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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Learn how to build an AI agent that orchestrates CI/CD pipelines, performs risk assessment on deployments, analyzes canary metrics, and triggers automatic rollbacks when quality degrades.
Build an AI agent that aggregates logs from multiple services, extracts patterns using clustering and LLM analysis, correlates events across systems, and generates actionable alerts.
Build an AI agent that analyzes cloud resource usage across AWS, GCP, and Azure, identifies waste, recommends rightsizing, and suggests reserved instance purchases for maximum savings.
Build an AI agent that monitors PostgreSQL performance, detects slow queries, recommends optimal indexes, schedules vacuum operations, and plans for capacity growth.
Build an AI agent that analyzes infrastructure usage trends, forecasts resource exhaustion, sets dynamic threshold alerts, and generates scaling recommendations before outages occur.
Learn how to build an AI agent that designs chaos experiments, controls blast radius, injects faults into production systems, observes behavior, and verifies automated recovery.
Build an AI agent that parses human-written runbooks, converts them into executable automation workflows with verification steps, handles edge cases, and supports safe rollback.
Learn how to implement Named Entity Recognition in AI agent pipelines using spaCy and LLMs, covering entity types, custom entity training, and real-time extraction strategies.
