6 Skills Developers Should Learn to Stay Ahead of AI

An interesting debate is taking place about the influence of Artificial Intelligence on software engineering.

Some people think that advanced AI systems like ChatGPT will replace most developers’ jobs. Others think AI will enhance developer experiences by taking care of basic tasks.

Whatever the case, AI is here to stay. Instead of worrying about AI, you can hone your skills to work alongside it. Here are some skills you can learn to stay relevant in software development.

1. Software Design

Software design is the process of designing different components of a software system. It illustrates how components will interact and coordinate to produce expected user experiences.

The software design process is dynamic and unique as it varies from one application to another.

Software design allows developers to interrogate the software development process comprehensively. This includes analyzing the system architecture, applications, navigation, and database management system.

After analysis, developers create a blueprint that consolidates everything. These include the steps, modules, objectives, and components. The design also indicates marketing strategies and roll-out timelines to develop the software.

Software design allows developers to translate business plans into software products or services. AI is not yet advanced enough to handle such concepts.

2. System Architecture

System architecture is the structural design of a system. This includes the components, their relationships, and the principles guiding its design. It’s another creative design process that assists developers in building highly scalable apps.

System architecture focuses on the overall structure. It anticipates choices and decisions that maintain quality. While software design focuses on functional requirements, system architecture addresses non-functional requirements.

Non-functional requirements address the future life of the system. They may address issues like the app’s maintainability, scalability, reliability, and system efficiency.

Without a well-defined architecture, developers resort to traditional systems that are challenging to implement and scale. Undesigned architectures result in unorganized source code and poor relationships between components. Such systems are prone to errors.

Applications without a formal architecture are easy to break and difficult to scale. System architecture makes it easy to determine the characteristics of an application. It’s important to understand the components and the entire system fully.

Architecture helps to answer basic questions about the maintenance of the application. These include inquiries on what to prioritize and what to scale back. Prioritizing helps to reduce the over-engineering of unnecessary features and components. The architecture also addresses constraints. These can be legal compliance, cost, market, and standards.

3. Database Design

Database design is the creative process of creating data models. It also includes establishing database relationships and analyzing constraints. AI makes analyzing constraints easier. But the overall structure & design of databases differ from one application to another.

Database engineers must maintain and manage systems databases depending on varying situations to help manage data. Well-structured databases have the following advantages:

• Eliminate redundant data and save disk space.
• Maintain data integrity and data accuracy.
• Easy access to data for internal and external sharing.

The database design process involves analyzing the system requirements. It involves identifying the purpose of the database. Specifically, it establishes the database tables and their components. It also analyzes and organizes the database relationships.

All these concepts vary from one application to another. The database structure can change over time as the system scales up or down.

4. Software Debugging

Analyzing software to figure out where a problem is coming from is a skill that AI is yet to undertake. Developers will still need to learn how to identify and fix issues as they arise.

AI can help provide possible solutions during debugging. Developers can then decide how best to apply the solutions.

Developers need to learn how to use different software and means to debug quickly. Identifying bugs, asserting expectations, and breaking down system failures are important skills.

You can find some good pointers on how to handle the debugging process in this Udacity Software development course:

Text editors, IDEs, and operating systems have built-in features to assist debugging. Developers can deal with these complex application issues while AI takes care of basic functionality.

5. Software Security

Software security is still an issue, even with the emergence of secure systems and practices. With businesses deploying more applications, the number of cyber attacks has increased.

Building software that is safe and secure is still a headache for developers. Clients invest a lot of resources to ensure their systems are safe. This includes hiring experienced cyber techs and acquiring software that limits attacks on systems.

While there are laws and awareness campaigns to tackle cyber attacks, they are still common. Cybercriminals have also advanced their technology. There’s a need for developers to stay on course and innovate security against threats. A single breach can substantially affect a system and its components.

As human reliance on software grows, so do threats. Hackers have become resilient in testing system vulnerabilities. Now more than ever, cybersecurity is a must-have skill for developers. There’s a need to ensure that all systems are safe against new threats.

6. Programming Proficiency

AI programs use popular concepts to write basic programs. Their programs address what already exists online. But when it comes to complex programming, AI still has to advance. It has to generate solutions for novel problems in engineering.

This gives developers an upper hand if they advance their programming skills. Developers can use these skills to foreshadow problems and provide solutions. This will boost creativity in software development.

How Can You Accommodate AI?

The influence of AI in software development is revolutionary. But can it replace developers? Not yet. However, developers can work alongside AI today.

While AI takes care of basic repetitive tasks, developers can focus on complex issues. This allows developers to increase their creative potential in their development process.

AI can speed up the software engineering process while reducing operational costs. If incorporated into computer science, it has the potential to advance technology greatly.

Learning new skills will benefit developers. Working with AI enhances their development experience and improves the quality of output. This is a win for everybody.