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Configure CrewAI agents to use different LLM providers including Anthropic Claude, local Ollama models, and Azure OpenAI, with model parameter tuning and fallback strategies.
Create configuration snapshots for reproducible AI agent testing. Learn snapshot creation, test isolation, seeded randomness, and techniques for achieving deterministic test results.
Build compliance-grade audit logging for AI agents operating in regulated industries, covering immutable log storage, data retention policies, SOC2 and HIPAA requirements, and log archival strategies.
Design and implement an AI agent gateway that provides centralized access control, structured logging, and intelligent rate limiting. Learn gateway architecture patterns, policy enforcement, and request routing for multi-agent environments.
Python decorator for llm tool authorization: learn how to build reusable decorators for AI agent tools including retry logic, caching, authentication, and rate limiting using functools.wraps and parametrized patterns.
Learn how to build an AI personal shopper agent that creates style profiles, curates product selections based on preferences, manages wish lists, and sends personalized alerts for new arrivals and price drops.
Understand how high-bandwidth interconnects enable multi-GPU and multi-node AI training, the differences between interconnect technologies, and why network topology determines training efficiency.
Build an AI agent that helps taxpayers understand filing requirements, set up payment plans for outstanding balances, check refund status, and navigate tax rules without providing tax advice.
Japan's unique labor shortage drives aggressive AI agent adoption, with NTT, Sony, and Toyota leading enterprise deployments across manufacturing, services, and government.
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