Beyond Code Snippets: AI Software Development Predictions for the Remainder of 2024

Over the past two years, AI software development made strides with the advent of code assistants such as Microsoft Co-Pilot, which are effectively the next generation of code linters. While these tools demonstrated the ability of AI to generate code snippets, AI is still very much in its infancy. Despite the wide-spread concern about rapid development, significant advances are required before AI can transcend its current limitations and empower non-technical users to deploy fully functional applications. This prompts us to contemplate: What progress will be achieved in AI software development during the remainder of 2024?

Bugs & Code Remediation

We’ve all had the difficult conversation with a developer when applications are running smoothly, all of a sudden operations go awry, an unanticipated bug appears and needs to be corrected…immediately. There is a level of confidence that the developer who wrote the code has a broad understanding and will be able to correct the issue. The idea that AI will advance and be able to effectively fix issues in existing software projects or code it has generated is unlikely in the coming months. Proper maintenance is a huge factor in any successful software application and AI has not matured enough to remediate issues. More importantly, how can a human successfully trouble-shoot code written by AI? The development team may not understand the way AI wrote the code originally. Overcoming such challenges will take more time than just the coming year. Human intervention will remain necessary for correcting bugs and gatekeeping maintenance in young products. 

Interface Progress

One notable current hurdle lies in the absence of AI to output vector designs, highlighting a lack of intuitive understanding of user interfaces. We see on the horizon, the progression in AI's capabilities encompassing transforming images into vectors and translating text into React components. This indicates a move towards expanding the scope of AI in front-end development throughout the remainder of 2024 into 2025.

Empowering Non-Technical Users

There are dreams of AI enabling non-technical individuals to build applications without extensive coding knowledge. This would require platforms to write, organize, and structure code. Next, AI would need to deploy the project to the internet and guide users in selecting appropriate databases. This is quite a steep jump from writing fragments of code. 

While basic functionalities are achievable in the coming year, more complex scenarios require further refinement and development. The closest parallel is the evolution of self-driving cars. Do driverless vehicles operate well on an open highway on a dry, sunny day? Yes, absolutely. Can they operate just as well along side-streets on a rainy, dark night? Definitely not. 

AI will remain a tool for users with existing knowledge on writing code. It effectively gives the educated user a starting point or serves as a partner to assist in the process. A developer can leverage AI to reduce review times, streamlining the development cycle and accelerating time-to-market. Less seasoned coders will benefit from AI by receiving suggestions for curated code, mitigating the risk of security vulnerabilities and avoiding mistakes. As AI continues to evolve, its role in collaboration with human developers will likely expand, contributing to a more symbiotic relationship between technology and human expertise in coding.

Scalability Challenges

AI currently struggles to conceptualize ideas and design complete systems. Beyond that as AI evolves, scalability emerges as a critical concern. If an AI-generated codebase gains one million users, can the initial code adapt and scale effectively? Doubtful AI will be writing such sophisticated code in 2024. However, it is likely that AI will support developers by structuring code into modules, preventing duplication, and supporting testability. This will help coders improve the quality of their code at a more rapid pace of development, which will eventually support bringing it to scale.

DevOps Landscape

We see foreshadowing of AI-driven tools for auto scaling and configuration, streamlining the development and deployment processes.

Midway through 2024, the landscape of AI in software development holds both promise and challenges. The journey towards enabling non-technical users to craft applications seamlessly, coupled with addressing scalability and maintenance concerns, will need more time to evolve. While the industry may not witness a complete transformation, incremental progress is certain, paving the way for a future where AI plays an increasingly integral role in the software development lifecycle.