AI coding assistants have revolutionized software engineering, whether we’re talking about GitHub Copilot, ChatGPT, Cursor, or any number of other tools.
By now, you’ve probably tried one yourself, or you’re thinking about it. AI coding assistants are tools that use machine learning to assist in writing and debugging code. They analyze patterns from millions of code repositories to suggest solutions in real-time.
But before diving into using AI code assistants, it’s useful to understand their capabilities and limitations, including how you can use them to learn how to code in a way that still ensures you grasp important fundamentals that’ll help you be a successful software engineer.
What are the benefits of an AI coding assistant?
AI coding tools excel at specific tasks. In particular, they can:
- Generate boilerplate code fast.
Need a basic React component? A Python function to read CSV files? AI assistants spit out working templates in seconds. No more copying from Stack Overflow. - Auto-complete syntax like a pro.
Forget semicolons or mixing up brackets. AI assistants catch these mistakes before you even run your code. It’s like having spell-check for programming. - Explain confusing code snippets.
Found a weird function online? Simply paste it in and you’ll get an easy-to-understand explanation of what each line does. It’s useful when you’re stuck. - Speed up your learning curve.
Instead of Googling “How to sort an array in JavaScript,” you can ask your AI assistant. You’ll get instant examples and learn patterns faster.
Where do AI coding assistants fall flat? (And why does it matter?)
AI coding assistants do have some limitations, and they stand out when you tackle elaborate projects, including when working in a professional software engineering team environment. Here’s where they present some challenges:
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- They don’t understand your project’s big picture or your company’s main objectives.
AI sees individual functions, not entire applications or larger business goals.. It can’t architect your app or make strategic decisions without your contributions. - Complex logic still needs human brains.
Are you building an algorithm to match users based on 15 different criteria? AI might generate something that looks right, but it fails to consider edge cases you and your team need to think through and explore. - They can’t replace foundational knowledge.
Using AI without understanding the basics is like using Google Translate to “speak” French. You’ll produce something that technically works but misses crucial nuances. - Addressing long-term code quality issues.
A recent report analyzed the quality of 211 million lines of code written with the help of AI code assistants. It found that while these tools can boost short-term productivity, they’re also introducing long-term code quality issues.
- They don’t understand your project’s big picture or your company’s main objectives.
Resourceful ways to use AI coding assistants
Are you ready to start using AI without becoming dependent? Here are some strategies to help you use these tools to help you, and not hinder you.
Use AI as a support, not a shortcut
Think of AI coding assistants like training wheels. Use them to explore new concepts, debug faster, and generate starting points. But make sure you understand why the suggested code works.
Always test and verify AI’s suggestions
Never copy and paste without a critical look at what AI has provided you. AI generates plausible-looking code that can be incorrect, so always run tests and check performance. For example, you wouldn’t want to pass along an AI-generated authentication code with a massive security hole.
Build your knowledge and understanding alongside AI tools
For every AI suggestion you use, write the same functionality yourself afterward. This is a helpful way to spot patterns, understand trade-offs, and develop real coding intuition. Your ultimate goal should be to code confidently without AI when needed.
Consider the benefits of group training
AI can’t replace structured learning environments. For example, coding bootcamps like Hack Reactor include hands-on classes taught by industry-experienced instructors. They’ll teach you foundational coding skills reinforced by cutting-edge AI coding tools, so you know how to code with or without assistance.
The winning formula: Build a strong foundation with AI tools
AI coding assistants enhance productivity for software engineers who already have a solid understanding of code. They can also help new coders learn faster. Are you ready to build your coding foundation? Apply now to our Beginner Coding Bootcamp and join 14,000+ alumni working across industries.