Artificial intelligence (AI) is changing how we approach software development. With all the buzz surrounding AI in the tech world, software teams are especially excited about using large language models (LLMs) to generate code. This shift is seen as a game-changer for boosting programmer productivity.
Take Simon Dawson, the head of engineering at Atom Bank. He mentioned recently that AI isn’t just about coding; it can also be a powerful tool for training and identifying promising junior developers. His team needs more senior engineers, so they’re focused on nurturing juniors to advance their careers more quickly.
AI acts like an advanced autocomplete for writing code, but it’s much more capable. Developers can input natural language prompts to get code generated, making it easier for people with limited programming backgrounds to create functional applications. This technology reduces the steep learning curve typically associated with software development. It also helps in documenting code and integrating different IT systems.
Another interesting aspect is that AI opens doors for non-programmers to become “citizen developers.” Low-code and no-code platforms allow users to turn their plain language requests into code. While these tools might not produce fully functional applications right away, they spark creativity and free up developers to focus on more complex tasks.
This year, Computer Weekly has explored two more significant trends in software. First, there’s Java, which will celebrate its 30th anniversary in 2025. Thanks to Java’s “write once, run anywhere” philosophy, its applications adapt to various hardware at execution time. Experts suggest that applications optimized at runtime through Java’s just-in-time compiler can be more efficient than hand-coded versions.
However, the Java landscape isn’t without its problems. Changes to the licensing of Java and the Java Development Kit (JDK) raise concerns for developers.
The second major trend involves Linux and open-source software. A recent decision to exclude Russian developers from the Linux kernel maintainers list underscores how geopolitics affects open-source collaboration. US sanctions could jeopardize global teamwork and might lead to intrusive background checks for software engineers across various industries.
Here are some of the top stories in software development for 2024:
1. As legal concerns grow, how can development teams tackle GenAI risks effectively?
2. LMAX Group has a tight eight-nanosecond latency on its applications. Andrew Phillips, the CTO, shares their strategy for achieving this.
3. The rise of the citizen developer: What insights do AI and data experts have on the impact of large language models?
4. The success of corporate AI strategies hinges on data quality. What steps can companies take to ensure they’re starting off right?
5. While open-source software offers cost savings and transparency, what challenges should businesses be aware of?
6. Cloud-native models are excellent for new workloads, but legacy IT systems require tailored approaches, leading many IT leaders to hybrid cloud solutions.
7. Developers need guidance on using large language models securely and cost-effectively in their applications.
8. IT leaders are exploring ways to minimize the environmental impact of software development.
9. Interest in OpenJDK and its commercial support has surged as Oracle Java SE becomes pricier.
10. What role do software-defined wide area networks play in modern cloud-native IT architecture?