Devin by Cognition

On a day-to-day basis, I use Windsurf's agentic mode, the cascade, to develop features in different projects that I work on.

Most of my feature development starts with working with Windsurf's cascade on a plan. For example, if the feature is to develop a new UI update that is linked to a backend, I use cascade to develop a plan to update the UI and also the plan to update the backend. Then I review it and ask Windsurf's cascade to ask any questions about use cases that are not clear. Once I confirm all the ambiguities and validate the plan, I use the agentic cascade mode to finalize and implement the solution.

Windsurf also helps in debugging because the agentic mode has terminal access. When I have an error, I use it as the first step to debug. I give it the error description, the error logs, and it iterates on it to debug and give me a review or a report after it is done to identify the root cause that helps me easily identify and then create a fix. When I need to create a fix for the bug, I use Windsurf in cascade mode to identify and create a plan and then proceed with the implementation.

Windsurf's cascade mode with the agentic integration and the ability to connect MCP servers and create custom agents helps to increase productivity. The agentic mode and the ability to connect with MCP servers that allow me to bring other context into my workflow are the most useful features.

Regarding Windsurf's features and usability, I think the standard is industry standard compared to others. Because I use other AI tools as well, I do not have to do a lot of changing and looking for where things are because it is standard across most of the industry. I think that is a win. Things are easy to configure as well and not too complicated. Windsurf's agentic AI is much more capable compared to other solutions; it understands much more context of the code better than other AI agents or solutions.

Windsurf's impact on my organization is always positive. When used well, in a way that you can plan and ensure that you are developing things that go right in a positive way, you can develop things really quickly and much more robustly. I think it increased productivity. When it was deployed, a lot of engineers had positive results. Things that used to take maybe three or four days can be handled with Windsurf in a day. There is a lot of productivity gains and it allows us to do more in little time.

Regarding improvements for Windsurf, I think it would be good if we had an integration with the cloud, a sort of cloud that way we can have autonomous agents that can handle tasks without human intervention. I know you can run background tasks inside the IDE, but it would be good to have a cloud version where it could spin up its own environment and be able to run and create a pull request for you automatically when it is done. I do not know if it is in the roadmap, but that would be nice to have.

Most of the tools are improving. Windsurf has capabilities to do a lot of things, but it is not a ten out of ten because it is not completely autonomous and it still needs guidance. Sometimes there are hallucinations in the way it works. There are still certain things you need to be much more careful about; otherwise, you end up with code that is not compliant. It is an eight because it does the job well and it has to be guided as an assistant. When it becomes a fully autonomous agent where it can really do things without human intervention, it will become a ten.

I have used Windsurf for close to two years.

Windsurf is stable.

For the number of users we had, it scaled well to close to six hundred users that used it.

I had pretty prompt customer service for Windsurf. We had points of contact that we could reach directly in case of issues, and they were quick to provide feedback, resolutions, and alternative ways to work around some issues.

We do not use a different individual solution before Windsurf; we have a multi-solution approach in my company, using multiple tools such as Windsurf, Hero, and others. The choice depends on the engineer's preference and their use cases; they might decide one tool or the other.

The setup and licensing for Windsurf were done by a dedicated team in the organization. I have no input in that. Mostly my input is to have the tool and use it and assess it. I do not have much more information on that.

Windsurf was subjected to an internal survey with close to six hundred employees in the organization, and we realized based on input from the engineers that it is hard to really identify and track the metrics of savings. Based on surveys conducted internally, we realized that tasks that used to take a week could now take one or two days per engineer. It saves close to three days of work for a one-week task, based on metrics we have globally from people who actually use the tool.

We do not use a different individual solution before Windsurf; we have a multi-solution approach in my company, using multiple tools such as Windsurf, Hero, and others. The choice depends on the engineer's preference and their use cases; they might decide one tool or the other.

Windsurf is a good tool, really powerful, with a really good agentic mode. It has to be used well to ensure that you benefit from its productivity. It can be combined with other integrations to make sure you are getting more context into the environment and also to use plan mode more often to ensure you get the best results.

Regarding Windsurf's governance and security, I know that we have different modes that allow you to choose what level of access you give to the agent. I think it is really well-defined if you want to go full access mode or you want to give it restricted access. It is well-defined and allows you to select which level of security you want. I think it is pretty good in terms of how things are administered.

Regarding Windsurf's accuracy and reliability of output, if you do plan the work that you do with the agent and you iterate on it, you get better results. It has to be used in a much more structured manner; you need to have more input inside the initial way it works before getting really good results. It gives great results as long as you use the right approach with the agent. I gave this review a rating of eight out of ten.

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.