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Package Description:
This coaching package is designed to give you a clear, practical introduction to AI tools for writing, design, and creative production. By the end, you’ll understand the fundamentals, have hands-on experience generating content across formats, and know exactly how to take your next steps. Package topics can include, but are not limited to: • Idea exploration: choose content types to prototype • Tool setup: experiment with AI for text, visuals, and media • Prompting basics: learn creative prompting and iteration • Guided build: produce 2–3 content pieces together • Workflow tips: set up repeatable content creation flows • Next steps: roadmap for refining and publishing Outcome: By the end, you’ll have a starter set of AI-generated content and a clear workflow for scaling creative production.
What you'll get from this package
2–3 AI-generated content pieces
Exposure to text, design, and media tools
Prompting techniques for creative workflows
A roadmap for content production
Additional details
Coaching delivered via live sessions.
Services included:
AI Podcast Creation
AI Graphics Creation
Talk to a team member
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
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5.0
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I build AI agents for real analytics environments - not demos, not proofs of concept. As Director of Business Intelligence and Analytics at Live Nation Entertainment, I've designed and shipped production agent systems that combine LLM reasoning, MCP servers, structured data querying, and document search into workflows that replace manual analytical processes. My hands-on stack includes Databricks, Gemini, Vertex AI Search, Streamlit, and custom MCP server development. I've also built open-source tooling in this space, including a video understanding MCP server using local/free models. I come from a decade-plus background in BI and data engineering, which means I understand the messy reality agents actually have to operate in - legacy data models, inconsistent schemas, stakeholder trust issues, and the gap between what LLMs promise and what they deliver in production. If you're trying to build your first agent, figure out the right architecture for your use case, or get an agent system actually adopted inside your organization - I can help you avoid the mistakes I've already made.
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5h of coaching