Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Build an AI agent that processes inbound emails, detects intent, generates contextual responses, and manages threaded conversations using FastAPI and IMAP integration.
Build an AI agent that ingests monitoring alerts, classifies severity, executes runbook steps automatically, and escalates critical issues to on-call engineers.
Build an AI calendar agent that prepares meeting briefs, generates post-meeting summaries with action items, and sends automated follow-up emails using Google Calendar webhooks.
Build an AI agent that processes web form submissions, validates data, generates personalized responses, and routes entries to CRM and notification systems using FastAPI.
Build resilient event replay infrastructure and dead letter queue management for AI agent systems with proper logging, recovery patterns, and operational tooling in Python.
Learn how to systematically migrate from rule-based chatbots to LLM-powered AI agents. Covers assessment, parallel running, phased migration, and quality comparison techniques.
A hands-on guide to migrating AI agent code from LangChain to the OpenAI Agents SDK. Covers concept mapping, code translation, testing strategies, and gradual migration paths.
Learn how to safely upgrade LLM models in production systems. Covers evaluation frameworks, prompt adaptation, cost impact analysis, and progressive rollout strategies.
