As large language models gain traction, innovation is shifting to refined small language models and agentic AI. Techniques like retrieval-augmented generation (RAG) improve LLM outputs, prompting architects to design more accommodating systems. Architects must also embrace AI-assisted development tools, ensuring they enhance efficiency without compromising quality, while considering how citizen developers operate. Environmental sustainability remains a pressing issue, with a focus on reducing the software's carbon footprint, even as strategies to incorporate renewable energy pose challenges. Trends lean towards decentralized decision-making to empower system builders and maintainers, preventing bottlenecks in architectural processes.
Because software architecture decisions always come down to trade-offs, there is never one right way to solve all challenges. For this reason, there has always been a healthy debate among the editors for when a trend should move along the adoption curve.
Architects need to consider AI-assisted development tools, making sure they increase efficiency without decreasing quality. They also need to be aware of how citizen developers will use these tools, replacing low-code solutions.
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