You're navigating the ever-evolving landscape of software design. What trends should you keep an eye on?

My recommendation is we all embrace Java and no longer evolve our software. That way when the AI overlords show up, they’ll hate their language so much they’ll create a self destruct sequence. Ironically, as it executes, there will be a heap error and it will stack dump four million lines long. Once humanity is saved—you’re welcome.

I think personalization is one area where integrating AI can greatly help. A user must have a more personalized experience. AI analyzes vast amounts of user data, including behavior, preferences, and interactions, to identify patterns and trends. By continually learning and adapting, AI ensures a dynamic, user-centric experience that evolves with each user's needs.

My job involves leading Innovation and Emerging tech teams & thought leadership for Fortune10s to SMBs across industries. I found it is critical to think how functional problems can be solved, rather than focusing on tech to begin with. Being a technologist restricts your thought process to how a problem can be solved in the technical realm of your specialized tech. But developing a techno-functional bridge capability is key for long term sustained value addition to any org or client. It is very rare that one tech will solve a biz problem, so there are many ways & techno combos to solve a problem. Tech can then be applied to a solution in many ways. Focus on AI, GenAI, Cloud Native, Security, ZeroTrust, Data Trends, XR.

AI integration is one of the hot new trends in software design. With the advent of copilot for everything, every organization is planning to build copilot for their enterprise application.

AI integration significantly enhances software design by improving user experience, automating development processes, and enabling intelligent decision-making. While there are significant benefits, AI integration requires careful consideration of data privacy, bias, and transparency to ensure responsible and fair use. If put to proper use, it allows for personalised interactions, automated code generation, and efficient testing. AI enhances security through real-time threat detection and fraud prevention, optimises performance, and manages data more effectively. It also fosters collaboration with smart assistants and innovative product features like computer vision and machine learning models.

Usability of application depends on its availability, which intern depends on a good DevOps setup. Application change deployment and testing should be done with a CI/CD setup.

User experience is one of the major differentiators for application. Application development goal should be to provide maximum functionality with minimum complexity in user interface. The best UX today is AI chatbot with multi modal user input.

Progressive Web Apps (PWAs): PWAs offer a more app-like experience on the web, combining the best features of web and mobile applications, such as offline access and push notifications. Low-Code/No-Code Platforms: These platforms enable rapid development with minimal coding, allowing non-developers to build applications and speeding up development processes.

Adopting low-code platform is a great way to speed up development, while minimizing defects. Nowadays low-code platforms are capable enough to build complex applications that used to require pro-code.

I can tell you about this. For 3 years I have been developing a low-code code generator to increase the productivity of my commercial developments, giving me the ability to make quick deliveries, reduce costs and get less tired. The generator currently fires in C#, .NET and Blazor, but my idea is promising: to add all the languages, frameworks and libraries out there to my generator and have it widely used for the initial configuration of any project. Here is an example of the capacity of this generator: 2 days ago I fired 22,000 lines of code to form CRUDs for 11 tables that I needed to add to my professional site, incredible, right?

Microservices Architecture: The trend toward microservices continues to grow, as it allows for more scalable and maintainable systems by breaking down applications into smaller, loosely coupled services. Serverless Computing: Serverless architectures, such as AWS Lambda or Azure Functions, are becoming more popular. They allow developers to focus on code without managing the underlying infrastructure, leading to greater scalability and cost efficiency. Containers (e.g., Docker) and container orchestration platforms like Kubernetes are widely adopted for their efficiency in managing microservices and scaling applications. Edge Computing: It involves processing data closer to where it’s generated to reduce latency and improve performance.

Building cloud native applications help offload maximum manageability of application to the cloud provider and increase productivity significantly. Cloud native application development also has the advantage of high Service Level Agreement (SLA) from the cloud provider, which helps increase availability of the application.

Designing for mobility between clouds is very helpful. You never know when one provider’s reliability, pricing or regional availability could become an issue over time.

Security is a very crucial aspect of building software. Some key aspects include implementing robust authentication and authorization mechanisms, encrypting data in transit and at rest, and conducting regular security testing and audits. Secure coding practices should be followed to prevent common vulnerabilities. Additionally, incorporating security by design principles ensures that security considerations are integrated into every phase of the software development lifecycle, from planning and design to deployment and maintenance, ultimately safeguarding the integrity, confidentiality, and availability of software systems.