Agent Architectures: Control Loops, State & Planning › Key Design Parameters

The key parameters for our agent architecture are:

• max_iterations: Maximum number of loop cycles before forced termination. This acts as a necessary safety guardrail, preventing infinite loops and controlling computation costs. Setting it too low may cause the agent to terminate prematurely before solving complex problems; too high risks excessive costs if the agent enters an unproductive cycle. Typical values range from 3 for simple tasks to 20 or more for complex research or debugging workflows.

• tools: Dictionary of available functions the agent can invoke. Each entry specifies the function and description as well as the parameter schema. The quality of tool descriptions materially impacts agent performance, because these descriptions form part of the prompt that guides the LLM's reasoning about which tool to use. Poorly described tools lead to confusion and incorrect selections.

• working_memory: Dictionary storing intermediate results and extracted facts across iterations, letting stateful behavior. The structure and content of working memory determine what information the agent retains for future reasoning. Well-designed schemas organize information by type and priority, while poor schemas allow important details to be buried under irrelevant data.

• current_plan: Ordered list of planned actions guiding the agent's execution strategy, updated as tasks progress. Dynamic plan updating allows the agent to adapt to new information while maintaining strategic coherence.

• steps: Complete history of observations and thoughts followed by actions and results, giving conversation context. This chronological record is the agent's episodic memory for the current session. This makes it possible to avoid redundant actions and justify its decisions based on prior reasoning.