Sam Partee, CTO of Arcade AI, explains that building production-grade agentic systems requires moving beyond simple chatbots. He details the critical components for creating reliable, secure, and scalable tools, including rigorous schema management, the principle of least privilege, continuous evaluation, and a crucial distinction between 'exploratory' and 'operational' tools.
Sam Partee, CTO of Arcade, explains the critical gap between AI agents that gather context and those that take secure, real-world actions. He introduces Arcade as a middleware platform that solves complex challenges like user authorization, fine-grained permissions, and token management, enabling developers to build scalable, enterprise-ready agents.
A deep dive into OpenAI's AgentKit, demonstrating how to visually build, deploy, and optimize multi-step, tool-calling agents using Agent Builder, ChatKit, and the integrated Evals platform.
Explore the distinction between LLMs and AI agents, focusing on how agents leverage reasoning, tool calling, and the ReAct prompting framework for autonomous decision-making and task execution in complex business workflows.
A deep dive into the OpenAI Responses API, covering its architecture, advantages over Chat Completions, and practical applications for building persistent, multimodal agents with GPT-5, including live demos on migration and multi-tool workflows.
Alex Salazar, CEO of Arcade, argues that the true value of AI is not in chatbots but in agents that can take real-world actions. He details the primary reasons agents fail to reach production—security, cost, latency, and accuracy—and introduces an "Agent Hierarchy of Needs" as a framework for building robust, production-ready agents. The talk emphasizes a critical shift from exposing raw APIs to building intention-based tools and solving the complex challenge of agent authorization through a delegated model.