects.

It reduced the initial effort, improved our productivity, and helped us save a significant amount of time.

In our case, Windsurf's pricing and licensing were reasonable and straightforward to work with, so we did not face any major setup complexity and the process was smooth from a procurement standpoint.

We evaluated other tools as part of the selection process, but Windsurf gave us the best balance of usability, integration, and productivity.

We went with Windsurf because of these advantages.

My advice would be to start with a small pilot project first so that the team can get comfortable with the workflow before rolling it out more broadly.

It is also worth setting clear guidelines on when to use it and having someone review outputs for more complex tasks.

Start small, define usage guidelines, and review outputs clearly at the beginning and you will see significant improvements.

I would rate this review 8 out of 10.

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.

I use Windsurf mainly to code projects that take less time to build based on prompting alone, which is similar to whiteboard coding.

I would not call it prototyping; I would call it complete end-to-end projects that I have built with Windsurf. For example, in my current work job, I built a delivery automation platform in Node.js using Windsurf. This involved integrating a Telegram bot into a Windsurf project to create a bot where delivery personnel can retrieve their daily delivery list. Everything was coded in Node.js with the help of Windsurf AI. For this project, I used the Claude Opus  2.7 model that Windsurf provides. It was quite quick for me to build this complete end-to-end solution and deploy it.

The time consumption has reduced drastically. If I had to build any project that would take at least a month or so with the required effort, I think it has been reduced to approximately a week, and the effort has also been reduced drastically.

As I explained, the delivery automation project that I am currently building would have taken easily at least 1.5 months minimum, considering I also had to deploy it. Now it only took me at most two weeks to build this from scratch, test it, and deploy it. Time consumption has truly been the most useful benefit.

In terms of cost savings, if I am building projects, it is saving more time, and I can utilize that extra time to build something else that is more important to the company. I would not say it is particularly about cost. The quality has obviously improved. Even though I come from a technical background, I think with the new models that Windsurf is providing access to, such as the latest ones from Claude or OpenAI models, their output and efficiency is much better than a person coding it. The quality is also better.

The thing I appreciated about Windsurf is the free AI model called Cascade, and it also provides SWE 1.5. Both of these, especially SWE 1.5, are very good at coding. Initially when I was in my college days, I did not have to jump onto the paid plan to build projects. Instead, I could use it with the SWE 1.5 model and build my blockchain projects for my college coursework. It was also quite quick. To elaborate, I was interning as well as studying in college. In that small amount of time that I had to quickly code and build this entire blockchain project for my coursework, I had to depend on Windsurf AI, for which I am very grateful, especially for SWE 1.5. Since I was still in college, I did not have to jump into the paid plan, and the free plan that included the SWE model worked out very well for me.

The best features Windsurf offers include the ability to handle prompts very maturely, as if I am explaining it to an engineer, so the model's understanding capabilities are very high. I would say even the free models that provide the SWE model are superb with understanding and planning out the entire approach. For example, if I have to start with a project, I only provide a brief about what I want, and Windsurf has already planned out step by step how and what to do. That is one significant feature. Second, as I mentioned, it takes the extension from VS Code, so the user interface is something I am already accustomed to. Furthermore, because the core objective of Windsurf is that you give prompts and it will do the coding, that core objective itself stands out. Nowadays AI is very involved in the work, so Windsurf has done a great job for coders where the coding is handled by the AI, and I just have to prompt. This is helpful even for non-technical people. They do not have to think or understand deeply into the code. Even the basics are fine, but not being deep into the code is acceptable if they do not know. By prompting and improving the prompts for Windsurf, I think they will get things done. I am grateful to Windsurf for this.

In summary, with the help of all these features that Windsurf provides, what is happening is the time consumption has been reduced drastically. If I had to build any project that would take at least a month or so with the required effort, I think it has been reduced to approximately a week, and the effort has also been reduced drastically.

Windsurf could be improved as it is lagging now compared to a competitor platform like Claude. It could have integrations with multiple MCP servers, compared to what Claude could offer. That is one area for improvement. Another area is the local hosting of Windsurf rather than just using it and downloading it. I think if I could remotely access Windsurf through prompts and such, it would also improve the features in this aspect.

Support for Windsurf could be better. I have faced the issue of having a paid plan but only being given free trial access. Even though I was on the paid plan and I had already paid, I needed that access instantly instead of being locked up with the limitation that the free trial had. The free trial only gave 100 credits, whereas my usage was even more than that. I had to be limited for that 10 to 14-day period that exists in the free trial, and only after that could I fully utilize it to its potential. That is one issue. This is something that most people have faced. I actually went through Reddit and other platforms, and this is something that most people have commented on, but it is still not yet corrected by Windsurf. That is one concern. However, the performance is good.

I have used Windsurf  periodically for months. Since my college years, I have also used Windsurf  to build projects and coursework. In addition, I use Windsurf in my current work job.

I think others looking into using Windsurf should start with the free plan and focus more on prompting. The best thing you could do is use the free models. You can use ChatGPT or Claude to get a proper understanding. First, explain what you want to those tools, get a prompt for it, and then use that prompt in Windsurf so that the output is much better than randomly saying things to Windsurf and asking it to get the job done. If you have a better understanding, you can go to ChatGPT or Claude, get a prompt from them, and then use that prompt in Windsurf so that the efficiency and output is much better. I have given this product a rating of 9 out of 10.

My main use case for Windsurf  is developing various microservices in our domain, which are Java Spring-based microservices. I use Windsurf  for generating code, writing unit test cases, and suggesting project creation from scratch, such as for Spring Boot . Moreover, we work heavily on the SQL side, where we frequently encounter slow-performing SQLs. I tune and fine-tune the SQLs with the help of Windsurf, and it gives good results to us.

Regarding my main use case with Windsurf, we try to adopt CI/CD as part of our current work protocol. We had an old repository of thirty to forty modules that needed to be migrated to CI/CD by updating the pom.xmls and the Jenkins  build files, which involved very repetitive work that developers needed to do manually. I took the help of Windsurf for this CI/CD integration for one module and asked Windsurf to replicate the same steps in all the modules by adding the build XML file and making changes in the build and deployment aspects. It very smoothly replicated all those files in all the modules and saved a lot of time on this manual effort.

The best features Windsurf offers include the code generation part where I can suggest something for generating a code file, and it has the option of validating that file before it commits to my file system. I can either accept or reject those changes. It has the capability to generate code up to the mark, with good quality. Since I have multiple options to try different models, it provides me good flexibility to validate which model fits in which scenario, allowing me to decide and choose a model that helps get my work done.

Regarding the features, another important aspect is the understanding of the context of the codebase. Windsurf is very powerful in analyzing my source code and understanding the context against which I am asking it to generate code. It helps a lot when I open my code repository and give the context, and by searching the file, I can locate which file to change, and Windsurf can read the complete code. According to the context, it can suggest me the solution.

Windsurf has positively impacted my organization by saving significant time, which is a great feature I have observed. The redundant manual and repetitive work we used to do is now handled by Windsurf. Many old codes were developed by previous team members, and new team members find it hard to understand. Windsurf helps a lot in understanding the code and providing crisp details about what each part of the code does. It definitely reduces the developer's effort in coming up with solutions and understanding the features or functionalities written in the code.

I see an option for improvement regarding the platform that Windsurf is developed on, which is VS Code. We have projects in different technologies and languages, so if Windsurf can smoothly support running Java code, Spring Boot  microservices, or enhance debugging capabilities, then it will be a one-stop shop for everything.

From a usability perspective, Windsurf should be more user-friendly. When code gets generated, I see room for improvement in copying, looking at old queries or prompts, and copying the output from the cascade window to other codebases.

I started exploring Windsurf since last year, so almost a year or so.

Windsurf so far looks stable to me; I have never seen it crash or fail to generate the required output. In the majority of cases, I see that Windsurf is working very stably.

Windsurf is able to handle larger workloads; I try to perform code generation for multiple modules, and Windsurf can manage that.

I have not talked to customer support for any issues.

I previously explored the Google Code Assistant once initially, and compared to that, I am really impressed by Windsurf's capability to understand the context and make code suggestions. That is why I prefer Windsurf. Before choosing Windsurf, I evaluated other options such as Google Code Assist.

I can comment on the time saved, but I do not have visibility on other aspects regarding return on investment.

We are more involved in the usability of Windsurf, so I am not sure about the pricing. The licensing is one aspect; we have a limited license for individual team members who can use Windsurf.

I would definitely suggest others to give Windsurf a try and start using all its features. It will help, and they will find some features that are very useful based on their requirements and what options they are looking for. Overall, Windsurf is a great tool, fitting the current AI journey that individual organizations are looking to join. It is really helping employees and developers accelerate their code generation lifecycle. I give Windsurf an eight out of ten overall.