AI Agent Workflows and Architectures Masterclass
Blog post from Arize
The AI Agents Masterclass by Jerry Liu and Jason Lopatecki delves into workflows and architectures of AI agents. Event-based systems and graph-based systems are two primary approaches to building AI agents, each with its own advantages and challenges. State management is a crucial aspect in both architectural styles. Production engineering for AI agents involves observability and debugging strategies, as well as performance optimization focusing on areas like routing accuracy, token usage efficiency, response latency, and error handling. The landscape of AI agents is maturing with teams prioritizing focused, reliable components over general autonomy, emphasizing the need to start simple and expand based on real-world usage patterns.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| AI Agents | 14 | 1,063 | 162 | 70 | +48% |
| LLM | 5 | 2,668 | 436 | 137 | -7% |
| Observability | 3 | 1,716 | 298 | 95 | +16% |
| Harness engineering | 2 | 7 | 5 | 5 | +17% |
| Real-time | 1 | 3,091 | 773 | 211 | -1% |
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