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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Survey of open-source agent frameworks in 2026: LangGraph, CrewAI, AutoGen, Semantic Kernel, Haystack, and DSPy with community metrics, features, and production readiness.
Build IT helpdesk AI agents with multi-agent architecture for triage, device, network, and security issues. RAG-powered knowledge base, automated ticket creation, routing, and escalation.
Year-over-year analysis of the agentic AI landscape comparing experimental 2025 chatbots to production multi-agent systems in 2026, with predictions for 2027.
How to design tool functions that LLMs can use effectively with clear naming, enum parameters, structured responses, informative error messages, and documentation.
Production resilience patterns for AI agents: circuit breakers for LLM APIs, exponential backoff with jitter, fallback models, and graceful degradation strategies.
Architectural comparison of multi-agent topologies including flat, hierarchical, and mesh designs with performance trade-offs, decision frameworks, and migration strategies.
Practical cost reduction strategies for AI agents including semantic caching, intelligent model routing, prompt optimization, and batch processing to cut LLM API spend.
Agent-specific prompt engineering techniques: crafting effective system prompts, writing clear tool descriptions for function calling, and few-shot examples that improve complex task performance.
