WellSky’s Engineering team have observed a remarkable advancement in artificial intelligence (AI) over the past year, transitioning from basic chatbots to addressing intricate challenges. When developed with precision, AI now has abilities to engage in Engineering collaboration, strategizing, and specialization akin to a team of human experts. This brings us to the concept of Agentic AI Architecture, which represents a significant evolution in how we construct intelligent systems.
Historically, many software solutions have utilized architects as strategic assets, applying contemporary software principles. In the realm of AI-driven solutions, we are witnessing the emergence of novel assets and architectural principles that are reshaping the landscape. This evolution is enhancing fundamental AI processes, such as Retrieval-Augmented Generation (RAG), where an AI model retrieves information from a knowledge base to produce more precise responses.
The distinguishing factor of successful AI solutions now lies in the optimization of Agentic RAG and Self-RAG. In these frameworks, an orchestrating AI agent dissects a problem into smaller tasks, plans multiple retrieval steps, poses follow-up questions, and even evaluates its own responses to promote accuracy.
This transformation is paving the way for sophisticated multi-agent systems, where numerous specialized AI agents collaborate effectively. Envision a team of experts: one conducting research, another writing code, and a third performing tests. This is precisely what multi-agent collaboration facilitates – specialization and explicit control. We are beginning to observe increased efficiency in addressing challenges with diverse requirements, as agents can delegate tasks, work in parallel, and manage state effectively.
When collaborating with independent AI agents, each possesses its own unique prompt, large language model (LLM), and tools.
When discussing "multi-agent" systems, we refer to multiple independent actors powered by LLMs, interconnected in a specific manner. They share a common state.
As the number of agents increases, it may become more effective to distribute work hierarchically.
WellSky’s engineering teams have reported productivity improvements by adopting this paradigm. This advancement is not solely about accelerating output; it also involves addressing problems that were once considered too complex for AI, such as modernizing intricate legacy software systems by segmenting the processes of normalization and perception, translation, and validation into manageable tasks for specialized agents.
Limiting agents in their context, while designing segmented and parallel AI workflows, creates a more grounded environment of increased confidence. However, it is a large upstream responsibility which requires frequent regulation from humans in the loop to ensure an accurate evolution of generated artifacts.
A particularly intriguing development, as highlighted in recent designs, is the emergence of an "architect agent." This agent does not perform the core tasks but instead guides the orchestrators and supervisors. It identifies patterns, proposes design methodologies, flags ambiguities, and directs tasks, essentially enhancing human judgment across extensive, tedious, and error-prone activities. This approach does not aim to replace human architects but rather to augment and scale our expertise, automating the components that hinder our efficiency and allowing us to concentrate on high-level decision-making.
For architects who may be reading this, and I count myself among them, you may wonder if these types of agents signify a threat to your profession. However, I have come to view it differently:
“It is not about replacing me as the architect. It is about scaling my judgment across extensive, tedious, and error-prone tasks. I am not automating away architecture. I am automating away the parts that slow me down.”
The era of agentic AI has arrived, heralding a future where intelligent agents collaborate seamlessly to unlock unprecedented levels of productivity and innovation. This represents a fundamental architectural shift that will empower us to construct more robust, scalable, and intelligent systems for the future.
