How can AI help developers do better work?

LaMDA. It uses an extensive compilation of text and code, such as books, articles, code snippets, and scripts. It also leverages Google Search's endless capabilities to access real-world information. It won't be long before we see this chatbot in the medical field, as Google's medical chatbot is already being tested in hospitals.

AI Tools for Developers

In the previous section, we discussed the three most popular AI chatbots made for general purposes. But the following tools were designed with the sole purpose of helping developers code faster and more efficiently:

Code completion

• GitHub Copilot A favorite of developers everywhere. Powered by Github and OpenAI, it turns natural language prompts into coding suggestions.
• Tabnino This solution combines the power of a sophisticated public code model and a custom algorithm. This code solution learns codes and patterns from your team, providing enterprise-grade solutions.
• Amazon Code Whisperer Based on billions of lines of code, it suggests code snippets to complete functions based on existing code and your comments.

Code review

• Deep Code is an AI-powered code review tool that stands out for its hybrid approach, combining generative and symbolic AI with the expertise of security researchers to prevent hallucinations (more on that later!).
• Veracode is trained by machine learning and based on research from security experts.

Automated testing and quality control

• Katalon Ranked as one of the best AI automation testing software by Gartner, as of July 2023. You can run automated tests for mobile, desktop APIs.
• Testimonial This leverages ML for creating, executing, and maintaining automated test cases. It is particularly useful for UI as it recognizes sequences for well-architected tests.
• LambdaTest enjoys a great reputation among those looking for a scalable test execution platform.

There are already many tools available aimed specifically at software developers and specific roles on technology teams. If you want more information about them, you can check their websites. Keep in mind that new AI tools are continually being released, as well as technological improvements and new features. Keeping up with new technologies can be tiring, but it is crucial!

Putting these tools to the test

Let's talk numbers and the real question behind why I should use any of these tools: How much does my productivity increase?

GitHub launched its AI-based coding assistant, Co-Pilot about 2 years ago and has made interesting discoveries already with developers who have been using it for a while. This is what their findings report:

• 88% feel more productive
• 59% feel less frustrated with coding
• 60% feel more satisfied with their work
• 74% can focus on the most satisfying aspect of work
• 88% complete tasks faster
• 96% are faster with repetitive tasks
• 77% spend less time researching or researching code
• 87% put less mental effort into repetitive tasks

This has just begun. Let's move away from the development sector and look at an interesting case. A recent study conducted by the National Bureau of Economic Research stated that customer support agents increased their productivity by 14% by using AI tools to assist with their tasks, dramatically helping those with less experience and minimally helping those with experience. This parallelism is a good reference to explain the impact of AI on other fields, such as software development. It is fair to assess that AI skills are essential for programmers (and virtually anyone) to remain competitive and innovative in the digital economy. They help level the playing field for less experienced programmers, older programmers, and those transitioning to new technologies, methodologies, and programming languages.

The imperfection of AI

While the attributes mentioned above paint a utopian picture of AI as a divine entity, it is necessary to dispel such illusions and shed light on the limitations of AI.

• Precision . Contrary to popular belief, AI tools do not always offer pinpoint accuracy and errors are not rare. It is advisable to cross-check the information obtained from AI tools. Bard, for example, often struggles to provide verifiable sources to substantiate its claims. Traditional machines will express their inability to perform a task due to inappropriate context or other reasons, whereas AI typically will not. Instead, it tends to produce incorrect results. This underlines the importance of experience in discerning the accuracy of AI-generated results.
• Artificial hallucinations . You can improve the output of an AI tool by providing more context. Keep in mind that these tools work with LLMs that try to predict your intent and opinion, which can sometimes lead to differing interpretations. This behavior is known as “hallucination” and can manifest itself even in cases of abundant context. This happens when an AI confidently produces responses without support from its training data.

AI hallucinations can be triggered due to several factors, including these:

• Bias in training data. Hallucinations can be derived from biased training data.
• Insufficient training data. Poor quality data can impair the model's ability to differentiate facts from fictional data, thus inducing hallucinations.
• Model complexity. As AI models become more complex, they become increasingly prone to hallucinations when identifying non-existent patterns in data.
• Overfitting. This is when the model is trained to effectively memorize the inputs and outputs of the training data, but will not be accurate for new data.
• Vector coding of LLMs . This happens when words with more than one meaning (for example, “bank”) have only one encoding, when they should have one per meaning. Problems with encoding and decoding can lead to hallucinations.

Is AI a threat to our jobs?

The short answer is no . And there are a few reasons why we can say this categorically.

First, an obvious disadvantage of AI tools is the lack of context about a specific organization, what we call experience of your work, for humans. While they reduce the need for some developers as they allow them to do more with fewer people, there is still a need for human oversight. AI is not equipped to replace the creative and strategic decision-making aspects of software development, which are crucial to creating innovative, user-centric applications.

The conversation is open and it's time to discuss how the development industry will change and what new roles are emerging due to advances in AI. Changes will come and those who are ready to adapt will prosper; those who aren't... well, they may be forced to learn or change careers.

In conclusion, AI tools have undeniable advantages for developers, allowing us to do our work faster and better, with fewer errors, and giving us more time to be human . Be ready to ride the wave or get crushed by it. No one can claim that there was no warning. So our jobs are safe… as long as we stay up to date with the tools at our fingertips and learn how to leverage them!

If you liked this, be sure to check out our other articles on AI.

• Could we develop a system similar to JARVIS?
• Has AI Killed the Developer Star? No, it gave us superpowers!
• Why Edge AI is the future
• The Ethics of AI in Software Development
• 3 Tips for Finding a Great AI Development Partner