GenAI Engineering: From the Myth of Agents to Architecture

The article analyzes the transition from the marketing myth of 'autonomous agents' to a rigorous engineering approach in GenAI systems. The author argues that LLM models are not independent intellects, but non-deterministic system components (similar to an unstable API) that require strict control, validation, and pattern-based architecture. Citing Tim O'Brien's concepts and MIT NANDA reports, the text points to the competency gap between demo showcases and production. The main thesis is the necessity of treating GenAI as a stress test for organizational architecture—this technology does not fix chaos in data and processes, but rather highlights it. The solution is the application of Pattern Prompting and known software engineering patterns to create predictable and secure enterprise-grade systems.