AI-Powered Software Development Will Enhance Developers’ Skills

AI coding tools are not just for the production of code, they accelerate existing processes, help developers learn and drive innovation

Chris Reddington, Senior product manager of strategy for developer relations, GitHub

July 8, 2024

3 Min Read
Two rows of programmers sitting at desks
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It’s no exaggeration to say the advent of AI coding tools has transformed the future of enterprise software development. Perhaps that’s unsurprising when you consider that 92% of developers already use them both in and outside of work.

However, as with any genuinely disruptive technology, there is inevitably some tension between early adopters and businesses looking to harness AI-powered software development to gain a competitive edge. This tension is completely normal for any powerful technology being integrated into enterprises. But it’s worth exploring the root cause of tension around the use of AI tools and how it can be alleviated.

The majority of enterprises are sufficiently progressive to understand the enormous opportunity AI coding tools can provide. However, some are not yet clear on the degree to which AI will transform their development processes or the fundamental impact it will have on the future of development itself.

Although they are in the minority, it’s not unusual to hear senior enterprise technology leaders questioning whether AI development tools should be used by junior developers. Their argument is typically focused on the idea that the use of AI tools from the outset of developers’ careers will mean they don’t develop the critical thinking muscle that is so vital in software engineering.

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In some quarters there is a perception that AI tools are so superpowered that budding developers will miss out on the education and coaching moments they require to learn and understand.

This is a complete misperception of the value AI delivers to developers at every level. For junior developers, AI tools accelerate their learning rather than hinder it. While all developers require foundational knowledge of software development to help them understand the job at hand, AI complements this base level of know-how and helps them build on it far faster than was previously possible.

Previously, the first few years of a junior developer’s career revolved around learning coding and organizational coding conventions. Before the availability of AI coding tools, this was undoubtedly a positive use of time and perhaps even a rite of passage. But AI can assist in onboarding junior developers more quickly, as a supportive learning tool. For example, using AI to explain organizational coding patterns and practices in natural language, or discovering documentation like naming standards and other conventions or expectations.

AI can help free developers at any level gain a more rounded view of the challenge they are trying to solve and the routes they can take to solve it. Rather than looking at a generic code sample, AI can provide explanations and examples in the context of their problem, enabling them to learn. That can only make them more valuable to organizations.

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Additionally, AI tools should be used alongside the usual checks and balances. Committing any code, whether supported by AI tools or not, should trigger the same guardrails across the organization. For example, code should still go through pull requests (PRs), be peer-reviewed by colleagues and remain subject to the necessary builds, tests and security checks. The code review process in the PR is another learning opportunity between the developer and their colleagues. Introducing AI-powered software development should make the development process refreshingly different but reassuringly similar.

Businesses must view AI as an important tool to support developers, alongside the existing, traditional support networks they use. Despite the rise of AI tools, it’s also important that developers continue to have access to programs and courses to help them learn and understand the foundations and principles of software development, as well as mentoring from senior members of their team. These are critical support functions that will always remain important. They are entirely complementary to encouraging developers to use the tools they want and need to do their best work.

Organizations considering restricting the use of AI tools to certain levels in their development teams are fundamentally missing a vital point: AI coding tools are not just for the production of code, they are there to accelerate an existing process, help developers learn and drive innovation. 

About the Author(s)

Chris Reddington

Senior product manager of strategy for developer relations, GitHub, GitHub

Chris is a passionate developer advocate on GitHub's DevRel team. He empowers execs, engineering leads and teams from the smallest of startups to established enterprises, helping them love GitHub and unlock their software engineering potential.

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