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 to automate desktop applications using PyAutoGUI combined with AI vision models. Covers screen recognition, coordinate mapping, multi-monitor setups, keyboard automation, and building robust desktop agents.
Build an AI-powered competitive intelligence agent that monitors competitor websites, detects meaningful changes, performs content diffing with sentiment analysis, generates alerts, and displays insights on a dashboard.
Learn how to build reflection agents that evaluate their own outputs, assign quality scores, and iteratively refine results through multi-round self-improvement loops using the Reflexion pattern.
Discover how plan-and-execute agent architectures split high-level reasoning from step-by-step execution, enabling robust replanning on failure and efficient handling of complex multi-step tasks.
Understand the MRKL (Modular Reasoning, Knowledge, and Language) architecture that combines LLMs with specialized expert modules, intelligent routing, and structured knowledge retrieval for building powerful AI systems.
Learn how to build AI agents with metacognitive capabilities — uncertainty estimation, confidence calibration, knowledge boundary detection, and know-when-to-ask patterns that make agents more reliable and honest.
Explore how AI agents use internal world models to simulate future states, predict action consequences, and perform look-ahead planning — enabling smarter decisions without costly real-world trial and error.
Build an AI agent that performs structured legal reasoning — searching precedents, constructing multi-step arguments with evidence chains, generating counter-arguments, and producing balanced legal analysis.
