Cursor

What do you like best about the product?

The AI integration in Cursor feels genuinely woven into the coding workflow instead of bolted on as an afterthought. Inline code generation and chat-based editing pull context from the whole codebase, not just the open file, so suggestions actually match existing architecture and coding patterns rather than generic boilerplate. Tab-to-accept autocomplete is fast and often predicts multi-line edits correctly, saving a lot of repetitive typing during daily development.
The interface stays close to a familiar VS Code layout, so there's almost no learning curve coming from that ecosystem — getting started took minutes rather than a real onboarding process. Extensions and settings carry over smoothly, and the editor stays responsive even in larger projects with many open files. Integration with existing Git workflows and terminal usage feels seamless, and referencing specific files or symbols directly in a prompt makes debugging and refactoring noticeably quicker than switching to a separate AI tool.
On pricing, the value holds up well against the time it saves — faster iteration and fewer context switches easily justify the subscription cost for a small technical team. Support has been reliable when needed, with documentation that covers most common issues, so there's rarely a wait to keep moving. Overall it's become a core part of the day-to-day coding process.

What do you dislike about the product?

Pricing gets frustrating once usage scales — the fast request limits on the standard plan get consumed quickly on larger codebases, and hitting that ceiling mid-task means either slowing down to conserve requests or upgrading to a higher tier sooner than expected. More transparency around real-time usage consumption would help, since right now it's often only clear after the fact.
Performance can also dip on very large repositories — indexing takes noticeably longer, and the context window occasionally doesn't fully capture relevant files scattered across a big project, so suggestions miss dependencies living outside the immediate working directory. That means double-checking generated code more carefully on bigger builds than on smaller ones.
The AI still occasionally hallucinates function signatures or library APIs that don't actually exist, especially with less common packages or internal libraries it hasn't seen much of, so verification against actual documentation remains necessary rather than optional. Multi-file refactors sometimes need manual cleanup afterward since the model doesn't always catch every downstream reference that needs updating.
Onboarding new team members to the AI-specific features (custom rules, context management, model selection) takes more explanation than just picking up a standard editor, since getting real value out of it requires understanding how to prompt and scope context effectively. Minor learning curve, but it's there.

What problems is the product solving and how is that benefiting you?

Cursor is solving the friction of context-switching between writing code and getting AI assistance — instead of copying code into a separate chat window and pasting suggestions back, everything happens inline within the actual editor. This has meaningfully sped up day-to-day development, especially for repetitive tasks like writing boilerplate, generating test cases, and drafting initial implementations of well-understood patterns.
It's also cut down significantly on time spent debugging, since the AI can scan across multiple files to spot the source of an error rather than manually tracing through the codebase file by file. For a small technical team without dedicated resources for every specialization, this has been a real force multiplier — junior or less experienced developers can move faster on unfamiliar parts of the stack because the AI helps bridge knowledge gaps in real time, whether that's an unfamiliar library, a new framework pattern, or legacy code someone else wrote.
Refactoring large codebases has become considerably less tedious too. What used to mean manually updating dozens of related files can now be scoped and handled in a single pass with AI assistance, with far fewer missed references than doing it by hand. On the documentation side, having AI help generate and maintain inline comments and docstrings has improved code readability across the team, which matters a lot given multiple people touch the same codebase over time.
The net benefit has been faster iteration cycles overall — less time spent on mechanical, repetitive work means more time available for actual architecture decisions, business logic, and problem-solving that requires real judgment.

What do you like best about the product?

Code generation, debug issues and ask questions about your project

What do you dislike about the product?

a bit expensive and some times it took more token then required

What problems is the product solving and how is that benefiting you?

It wrote a complete code of live activity in my swiftui project with actions and response

What do you like best about the product?

What I like most about Cursor is that it feels like an IDE first and an AI tool second, which means I'm the guy in the chair. The AI is deeply integrated into the development workflow instead of feeling like a separate chatbot. Features like editing across multiple files, understanding the codebase context and making targeted changes save a lot time compared to constantly copying code back and forth.

I also appreciate that cursor doesn't try to replace the developer. It speeds up repetitive work, helps me navigate unfamiliar code, and lets me stay focused on solving the actual problem. It strikes a good balance between automation and keeping me in control, which makes it something i can use throughhout the day rather than occasionally

What do you dislike about the product?

Sometimes the AI makes broad changes when i want a small, targeted edit. It can also lose context in very large or complex codebases.

Occasionally, the suggested code looks correct but misses subtle project specific details. I would also like more transparency into why it chooses edits or approaches

What problems is the product solving and how is that benefiting you?

Cursor reduces the time spent on repetitive coding tasks like refactoring, debugging and boilerplate generation.

It understands the project context, so I spend less time explaining my code.

This lets me stay focused on solving problems instead of switching between tools.

As a result, I'm able to build features faster and maintain better development flow.

What do you like best about the product?

That the AI is embedded in the core of the editor and not attached with a side widget. The autocomplete with Tab is super fast and being able to launch refactorings that affect multiple files at once from Composer saves you a lot of time. Being a fork of VS Code, the learning curve is zero; you open your workspace, it indexes the project, and you're working from the first minute.

What do you dislike about the product?

RAM consumption gets spammed quite a bit when indexing large repositories, and sometimes the credit system falls short if you push Composer hard daily. It would also be cool if the context management allowed for a bit more manual fine-tuning of the files to ignore.

What problems is the product solving and how is that benefiting you?

It takes the heavy carpentry off my shoulders: writing repetitive code, assembling types, and searching for documentation. By indexing the entire project, I can request refactorings that touch multiple files at once without having to manually copy and paste context. In the end, it translates into developing much faster and focusing on logic and architecture instead of wasting time on mechanical tasks.

Regarding integrations, being a direct fork of VS Code, you can import all your extensions, themes, and previous configuration with a click, and it connects very well with GitHub/GitLab repositories and external documentation through the option to add custom docs. In terms of ROI, the impact is immediate: with the monthly subscription, you recover those work hours in the first few days of use just with the time you save from writing repetitive code and migrating files.

In terms of support and onboarding, the curve is flat. The onboarding literally takes two minutes because it brings all your VS Code configuration at once, without having to relearn shortcuts or reinstall tools. On the support side, the community in its forum is super active and they release updates almost every week, fixing bugs and incorporating the latest models as they come out, so you never get stuck with an obsolete version.

What do you like best about the product?

I use Cursor for coding HTML apps and Android/iOS apps, including Whisper translation apps. I like that it's really clean and pro. It offers a large range of models. I like the model composer because it's fast. The initial setup was easy and fast.

What do you dislike about the product?

I don't like that you hit your monthly limits in an hour. The rate limits are a big issue, and I think increasing them would really help. Also, even though Cursor is popular, I felt that Antigravity was better.

What problems is the product solving and how is that benefiting you?

I use Cursor for coding HTML and mobile apps. It offers a large range of models.