My curiosity about AI coding assistants started when I found myself struggling to quickly ramp up on new technologies after spending years in leadership roles away from hands-on coding. Like many developers, I was intrigued by the rising wave of AI-powered tools that promised to streamline development, but I wondered—could they really help me bridge the gap? These AI assistants promised to revolutionize how we code—offering everything from intelligent code completion and real-time documentation lookup to automated testing and bug detection. The pitch was compelling: imagine having a senior developer looking over your shoulder, offering suggestions, catching errors, and helping you navigate complex codebases. They would supposedly cut development time in half or less, eliminate hours spent digging into third-party codebases, and make coding more accessible to developers at all skill levels.

But the reality often fell short. Early tools would frequently suggest non-sensical code or simply miss the context of what you were trying to achieve to the point where they were more an obstacle than an asset. But as AI technology evolved, particularly with the advent of Large Language Models (LLMs) trained specifically on code, these tools began to show real promise. The suggestions became more contextually aware, the code more reliable, and the overall experience more natural.

Enter Cursor—a tool that promised to be different by combining the power of LLMs with a streamlined coding environment. What caught my attention wasn't just the AI capabilities, but how seamlessly they were integrated into the development workflow. Unlike previous tools that felt bolted on, Cursor was built from the ground up with AI assistance in mind.

After a month of using Cursor for developing my blog, I can confidently say it's been a game-changer 🚀—though not without its quirks and limitations. It has significantly streamlined my workflow, helping me write code faster and navigate unfamiliar technologies more efficiently. However, like any AI tool, it comes with challenges—sometimes making incorrect assumptions or requiring careful prompt crafting to get the best results.

In this post, I'll dive into both the benefits and limitations I've encountered while using Cursor in my daily development process.

Making Every Minute Count

The reality of being on paternal leave means that my development time comes in unpredictable bursts—fifteen minutes here, an hour there if I'm lucky. While I haven't started building my business app yet, developing this blog serves as a perfect mini-project to get back into programming.

As someone who has transitioned into leadership roles, I've spent more time in meetings than writing code lately. But Cursor's AI capabilities allow me to maintain momentum even during these brief windows of opportunity. Instead of spending precious minutes refreshing my memory on API documentation or debugging syntax, I can dive right in, with an AI assistant that remembers the context and helps me pick up the thread immediately.

This experience not only helps me regain my coding confidence but also provides hands-on experience with modern web frameworks—essential knowledge I'll need when I start developing my own business.

The Power of AI-Assisted Development

One of the most impressive aspects of working with Cursor has been its ability to help me navigate unfamiliar territory. Despite having only occasionally used JavaScript professionally and never having touched TypeScript before, I found myself confidently adding features to a foreign codebase within minutes. The AI assistant made me feel fluent in languages and frameworks that were practically new to me.

Take Tailwind CSS, for instance—a framework I had never used before. Cursor bridged the knowledge gap perfectly. As someone primarily focused on backend development, I was amazed at how quickly I could create modern, responsive layouts. The AI suggested Tailwind classes that handled everything from basic styling to complex responsive behaviors, effectively turning me into a competent frontend developer overnight. ✨

Another example was when I decided to add commenting functionality to my blog. This task perfectly demonstrated how Cursor handles real-world development challenges. The AI helped me navigate through multiple requirements: setting up the Remark42 server on Fly.io, configuring the Next.js integration, and ensuring everything worked seamlessly with my existing codebase. What might have taken hours or even days of research and trial-and-error was accomplished in a fraction of the time. Let me show you exactly what happened when I gave Cursor this prompt:

Integrate my blog with Remark42 to support comments on my blog posts. Use Fly.io for production hosting.

The AI's response was comprehensive, providing not just code but rich context and detailed explanations for each step. While the React component shown below is just an excerpt from the full output, it demonstrates how Cursor understood the complexity of the task. The AI broke down the integration into manageable chunks, explaining the purpose of each configuration option and providing guidance on best practices. Here's a glimpse at the React component it generated:

1"use client";
2
3import { useEffect } from "react";
4
5interface Remark42Props {
6  url: string;
7  id: string;
8}
9
10declare global {
11  interface Window {
12    remark_config: {
13      host: string;
14      site_id: string;
15      url: string;
16      max_shown_comments: number;
17      theme: string;
18      locale: string;
19    };
20  }
21}
22
23export default function Remark42({ url, id }: Remark42Props) {
24  useEffect(() => {
25    // Initialize Remark42 configuration
26    window.remark_config = {
27      host: process.env.NEXT_PUBLIC_REMARK42_HOST || "https://comments.yourdomain.com",
28      site_id: process.env.NEXT_PUBLIC_REMARK42_SITE_ID || "your-site-id",
29      url: url,
30      max_shown_comments: 10,
31      theme: "light",
32      locale: "en",
33    };
34
35    // Load Remark42 script
36    const script = document.createElement("script");
37    script.src = `${window.remark_config.host}/web/embed.js`;
38    script.async = true;
39    document.body.appendChild(script);
40
41    return () => {
42      document.body.removeChild(script);
43    };
44  }, [url]);
45
46  return (
47    <div className="mx-auto mt-8 max-w-2xl">
48      <div id="remark42"></div>
49    </div>
50  );
51}

We can see here that it not only added the required scripts and elements for integration straight from the Remark42 documentation (without us needing to give it any pointers of where to find it), but also that it figured out that it needed to use the useEffects hook as well as provided type safety through TypeScript declarations and interfaces. This attention to detail meant I could start using the component right away with proper type checking and IDE support.

What impressed me most was how Cursor handled the full-stack nature of the integration. Not only did it generate the frontend component shown above, but it also provided the necessary Fly.io configuration files. The AI understood that a commenting system needs both client and server components, and it seamlessly delivered both—starting with that React component and following up with the complete server configuration.

1app = "your-remark42-app-name"
2primary_region = "lhr"
3
4[build]
5  dockerfile = "Dockerfile.remark42"
6
7[env]
8  REMARK42_SITE = "your-site-id"
9  REMARK42_ADMIN_SHARED_EMAIL = "your-email@example.com"
10  REMARK42_ADMIN_SHARED_PASSWORD = "your-secure-password"
11  REMARK42_SSL_TYPE = "none"
12
13[http_service]
14  internal_port = 8080
15  force_https = true
16  auto_stop_machines = true
17  auto_start_machines = true
18  min_machines_running = 0
19  processes = ["app"]
20
21[[vm]]
22  cpu_kind = "shared"
23  cpus = 1
24  memory_mb = 1024

This kind of comprehensive assistance transformed what could have been a complex integration process into a straightforward implementation. Instead of juggling multiple documentation sources and figuring out how different pieces fit together, I could focus on customizing the solution to my specific needs. Even the deployment process was simplified, with Cursor providing the exact commands needed:

1# Install Fly.io CLI if you haven't already
2brew install flyctl
3
4# Login to Fly.io
5flyctl auth login
6
7# Launch the Remark42 app
8flyctl launch
9
10# Deploy the app
11flyctl deploy 

Now, I have of course take this code and improved upon it, but it showcases how quickly and effectively Cursor helped me get started. Within minutes, I had a working comments section that I could then customize and enhance. But the initial scaffold that Cursor provided saved me hours of setup time and gave me a solid foundation to build upon. This pattern of rapid prototyping followed by thoughtful refinement became my standard workflow with Cursor. The AI would help me quickly implement a feature's core functionality, and then I could iterate and improve upon it with my own expertise. It's like having a junior developer who can handle the initial groundwork while you focus on the architecture and polish.

Beyond just churning out code, Cursor's hidden superpower was its ability to teach. 🧑‍🏫 By allowing me to mark specific code snippets and add them to the context, I could have real-time, meaningful discussions about my own code right within the editor. Instead of constantly switching between documentation tabs and Stack Overflow threads, this approach not only saved me countless hours of research but also deepened my understanding of the codebase I was working with.

When AI Gets It Wrong: Learning from the Stumbles

Of course, it wasn’t all smooth sailing. Like any tool, Cursor has its quirks and limitations. One particularly frustrating experience involved its persistent misunderstanding of my framework version. It repeatedly suggested “fixes” for code that was already correct, assuming I was using an older version of Next.js where params was a synchronous prop for dynamic routes. No matter how many times I corrected it, the AI stubbornly clung to its outdated assumptions.

Then there were the more amusing misfires. In one case, I asked Cursor to fix a simple linting error. Instead of a quick adjustment, it went into full-blown overengineering mode—layering increasingly complex type casts in an attempt to appease TypeScript. Before I knew it, it had spiraled into a recursive type assertion nightmare, generating an ever-growing mess until the system finally gave up, leaving behind a massive, unusable source file. 🤦‍♂️

My attempt to use Cursor for logo design was another memorable misadventure. No matter how I tweaked my prompts, the results were underwhelming. Determined to make it work, I kept refining my inputs—until I realized I had burned through my entire monthly quota in a single day. 😅 Lesson learned: AI tools, while powerful, aren’t always the right tool for the job. Some tasks still require specialized software or plain old human creativity.

Even implementing something as simple as a news sitemap turned into an unexpected challenge. It took three tries to get it right. First, the AI overlooked my existing content schema and duplicated most of the information. Then it tripped over Next.js App Router’s built-in sitemap support, which wasn’t compatible with Google News extensions. Finally, after some nudging in the right direction—pointing it toward the Next.js SEO examples—it clicked into place.

But here's where things got interesting: despite my initial frustration, Cursor showed its true potential. Even though I had pointed it to examples using Next.js's older Pages Router, the AI recognized I was using the newer App Router architecture. It smoothly adapted the solution, implementing the news sitemap using Route Handlers—proving that when AI tools properly understand context, they can deliver surprisingly elegant solutions. This kind of adaptability turned what could have been another setback into hitting the bullseye dead center. 🎯

Through these ups and downs, I've developed some practical strategies for working with AI coding assistants effectively.

Making AI Work for You: Practical Tips

After a month of daily use, I've discovered several approaches that help maximize the benefits of AI-assisted development while avoiding common pitfalls:

1. Break Down Complex Tasks. I learned quickly that Cursor works best when given focused, specific tasks. Rather than expecting perfect code on the first try, I've found success in using Cursor as part of an iterative process. I start with a basic prompt, evaluate the results, and then continue to refine it by adding more context or providing instructions for how to adjust it to get it right. This matches well with how I need to work during parental leave—making incremental progress in short bursts of time.
2. Leverage Context Effectively. One of Cursor's most powerful features is its ability to understand context. When I need to modify existing code, I first highlight the relevant sections and add them to the AI's context. This gives Cursor a better understanding of the codebase and leads to more accurate suggestions.
3. Verify and Validate. While Cursor's suggestions are often spot-on, I've learned to always review the code it generates. If unsure, you can even ask it to do it for you! For example, I often ask Cursor to explain its own code or to identify potential edge cases I should consider.
4. Use AI as a Learning Tool. Beyond just generating code, I've found Cursor incredibly valuable as a learning resource. When it suggests a solution I'm not familiar with, I ask it to explain the reasoning and provide documentation links. This has accelerated my learning of new frameworks and best practices.
5. Know When to Step Back. Sometimes, especially with complex architectural decisions or creative tasks, it's better to step away from the AI assistant and think through the problem yourself. Not everything needs to be done in your IDE, and there are plenty of other AI tools out there that can help out with research.
6. Manage your resources wisely. AI tools like Cursor often have usage quotas or limits. I learned this the hard way during my logo design adventure! Plan your usage strategically—save your quota for complex coding tasks where AI assistance provides the most value, and consider upgrading your plan if you find yourself consistently bumping against limits. You can also stretch out your resources by using non-premium models such as gpt-4o-mini for easier tasks.

These strategies have helped me maintain a productive workflow even with the unpredictable schedule of parental leave. The key is finding the right balance between leveraging AI's capabilities and maintaining control over your development process.

The Future of AI-Assisted Development

After a month of hands-on experience with Cursor, I'm more convinced than ever that AI-assisted development is not just a trend—it's the future of how we'll write code. Instead of spending hours debugging syntax errors or searching through documentation, we can focus on higher-level problem-solving and system design. The AI handles the tedious parts—suggesting code completions, fixing common errors, and providing instant documentation lookups—while we concentrate on the creative and strategic aspects of development.

What excites me most is how tools like Cursor are democratizing development expertise. They're not just making experienced developers more efficient; they're helping newcomers bridge the gap between learning and doing. I've experienced this firsthand—being able to work confidently with frameworks and languages I barely knew before.

This technological evolution could usher in an exciting new era of solo entrepreneurship. With AI tools acting as force multipliers, individual developers can now tackle projects that would have previously required entire teams. We're seeing the emergence of 'micro-SaaS' businesses and niche solutions created by solo founders who can leverage AI to handle everything from code generation to customer support. In my case, being able to develop a full-featured blog while juggling parental responsibilities would have been nearly impossible just a few years ago.

These AI assistants effectively function as virtual team members—they don't replace human creativity and decision-making, but they dramatically amplify what one person can achieve. This democratization of development capabilities means more diverse solutions making their way to market, addressing problems that might otherwise go unsolved simply because they were too resource-intensive for a single developer to tackle. The result? A richer ecosystem of software solutions, more opportunities for independent developers, and ultimately, more value delivered to society. 🌟

Have you experimented with AI-assisted development? I'd love to hear about your experiences—both the wins and the frustrations. What tools have you tried? How have they changed your workflow? Share your thoughts in the comments below, and let's learn from each other's journeys. Whether you're a seasoned developer exploring AI tools or just getting started, your perspective could help others navigate this exciting new frontier in software development. And if you're curious about specific aspects of my experience with Cursor that I haven't covered here, don't hesitate to ask! 🤝