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InfoQ Homepage Guides Agentic AI Architecture

Architecture & Design

Agentic AI Architecture

The IT industry is changing before our very eyes. With AI entering the software architecture and development landscape, whether we like it or not, we are set to be taken on a roller coaster, the likes of which we haven’t seen since the advent of microservices and cloud-native computing. If the last decade was spent mostly on mastering and optimizing the cloud and micro- or nano-scale service-oriented architecture, the next decade will likely be spent figuring out how to master AI for building a new generation of IT systems.

In this eMag, we try to establish agentic AI architecture as a new type of software architecture that will likely dominate the industry for years to come. The articles, written by industry experts, cover various elements and aspects of agentic AI architecture. We aim to present the latest trends and developments shaping the new type of architecture as it enters the mainstream.

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The InfoQ Agentic AI Architecture eMag includes:

  • "From Microservice to Agents: The Next Evolution of Distributed Systems" by Mallika Rao, discusses the shift in distributed systems architecture, driven by large language models (LLMs) and reasoning systems. Mallika argues that agentic AI architectures focus on decomposing decisions, much like microservice architectures decompose functionality. Additionally, the author shares initial architectural patterns and failure modes introduced by the new paradigm, highlighting the increased importance of observability and reliability in these new types of agentic systems.
  • Karthik Ramgopal covers "The Evolution of Agentic Harnesses: From Chains to Graph to Code", in which he describes how building agents that interact with large language models has evolved in recent years from ad hoc experiments to resilient, production-grade architectures. Karthik also shares best practices and battle-tested advice for robust agentic AI architectures, drawn from his experience building several agentic solutions.
  • "Systemic Approach to Memory, Knowledge, and Context in the Agentic AI Architectures" by Adi Polak, delves into the knowledge layer of agentic AI and introduces context engineering as a new discipline that has emerged in the agentic AI space. Adi argues that context management should be tuned to the system it supports and discusses key elements and mechanisms for incorporating high-quality context data into LLM prompts to reduce or eliminate hallucinations.
  • Subash Natarajan and Ahilan Ponnusamy present the "Agentic AI Architecture Framework for Enterprises," which describes a three-tier framework for designing and delivering agentic AI systems, covering many distinct elements, solutions, and patterns. Authors then offer industry-specific examples and share implementation strategies and guiding principles required for successful adoption.
  • "Agentic AI Architecture: Current Challenges and Future Opportunities" by Rafał Gancarz, wraps up the eMag's overarching topic by examining how agentic AI architecture, as a new generation of software architecture, will change the IT industry as we know it today. In the article, Rafał connects the dots and cover a broad range of areas and architectural aspects that will need to adapt to address the challenges posed by agentic AI.

While it’s impossible to characterize the new type of software architecture fully at this point, we hope this eMag offers useful insights into how the agentic AI space will shape the future of the IT industry in the coming years. Agentic AI Architecture is still in its infancy, but we hope to track how it evolves and matures and cover all key milestones and breakthroughs in the future.

Your feedback is invaluable to us. We eagerly await your thoughts at at editors@infoq.com or on LinkedIn, Bluesky or X.

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