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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Implement robust ambiguity handling in AI agents with detection strategies, clarifying question design, confirmation patterns, smart defaults, and disambiguation techniques.
Master core Kubernetes concepts every AI engineer needs — Pods, Deployments, Services, and ReplicaSets — with practical YAML manifests for deploying AI agent workloads to production clusters.
A hands-on guide to the official OpenAI TypeScript SDK. Learn how to set up the client, create chat completions, implement function calling with tool definitions, and stream responses in a Node.js application.
Learn how Corrective RAG (CRAG) adds relevance scoring, re-retrieval, and web search fallback to catch and fix bad retrievals before they reach the user. Full Python implementation included.
Implement multi-tenant authentication for AI agent platforms using FastAPI. Learn tenant identification, JWT claims design, row-level data isolation, and cross-tenant prevention strategies.
Master the art of composing multi-layer prompts dynamically. Learn composition patterns, priority ordering strategies, token budget allocation, and techniques for building modular prompt pipelines.
Connect your AI agent to Google Workspace for automated document creation in Google Docs, data manipulation in Sheets, and intelligent email drafting in Gmail using Google APIs and OAuth2 authentication.
Learn how to apply time series forecasting to AI agent data, predict conversation volume and cost trends, detect seasonality patterns, and build capacity planning models that keep your agents running smoothly.
