As a software engineer, I am constantly looking for ways to improve my efficiency and productivity. One area of technology that I’ve found which has gained a lot of attention in recent years is artificial intelligence (AI). AI tools can help you write code more quickly by generating it automatically based on a prompt or set of instructions.

However, it’s important to use AI tools as a supplement to, rather than a replacement for, human expertise and judgment. While AI can be a useful tool, it’s not perfect, and it’s always a good idea to review the code that it generates to ensure that it meets the desired specifications and is of high quality.

What follows is my evaluation of the benefits and limitations of current AI tooling. I did not focus on any one single tool, but rather the genre as a whole. After exploring the landscape, we’ll wrap up with a few tips for using these tools effectively. Let’s dig in.

The Benefits of AI Tools:

• Increased consistency: AI tools can help ensure that code is written consistently, following established guidelines and standards. This can make it easier to maintain and update the code in the future.
• Fewer errors: AI tools can help reduce the number of errors in code by automatically generating it based on a prompt or set of instructions. This can save time and effort that would otherwise be spent debugging and fixing errors.
• Improved efficiency: By automating certain tasks, AI tools can help you complete projects more quickly and efficiently. This can free up time to focus on more complex or creative tasks.
• Increased productivity: By using AI tools to automate routine tasks, you can increase your overall productivity and get more done in less time.
• Expanded knowledge: Using an AI tool that is trained on a large dataset of code and information can provide access to a wider range of knowledge and experience than an individual human software engineer. This can be a benefit when using AI tools to generate code or perform other tasks.

The Limitations of AI Tools:

• Complexity: AI tools may not have the same level of understanding of the problem domain as a human software engineer, and therefore may not be able to generate code for more complex tasks.
• Review and testing: The generated code still needs to be reviewed and tested to ensure that it is correct and meets the desired specifications. Skipping this step could lead to errors and issues that could have been caught with a thorough review.
• Lack of creativity: AI tools may not be able to come up with creative or innovative solutions to problems, as they are limited to the information and instructions provided to them.
• Dependency: Relying too heavily on AI tools may lead to a loss of skills and knowledge, as developers may not have the opportunity to practice and improve their own coding abilities.
• Bias: If the dataset used to train an AI tool is biased, the tool may generate biased output as well. It’s important to carefully consider the dataset used to train the tool and ensure that it is diverse and representative.
• Connectivity: The current generation of AI tools (specifically LLMs) are hosted online by large organizations. Any requests you make to their service can be logged and this is a valid concern for some people/organizations. Additionally, you cannot access the service if you yourself are not connected to the internet (e.g. travel - although, that is increasingly less of a problem).

Despite these limitations, AI tools can still be a valuable addition to a software engineer’s toolkit when used effectively. And now for the tips I promised for using AI tools effectively in software development.

Tips for Using AI Tools Effectively:

• Use the AI tool as a supplement, not a replacement: As mentioned earlier, it’s important to use AI tools as a supplement to, rather than a replacement for, human expertise and judgment. This will help ensure that the code being generated is of high quality and meets the desired specifications.
• Review the generated code carefully: Make sure to take the time to review the code that the AI tool generates. This will help you catch any errors or issues that the tool may have missed.
• Understand the limitations of the AI tool: It’s important to have a clear understanding of the capabilities and limitations of the AI tool you are using. This will help you know when it is appropriate to use the tool and when it may be better to write code manually.
• Use the tool in moderation: Don’t rely on the AI tool for every task. Instead, use it judiciously and only when it can add value to your workflow.
• Continually improve your own skills: Make sure to continually improve your own programming skills, even if you are using AI tools. This will help ensure that you are able to understand and review the code that the tool generates, as well as write code manually when necessary.

By following these tips, you can maximize the value of AI tools in your workflow and avoid becoming overly reliant on them.

However, it’s always a good idea to periodically check in with yourself to ensure that you are using the tools effectively. One way to do this is to ask yourself the following “break glass” question (i.e. a question that’s available in case you don’t know what else to do): “If I had to write code manually, would I be able to do so effectively?” If the answer is “no,” it may be a sign that you are becoming overly reliant on the AI tool. In such cases, it may be a good idea to take a step back and reassess your use of the tool to ensure that it is being used effectively and in a way that complements your own skills and expertise.

Break Glass Question: “If I had to write code manually, would I be able to do so effectively?”

In some cases, you may be able to write large blocks of effective code manually without the help of an AI tool, but it might take longer because you would need to perform some research, make a number of decisions, and iterate towards a solution. In these situations, it’s important to be mindful of the scope of the AI usage and avoid biting off more than you can chew, as this can lead to the over-reliance problem mentioned earlier. To strike the right balance, consider using the AI tool to automate certain tasks or generate code for simple, routine tasks, while reserving more complex or creative tasks for yourself. This can help ensure that you are using the AI tool effectively and not asking it to do too much at once.

AI tools can be a valuable addition to a software engineer’s toolkit, providing the ability to generate code quickly and improve efficiency. But remember, it’s important to use these tools to supplement your own expertise and judgment, not to do all the work on your behalf. By understanding the benefits and limitations of AI tools, and using them effectively, you can maximize their value in your workflow.

Do you have any tips for using AI tools effectively in software development? Share your thoughts in the comments below!