AI-assisted software development processes are growing every day, and new tools continue to enter our lives. So far, the most popular tools in this space have been Cursor and Windsurf.Using Cursor for AI-assisted development saves an incredible amount of time. Especially when it’s in the hands of someone who knows what they’re doing, these kinds of LLM coding tools can be extremely beneficial. MCP servers, in particular, have taken things to a whole new level, and it looks like we’ll see even better advancements in this area in the near future.> Model Context Protocol (MCP) is an open standard designed to facilitate seamless integration between large language models (LLMs) and external data sources or tools. Introduced by Anthropic in November 2024, MCP addresses the challenge of connecting AI systems to diverse datasets by providing a universal protocol, thereby replacing fragmented integrations with a more sustainable architecture.Everyone has their own experiences with these AI-assisted tools like Cursor and Windsurf. Someone love them, someone find them lacking, and someone struggle to adapt. A lot of this actually comes down to expectations and habits. Personally, the process is going pretty well for me, but I’m not fully on board just yet.Even though we can guide the code and methodologies being used, sometimes explaining errors and walking through solutions can become exhausting and tedious. That’s why, while I offload a lot of the general work to AI, I still handle many things myself, especially minor adjustments. I’m trying to shift my approach to more of a “review, fix small issues, and refactor” level. I’m not fully immersed in the process, but I still maintain control. I’ll figure out the next steps as I go.One of the most important things is to really understand and learn the tool you’re using. Whether it’s Cursor or Windsurf, these are excellent tools, but if you don’t fully grasp their features and concepts, you might end up taking much longer to get results—or worse, not getting the results at all. That’s why it’s crucial to cover every aspect that impacts the context of your work. The faster you get a handle on things like “What are the modes?”, “How should rules files be structured?”, and “How can I make the context clearer?”, the better and more efficient your output from these tools will be.### In summaryAI can generate rapid outputs for PoC-style work. It’s particularly useful for UI tasks, writing tests, and similar areas where you can get better and faster results. But when moving into production-level projects, having an experienced eye overseeing the process makes a huge difference (in my opinion). Even if AI writes the code, having the knowledge and experience to evaluate the results meaningfully is essential.We’ll all be watching to see where things evolve in the coming period—how much things will improve, how much faster and more reliable they’ll get. Let’s see what’s next! 🚀