What happened
The text explains that microservices helped break monolithic applications into independent services, with clear boundaries, defined APIs and separate evolution. For many organisations, this became the dominant model for large-scale distributed systems.
The new approach, driven by large language models and reasoning systems, shifts the focus to decision decomposition. Instead of following a fixed flow, systems choose actions, tools and reasoning sequences at runtime.
According to the article, this brings more adaptability and a better ability to handle ambiguous inputs, but it also increases complexity. Observability, reliability and context management become central concerns, and patterns emerge such as separating planning from execution, specialising agents and embedding evaluation in execution loops.
Key points
- Microservices split functions across independent services.
- Agentic AI distributes decisions, not just tasks.
- Behaviour now depends on runtime context.
- Observability and reliability become harder to ensure.
- New patterns emerge to manage complexity and variability.
Why it matters for your organisation
For companies and public bodies, the shift means rethinking how complex systems are designed, monitored and governed. When execution is no longer fully predictable, the ability to explain decisions, trace problems and control outcomes becomes even more important.