AI Dev 26 x SF | Melissa Herrera: Your Agents Should Be Durable

DeepLearningAI · Beginner ·🤖 AI Agents & Automation ·1h ago
Building AI agents is easy — but making them production-ready is hard. AI agents in production face infrastructure failures, API timeouts, and rate limits that demos never show. This talk by Temporal's Melissa Herrera demonstrates how durable execution transforms fragile agent prototypes into production-ready systems. Through live demos and real-world examples, attendees learned how Temporal's Workflow orchestration handles crash recovery, automatic retries, long-running tasks, and state management — letting you write simple code while getting enterprise-grade reliability for your AI agents.
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

⚡
The Folly of Global AI Platforms: Or How We Built a System That Actually Works in Cameroon
Learn how to build a functional AI system in a resource-constrained environment like Cameroon, and the importance of considering local context and infrastructure in AI development
Dev.to · Lisa Zulu
 ⚡
The peer-reviewed AI systems running full scientific research projects
AI systems are now capable of running full scientific research projects, publishing peer-reviewed papers in top journals like Nature
Medium · AI
 ⚡
The peer-reviewed AI systems running full scientific research projects
Learn about AI systems that can run full scientific research projects, a breakthrough with potential to accelerate discovery
Medium · Programming
 ⚡
From Code to Cloud: 3 Labs for Deploying Your AI Agent
Deploy your AI agent to the cloud with 3 practical labs
Dev.to · Shir Meir Lador
Up next
Agent-first workflows from prompt to production
Google Cloud Tech
Watch →