The Rise of the Deep Agent: What’s Inside Your Coding Agent

How Deep Agent Architecture Enables Reliable, Production-Ready AI Coding Agents

AI coding tools like Claude Code and Cursor are rapidly evolving from simple autocomplete assistants into autonomous, multi-step problem solvers. While adoption is accelerating across millions of developers, most custom agent projects still struggle to reach production. What separates experimental builds from reliable systems?

This session, presented by SambaNova, dives into the foundations of Deep Agent Architecture and explains what makes a “deep agent” fundamentally different from a traditional chatbot or basic LLM chain. You’ll gain a clear understanding of the structural patterns that power modern coding agents – and why orchestration, memory, tools, evaluation, and agent skills form the backbone of production-ready AI agents.

Through practical examples and a live demo, you’ll see how advanced agents decide what to do next, maintain long-term context, and coordinate multiple components without losing track. You’ll also learn a structured 6-step development process designed to help teams design, evaluate, and deploy agents with confidence.

By the end of the session, you’ll have both a strong conceptual framework and actionable guidance for implementing Deep Agent Architecture in real-world AI systems.

🛠️ What We’ll Cover:

• Core Concepts – What defines a deep agent and how it differs from simple chatbots

• Architectural Foundations – The 5 Pillars behind Deep Agent Architecture

• Decision-Making Patterns – How agents plan, reason, and select next actions

• Multi-Agent Coordination – When distributed agent systems improve reliability

• Evaluation Strategies – The Smart Intern Test and structured validation methods

• Live Demo – Comparing a basic chain versus a full agent on the same task, featuring SambaNova technology

• Production Roadmap – A 6-step process for building reliable AI agents

🔍 Why Attend?

• Understand why many agent systems fail before production

• Learn practical Deep Agent Architecture patterns used in real systems

• See a hands-on comparison between simple and advanced agent workflows, powered by SambaNova

• Leave with a clear roadmap for building production-ready AI agents