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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How to build AI agents that catch and fix their own errors through output validation, reflection prompting, retry with feedback, and graceful escalation when self-correction fails.
How autonomous coding agents work in 2026 comparing Claude Code CLI, OpenAI Codex, and Cursor IDE with architecture details, capabilities, pricing, and real usage patterns.
Technical guide to building AI agents that automate document processing — PDF parsing and extraction, email classification and routing, and spreadsheet analysis with reporting.
Build a powerful AI coding assistant that reads files, runs tests, and fixes bugs using the Claude API and Model Context Protocol servers in TypeScript.
Technical deep dive into agent memory architectures covering conversation context, vector DB persistence, and experience replay with implementation code for production systems.
Complete testing guide for AI agents covering mocking LLM responses for unit tests, integration testing with tool calls, and end-to-end evaluation with golden datasets.
Head-to-head comparison of ElevenLabs Conversational AI and OpenAI Realtime API for building voice agents: latency, voice quality, pricing, languages, and function calling.
Step-by-step tutorial on building an MCP server in TypeScript, registering tools and resources, handling requests, and connecting to Claude and other LLM clients.
