Cameron Rohn discusses sharing instructions and points developers to online tutorials for step-by-step guidance.

Tom Spencer highlights three different design patterns, showcasing a breakdown by workflow to structure development.

Introduce an open version demonstration replicating computer use examples for clarity.

When too many tools are configured, take screenshots and annotate which tools to use.

Leverage sub-agents within your architecture to break down and manage complex tasks.

Question if your initial thoughts are correct to prevent flawed designs.

Actively explore the possibility of being wrong to refine your agent design.

Exploring specialized environments like LangChain to focus solely on large language model executions.

Tom discusses methods for effectively saving context between agent interactions to improve continuity and performance.

Cameron compares agent architectures to microservices to emphasize the need for modular, collaborative agent design.

Using the MCP framework to streamline authentication and authorization when designing custom agents.

They explore various design patterns for Langgraph agents, including the agent-to-agent (A2A) pattern.

Imagine a node diagram where each node connects to every other node, showcasing relationship complexity.

Presentation of a diagram illustrating key components of agent architectures.

This segment delves into the concept of land graphs and their significance in AI architectures.

Documentation includes a diagram illustrating the agent architecture defined as a supervisor pattern, crucial for understanding research agents.

The debate highlights that selecting the right agent architecture depends on the specific task context rather than a one-size-fits-all model.

Each agent in the swarm is aware of every other agent and can delegate tasks, prompting considerations about agent-to-agent interactions.

In a swarm architecture, every agent has access to every other agent to enable full collaboration.

Tom discusses the complexities and core requirements necessary for long-running multi-agent architectures.