Otto Williams
Jun 3, 2024
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In the span of just a few years, generative AI has transformed how organizations build products, create content, and resolve problems. The majority of business and technology leaders using GenAI are focusing on efficiency and cost-effectiveness gains, according to a 2024 Deloitte survey, with 91% of respondents reporting that they “expect generative AI to improve their organization’s productivity.”
For software developers, generative AI is a game changer, though the term “artificial intelligence” can be misleading. It’s not actually intelligent; it crunches numbers, recognizes patterns, and processes data at a speed beyond human capabilities. It’s no replacement for human expertise and execution, but it can take the lead on mundane, repetitive tasks, allowing teams to dedicate more time and energy toward critical thinking, problem-solving, and collaboration.
A 2023 McKinsey study showed that generative AI tools can significantly improve software developers' productivity on common tasks: "Documenting code functionality for maintainability (which considers how easily code can be improved) can be completed in half the time, writing new code in nearly half the time, and optimizing existing code (called code refactoring) in nearly two-thirds the time." And GitHub’s research found that Copilot, its popular AI development tool, helps developers complete tasks up to 55% more quickly.
By using GenAI tools on my own development team, I’ve discovered that they are most valuable in two key applications:
- Code suggestion and autocompletion: AI can analyze developers' code as they work, automatically generating recommendations for code snippets or complete functions based on context and input. Autocompletion reduces manual coding time, especially when there are blocks of repetitive code in a project.
- Code analysis and bug detection: Generative AI can quickly review code to detect errors or bugs early in the development process. AI tools can also learn from historical data and automate code pattern analysis, proposing modifications to improve code blocks.
Strategies For Implementing AI In Software Development
To maximize the benefits of AI in software development, I recommend the following four strategies:
1. Test And Evaluate Different Tools
Experiment with a variety of AI plugins and platforms to find one that best fits your team’s needs. Test each tool on basic tasks, then scale up to bigger projects, such as detailed code creation or bug analysis, to gauge where it offers the maximum benefit.
2. Create Better Prompts
The quality of your results depends on the quality of your prompts. Learn how and what to ask GenAI to get the most out of your programming tools. If you don't get the answer you're looking for with your first query, iterate to refine your prompt. Provide additional context and specific requirements to guide AI toward your desired outcomes.
3. Review Code Carefully
GenAI can greatly improve your efficiency in code creation, but it still needs human oversight. I see AI as just another tool in an experienced developer's toolbox. You can’t expect a junior developer to write perfect code with GenAI, in the same way you can’t expect a junior marketer to write a flawless article using ChatGPT. You may end up with a solid structure and some sections that work well, but you’ll also likely have blocks that need to be debugged or rewritten. Have a senior developer on your team double-check everything AI creates to prevent errors.
4. Protect Sensitive Data
Be mindful of data privacy and security considerations when using GenAI for software development. Set clear team policies that prohibit sharing sensitive client data or proprietary information with AI providers that make queries publicly available.
While GenAI can significantly enhance your team’s productivity, it's not a panacea. It’s a valuable tool when trained and used correctly. You can’t expect it to work miracles, but you can leverage it to save time and money throughout the development pipeline. Set realistic expectations, and use AI tools strategically and thoughtfully—in conjunction with human expertise and oversight—to deliver software solutions more efficiently than ever before.
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Source: [Forbes](https://www.forbes.com/sites/forbestechcouncil/2024/06/03/how-to-accelerate-software-development-with-generative-ai/?sh=676a00453ac3)