I've been using AI tools for coding for around two years, specifically playing around with Cursor for about eight months. In that time, I've gone from skeptic to convert to what I'd call a "balanced practitioner." Let me share what I've learned along the way.

These days, I rarely type out complete functions or logic from scratch. With Cursor + Sonnet 3.7 at my fingertips, I'm prompting nearly everything. Manual typing has become just an implementation detail in my workflow - a mindset shift that has completely transformed my productivity.

Using AI tools gives me more bandwidth to take on more tasks and ship faster overall. I'm finishing features in half the time, creating documentation without the usual procrastination, and handling more parallel tasks than ever before. But there's a fine art to using these tools effectively.

The Vibecoding Phenomenon

I have noticed that many developers fall into what I refer to as the "vibe-coding trap." They provide vague prompts to AI tools and accept the output without critically evaluating it. While the code may compile and adhere to certain patterns, it often introduces subtle technical debt that accumulates over time.

Systems designed predominantly by AI often implement generic patterns rather than ones tailored to specific project needs. They don't account for the quirks of existing codebases. And they can create a false sense of understanding - you think you know how your system works, but you've outsourced the thinking.

Fortunately, I've developed an approach that maintains quality while leveraging AI's strengths.

Finding the Sweet Spot

Through observation and practice, I've refined the best human-architected, AI-implemented approach. Here's my formula:

1. You define the architecture. Before touching AI, sketch out the components, interfaces, data flow, and patterns you want to use.
2. You design the APIs. Determine how different parts of your system will communicate, what the contracts will look like, and how errors should be handled.
3. You establish the patterns. Decide on the conventions, patterns, and practices that make sense for your project.
4. Then, let AI implement the details - Once the blueprint is clear, AI can fill in the implementation details following your guidelines.

The architect in me stays human while the implementation details get an AI boost. This approach has fundamentally changed what I can accomplish in a day without sacrificing quality.

Where AI Truly Shines

I've found AI to be exceptionally helpful for:

• Writing boilerplate code that follows established patterns
• Implementing algorithms, I understand conceptually but don't want to type out
• Creating comprehensive unit tests for my code
• Generating documentation that accurately reflects my intention
• Learning new framework APIs without context-switching to docs
• Creating multiple related files that follow a consistent pattern

These tasks consumed hours of my time without adding much intellectual value. Now, they take minutes while I focus on the aspects of development that must remain human-driven: system architecture, high-level design decisions, security considerations, and understanding the broader business impact of technical choices. 

Despite all the AI assistance, I'm shipping faster than ever, with guardrails that keep the code quality high. AI doesn't replace my expertise - it amplifies it by handling the tedious parts. 

When working with AI coding tools, I stick to a few key principles: make prompts specific rather than vague, design first and then implement, review everything before committing, understand all code I accept, and refine through multiple iterations rather than accepting first drafts. 

The magic happens when you define clear boundaries: human-driven design and AI-assisted implementation.

Final Thoughts

Finding balance in AI-assisted coding isn't just about productivity—it's about maintaining craftsmanship while eliminating drudgery. It's about using AI as a force multiplier for your expertise rather than replacing your thinking.

I smile when people ask if I'm worried about AI replacing developers. The developers who will thrive aren't those who can type the fastest or memorize the most APIs—they're the ones who can architect elegant solutions and leverage AI to implement them efficiently.

I often say: "Software is not about software; it's about people." AI hasn't changed that fundamental truth—it's just given us new tools to express our solutions more effectively.

So, go ahead and embrace AI in your workflow. Just remember to balance the vibe in your coding.