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 intelligent ETL pipeline agent that uses LLMs to infer schemas from messy data, transform records with natural language instructions, and validate data quality at each stage.
Learn how to build safety evaluation pipelines for AI agents including red team datasets, automated harm scanning, policy compliance scoring, and production safety monitoring.
Learn how to design normalized database schemas for AI agent systems that store conversations, messages, tool calls, and metadata with proper indexing and query patterns for production workloads.
Learn how to export AI agent models to ONNX format, optimize them with ONNX Runtime, and deploy cross-platform for consistent inference performance on any hardware.
Build a PDF processing agent that extracts text, tables, and charts from documents using Python. Covers page-level parsing, table detection with pdfplumber, chart analysis with vision models, and structured output generation.
Build an AI agent that generates professional documents like contracts, proposals, and reports by combining template engines, dynamic data injection, and PDF rendering with version tracking.
Build an AI agent that extracts key concepts from study material, generates effective flashcards, and schedules reviews using the SM-2 algorithm with performance analytics.
Learn how to build an AI agent that scans for CVEs in dependencies, audits container images, generates fix suggestions with priority scoring, and tracks remediation progress.
