Making Sense of AI Agents Hype: Adoption, Architectures, and Takeaways from Practitioners
This work provides insights for practitioners on how companies implement AI agents, but it is incremental as it synthesizes existing knowledge without introducing new methods.
The authors tackled the problem of understanding real-world industrial practices in AI agent design by reviewing 138 practitioner conference talks to examine adoption patterns, architectural strategies, and application domains.
To support practitioners in understanding how agentic systems are designed in real-world industrial practice, we present a review of practitioner conference talks on AI agents. We analyzed 138 recorded talks to examine how companies adopt agent-based architectures (Objective 1), identify recurring architectural strategies and patterns (Objective 2), and analyze application domains and technologies used to implement and operate LLM-driven agentic systems (Objective 3).