Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal

Temporal's Value Proposition for Agentic AI - Temporal positions itself as a solution for building reliable and scalable agentic AI applications, addressing the inherent unreliability of LLMs and the complexity of distributed systems [2][3][7] - The company's mission is to outsource reliability and scalability, allowing developers to focus on business logic [7][8] - Temporal offers language-idiomatic SDKs and handles plumbing code, ensuring reliable process execution and providing guardrails [8][9] - Customers are currently running agents on Temporal at scale in production, experiencing agility and speed in development [12][13] Technical Architecture and Impact - Temporal introduces a workflow abstraction to simplify complex interactions between LLMs, chat history databases, and tools [15][17] - Using Temporal can accelerate development, with case studies showing feature delivery velocity improvements of over 6x [18] - Temporal Cloud handles the heavy lifting of reliability and scalability, while the agent's code runs in the user's environment [28][29] - Temporal is an open-source product, offering a code exchange for developers to explore and utilize [31] Customer Success and Adoption - Dust and other companies are building agents on top of Temporal [11] - Gorgeous, a customer service provider for brands like Reebok and Timbuktu, uses AI agents built on Temporal [11][12] - A consumer application customer is scaling with events without needing to handle scale logic [19]