The Problem with Agent Reliability
Conventional AI agents often fail unpredictably. Relying solely on prompting leads to inconsistent state management and unreliable interactions with external tools or APIs.
The Proxy Base Agent (PBA) provides engineered reliability. It employs an explicit state machine architecture, enforced at runtime by the Proxy Structuring Engine, to guide LLM behavior. This defines agent logic (e.g., Plan ➔ Act) and ensures dependable execution.
How It Works
State Machine Logic - Agent behavior (Thinking, Tool Call states) is defined via state machines. Nested structures enforce rules within each state.
Runtime Enforcement - The Proxy Structuring Engine guarantees valid state transitions and structurally correct outputs (e.g., tool calls) during generation.
Dynamic Capabilities - Connecting to Model Context Protocol servers adds tools by rebuilding relevant state machine components at runtime.
Observable Control - Explicit states for planning and action provide transparency and allow for predictable agent behavior.
Applications
Trustworthy Automation - Build agents that reliably complete complex, multi-step tasks without unpredictable failures.
Secure Tool Interaction - Integrate safely with APIs and external systems, preventing errors from malformed requests.
Custom Agent Systems - Develop specialized agents tailored to specific domains, proprietary data, or unique workflows.
Personalized AI - Enable agents that run locally, maintain state consistently, and adapt to individual needs.
Benefits
Dependable Execution - Move from unreliable prompting to engineered reliability for critical tasks.
Simplified Development - Build complex agents faster by relying on guaranteed structural components and predictable execution flow.
Increased Trust & Control - Confidently delegate tasks to AI through observable, controllable, and reliable performance.