Prompt Engineering & Loop Engineering, Clearly Explained!

Strix is an open-source AI agent framework designed to automate penetration testing for modern applications. It addresses security gaps that traditional CI/CD pipelines, unit tests, and observability tools often miss, such as broken access control and business logic flaws. By crawling live applications and dynamically probing abuse paths, Strix simulates adversarial behavior to identify vulnerabilities before they are exploited. The tool has already identified over 600 verified vulnerabilities across hundreds of companies and open-source repositories. The text explains the evolution of AI agents from simple 'inner loops' to automated 'outer loops.' While the inner loop, exemplified by the ReAct pattern, handles tool calls and model execution, the outer loop traditionally requires human intervention for prompting and error correction. Modern loop engineering aims to automate this outer layer, allowing systems to trigger on events and run autonomously until tasks are completed. However, this transition necessitates robust verification methods, context management, and cost controls to replace human oversight effectively. Corrective RAG (CRAG) is an agentic workflow designed to improve the reliability of RAG systems by introducing a self-assessment step for retrieved documents. The process involves searching a vector database, evaluating context relevance via an LLM, and falling back to a web search if the initial context is insufficient. This implementation utilizes LlamaIndex for orchestration, Milvus for vector storage, and Firecrawl for web scraping, with CometML Opik providing tracing and monitoring.