The software industry is undergoing its most significant transformation since the advent of cloud computing. AI is fundamentally changing how we build, operate, and interact with software. As someone who has observed and written about major recent industry shifts from SOA to microservices, and from containers to serverless, I see AI driving an even more profound change.
This isn't just about automating coding tasks or adding chatbots to applications. We're witnessing the emergence of new development paradigms, operational practices, and user interaction models that will reshape how teams are structured and software is consumed.
The full version of this article examines five trends that are already impacting software teams and will become increasingly influential in the years to come. For each trend, we'll explore what's changing, real-world examples, and discuss how different roles – from developers to architects to product managers – can adapt and thrive in this new landscape.
Your next steps should align with your role in software development:
- For developers, hands-on experience with coding assistants like Cursor and GitHub Copilot is the bare minimum. Automating code reviews with tools such as CodeRabbit is another low-hanging fruit. Focus on integrating these tools into your daily workflow by identifying low-risk scenarios where they are effective. If these are not allowed by your employer, use them in your open-source work or side projects and explain to your colleagues the benefits and limitations.
- Operations teams should explore how AI can automate more tasks and reduce the need for human intervention. Then prepare to operate AI-workloads, whether that is only a few calls to external LLMs, or running full agentic systems.
- Architects should focus on understanding end-to-end LLM-powered architectures and how agentic systems fit into enterprise environments. This means going beyond individual AI components to understand how to design reliable, secure systems that leverage AI capabilities while maintaining enterprise-grade quality. The priority should be identifying strategic opportunities within the organization, whether modernizing legacy applications with AI capabilities or designing new AI-native systems from the ground up.
- Technical writers must embrace AI tools as the new word editors. Experiment with many tools, models, and prompts, and focus on automating the writing workflow. The content in the future will be conversational.
- Product managers must track AI trends and their potential impact on product strategy. Study AI-native products to understand how natural language interfaces and AI assistance can enhance user experience.
Designing, operating, and programming as we know it will continue to evolve, but building these foundational skills will prepare you for whatever comes next. Start now because this trend will be here for the next decade.
This content is an excerpt from a recent InfoQ article by Bilgin Ibryam, "AI Trends Disrupting Software Teams".
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