Teaching Agentic AI: Creating Workshops, Courses, and Content
How to design effective agentic AI curriculum, build hands-on workshop exercises, assess learner progress, and grow a community around your educational content.
Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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How to design effective agentic AI curriculum, build hands-on workshop exercises, assess learner progress, and grow a community around your educational content.
Master the sampling parameters that control LLM behavior — temperature, top-p, top-k, frequency penalty, and presence penalty — with practical examples showing when to use each.
Learn how Temporal provides durable execution guarantees for AI agent workflows. Covers workflow definition, activities, automatic retries, and state management for long-running agent pipelines.
Implement memory decay functions that let AI agents naturally forget stale information while preserving important memories, using importance scoring, refresh-on-access, and automated cleanup.
Master TensorFlow Lite for deploying AI agent models on Android and iOS devices, including model conversion, quantization strategies, and real-world integration patterns.
Learn to build an AI agent that analyzes source code, identifies untested paths, and generates high-quality unit and integration tests with proper assertions, fixtures, and edge case coverage.
Build a comprehensive test suite for MCP servers covering unit tests for tool logic, integration tests for protocol compliance, mock clients for end-to-end validation, and edge case coverage.
Learn how to test multi-agent handoff logic, verify conversation routing, validate context transfer between agents, and test boundary conditions in agent orchestration systems.
Build comprehensive multilingual test suites that validate AI agent quality across languages with automated quality checks, native speaker reviews, and regression detection.
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