Who are these courses designed for?

Ed's curriculum is split into two distinct paths: the AI Engineer track is built for software developers and architects who want to build production-grade agentic systems and tool integrations, while the AI Leader track is designed for founders, executives, and managers looking to strategically deploy Generative AI within their organizations.

What is Ed's teaching style?

His teaching style is highly practical, logical, and execution-oriented. For technical tracks, Ed uses a code-first, hands-on approach where you build actual systems from scratch. For leadership tracks, he focuses on actionable frameworks, cost-benefit analyses, and real-world case studies rather than high-level buzzwords.

Does the course cover the latest AI developments like MCP?

Yes. Ed constantly updates his curriculum to reflect industry shifts. His technical courses cover advanced Agentic AI paradigms, multi-agent frameworks, and the Model Context Protocol (MCP) to ensure students are learning modern, industry-standard integration methods.

Ed Donner

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Who Is Ed Donner?

Ed Donner is a distinguished technology executive, entrepreneur, and educator dedicated to bridging the gap between cutting-edge artificial intelligence and real-world implementation. With decades of experience leading high-performing engineering teams in investment banking—notably serving as a Managing Director at Morgan Stanley—and co-founding the AI-driven recruitment platform untapt, Ed brings a rare blend of deep technical mastery and strategic business acumen to his courses. His teaching philosophy centers on dismantling complex AI concepts, such as agentic workflows, Model Context Protocol (MCP), and large language model architectures, into highly practical, production-ready frameworks. Whether guiding software engineers in building robust multi-agent systems or…

Overview of Ed Donner

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Ed Donner's Programs

Highest rated

AI Engineer Agentic Track: The Complete Agent & MCP Course

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The AI Engineer Agentic Track: The Complete Agent & MCP Course, meticulously crafted by Ed Donner, is an industry-leading program designed to elevate developers into proficient AI Agent engineers. This comprehensive training explores the cutting-edge landscape of autonomous AI, moving far beyond basic prompting to teach students how to build robust, production-ready agentic systems. Over an intensive journey, learners will master the industry's most sought-after frameworks, including the OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, and the Model Context Protocol (MCP). The course heavily emphasizes hands-on mastery through eight ambitious, real-world projects. Students will build everything from a personalized Career Digital Twin and automated SDR Sales Agents to complex multi-agent setups like a software engineering squad in Docker and an autonomous stock-trading floor powered by MCP servers. This program is ideal for software engineers, data scientists, and technical product managers who want to understand the architecture of modern AI workflows, tool calling, and multi-agent coordination. By the end of this curriculum, you will possess a professional-grade portfolio showcasing your ability to design, deploy, and manage self-improving AI systems that solve genuine business problems.

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Top #2

AI Leader: Generative AI & Agentic AI for Leaders & Founders

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Navigating the rapidly evolving landscape of Generative AI requires more than just technical knowledge; it demands strategic leadership and commercial foresight. In "AI Leader: Generative AI & Agentic AI for Leaders & Founders," instructor Ed Donner delivers a comprehensive framework designed specifically for executives, entrepreneurs, and decision-makers looking to turn artificial intelligence into a tangible driver of business ROI. This actionable briefing cuts through the hype of large language models (LLMs) to explore the practical realities of scaling AI performance. Leaders will gain critical insights into the core technical levers—from Retrieval-Augmented Generation (RAG) to advanced reasoning models—while understanding the financial trade-offs of each approach. Crucially, the course demystifies the paradigm of Agentic AI, preparing founders to safely navigate the risks, benefits, and architectural decisions associated with autonomous workflows. By focusing on measurable outcomes, strategic planning, and managing the inevitable workforce transitions, this course empowers leaders to confidently steer their organization’s AI roadmap, making high-impact decisions that secure a sustainable competitive advantage.

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Ed spent over twenty years in enterprise technology and startups. He served as a Managing Director at Morgan Stanley, leading major software engineering initiatives, and later co-founded untapt, an AI-powered talent marketplace that leveraged deep learning algorithms before its successful acquisition.