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AI Coding Assistants: Friend or Foe? A Beginner’s Guide
So, you’ve heard about AI helping programmers write code? It’s true! But just because these tools exist doesn’t mean you should use them all the time. Sometimes they’re amazing, and sometimes they can cause more problems than they solve.
Think of it like this: imagine you have a super-smart robot that can build things. Sometimes it builds exactly what you want, quickly and perfectly. Other times, it gets confused and makes a mess. It’s all about knowing when to let the robot help and when to do things yourself.
What the Experts Say
One expert, Kevin Swiber, says it’s really important to learn when and how to use these AI code assistants. Things are changing so fast, it’s hard to keep up!
And guess what? A lot of programmers are already using AI. According to a survey, 63% of professional developers use AI in their work. They’re using it to save time on things like writing basic code, creating simple functions, writing documentation, and finding mistakes (debugging).
When AI Shines: The Good Stuff
AI is really good at certain tasks. Here are a few examples:
- Writing basic code: Think of the repetitive parts of coding, like setting up the foundation of a house. AI can do that quickly and easily.
- Simple tasks: When you have a clear goal and the code isn’t too complicated, AI can be a real star.
- Popular tools and libraries: If you’re using common programming tools, AI has probably seen them before and knows how to work with them.
Charity Majors, another expert, says AI works well for things like web development (building websites) and mobile development (building apps). The more common the code, the better AI performs. Also, if you get feedback quickly, like with front-end development (the part of a website you see and interact with), AI is more helpful.
Harry Wang adds that AI is great for things like:
- Scaffolding microservices: Lila asks, “John, what are microservices?”
John: Imagine you’re building a big apartment building. Instead of building the whole thing at once, you build small, independent apartments (microservices) that all work together. AI can help you set up these individual apartments. - Generating REST APIs: Lila asks, “John, what are APIs?”
John: Think of an API as a waiter in a restaurant. You tell the waiter (API) what you want (like getting data from a website), and the waiter brings it to you. REST is just a common way of organizing these waiters. - Prototyping: AI can help you quickly create a rough draft of your code, like sketching out a design before building the real thing.
Basically, AI is awesome at taking care of the boring, repetitive stuff, freeing up programmers to focus on the more creative and challenging parts of their work. It’s like having a super-efficient assistant!
AI can also help with tasks outside of writing code directly, like designing the structure of a project, fixing errors in tests, understanding data, and even writing blog posts.
When AI Stumbles: The Not-So-Good Stuff
But AI isn’t perfect. There are situations where it’s not so helpful, and can even make things worse.
Here are some situations where AI might struggle:
- Complex projects: If your project is huge and complicated, AI might get lost.
- Unclear goals: If you don’t know exactly what you want, AI won’t be able to help you. It needs clear instructions.
- Changing existing code: AI is better at creating new code than modifying old code. It’s like trying to remodel a house while it’s still being built.
- Brand new ideas: If you’re working on something completely new and unique, AI might not have enough information to be helpful.
One expert, Swiber, warns that you can waste time and money if you just let AI do whatever it wants. You need to check its work regularly! He also mentions version control (a system that tracks changes to your code) is very important.
Charity Majors agrees that AI is better at creating new code than changing existing code. While AI can speed things up, you still need to carefully review the code it generates. Otherwise, you might spend more time fixing AI’s mistakes than you would have spent writing the code yourself!
Harry Wang points out that AI can make mistakes if you give it vague instructions or if it doesn’t understand the context of the code. These mistakes can be hard to find because AI works in a “black box” – we don’t always know how it came up with its answers. This makes AI risky for important projects that need to be very reliable.
What Leaders Need to Know
Spencer Kimball compares the rise of AI to the introduction of electricity or computers. It’s a huge change! He says that AI can make programmers much more productive, which is like hiring more people without actually hiring them.
Even though it’s tempting to jump on the AI bandwagon, leaders need to understand its limitations and set clear rules for how it should be used. You can’t just let AI run wild!
It’s important for both programmers and leaders to learn about AI and understand its strengths and weaknesses. This will help them use it effectively.
The Future is Bright (But Still Requires Caution)
The capabilities of AI are changing rapidly. What’s true today might not be true tomorrow. But experts agree that AI will play an increasingly important role in software development. One survey found that 92% of developers expect AI to help them in their careers.
Kimball believes that AI will open up many new possibilities, but also create new challenges. One of the biggest challenges will be making sure that data is secure and protected.
One thing that’s holding AI back right now is the “context window” – the amount of information that AI can consider at one time. But this is improving all the time. As AI can process more information, it will become even more powerful.
For now, it’s important to use AI wisely and understand its limitations. But remember, AI is getting better all the time. As Kimball says, “This is the worst the models are ever going to be!”
John’s thoughts: It’s exciting to see how AI is changing the world of programming. It’s not a replacement for human programmers, but a powerful tool that can help us be more efficient and creative. As AI continues to evolve, it’s essential that we learn how to use it responsibly and ethically.
Lila’s thoughts: As a beginner, all this AI stuff seems a bit overwhelming, but also super cool! I’m excited to learn more and see how it can help me become a better programmer.
This article is based on the following original source, summarized from the author’s perspective:
Knowing when to use AI coding assistants
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