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An overview of advanced AI agentic systems, their architecture, interaction methods, and development principles. Explore how AI agents interact with computers through graphical user interfaces and directly with complex physical environments via multimodal inputs. Dive deep showcasing various examples like Claude CLI and Gemini CLI, to facilitate intelligent, collaborative coding and task automation. Essential patterns for building robust agents, including prompt chaining for task decomposition, dynamic routing for decision-making, parallelisation for efficiency, and tool use for external interactions. Key concepts such as multimodality, grounding, and transformers are defined, alongside strategies for memory management, learning and adaptation, and multi-agent collaboration via protocols like A2A. The importance of human-in-the-loop (HITL) processes, resource-aware optimisation, and rigorous evaluation and monitoring for ethical and effective AI deployment is also highlighted, ensuring these intelligent systems are both powerful and reliable.

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Deep dive into AI agentic systems, their architecture, interaction methods, and development principles. How to build intelligent systems that are both powerful and reliable. Patterns for building robust agents. Key concepts and strategies and protocols like A2A. human-in-the-loop (HITL). The need for rigorous evaluation and monitoring for ethical and effective AI deployment .

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