The automation era gave us systems that follow rules. The agentic era gives us systems that pursue objectives. This distinction sounds subtle. It changes everything.
Traditional automation is deterministic: if X, then Y. Agentic systems are probabilistic: given objective Z, find the best path. This fundamental shift requires new architectural patterns, new governance models, and new ways of thinking about human-machine collaboration.
What Makes a System “Agentic”?
An agentic system has four defining characteristics:
- Goal-oriented: It works toward objectives, not just follows instructions
- Autonomous: It can plan, execute, and adapt without step-by-step guidance
- Tool-using: It can invoke external tools, APIs, and services to achieve its goals
- Self-correcting: It can evaluate its own outputs and adjust its approach
The Architecture of Agency
Building agentic systems requires rethinking several foundational assumptions about software architecture. The whitepaper details the orchestration patterns, memory architectures, and safety mechanisms that make autonomous systems practical and reliable.
Organisational Implications
When software can act autonomously, the role of every knowledge worker changes. This isn’t about replacement — it’s about redesigning the interface between human direction and machine execution.
The organisations that deploy agentic systems effectively will fundamentally outperform those that don’t. Not because the technology is better, but because the cognitive architecture is better.
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