To develop a detailed piece, you must integrate several foundational building blocks:
: The blocking agent needs access to the current "state" (conversation history) to identify context-specific risks that might not be apparent in a single message. blocking agent
: When a block occurs, the system must handle it gracefully—such as providing a standardized "I cannot fulfill this request" response—rather than just crashing or failing silently. Key Patterns in Modern Agentic Systems How to Build Reliable AI Agents (without the hype) To develop a detailed piece, you must integrate
and every week there is a new fire ship video dropping something new where you're like "Oh shit do we now also need to know this?" YouTube·Dave Ebbelaar Its core purpose is to prevent "hallucinations," enforce
Developing a "blocking agent"—more commonly known as a or middleware agent —is the process of building a specialized AI component designed to monitor, filter, and intervene in the interactions of a primary AI agent. Its core purpose is to prevent "hallucinations," enforce safety policies, and block unauthorized actions (like leaking credentials) before they reach the user or the external environment. Core Architecture for a Blocking Agent
: A blocking agent must return deterministic results (e.g., "Pass" or "Fail"). For example, a "ContentFilterMiddleware" might check for banned keywords and return a jump_to: "end" signal to skip further processing if a violation occurs.
: This is the "brain" that analyzes incoming data against your rules. In production systems, this often involves a smaller, faster model (like GPT-4o-mini or Claude Haiku) optimized specifically for classification and risk detection.