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This coaching package is built to take you from idea to a working AI agent that you can use, share, and build upon. You’ll get a mix of strategy, hands-on building, and practical resources to ensure you leave with both a functional product and the know-how to extend it. Package topics can include, but are not limited to: - Use case definition: clarify the problem your agent will solve, its target users, and where it will fit into your workflow or business - Tool and tech stack setup: guidance on choosing and setting up the right frameworks (LangChain, AutoGen), APIs (OpenAI, Anthropic), and integrations (Slack, Notion, CRM, etc.) - Prompt and workflow design: build the logic, memory, and workflows that make your agent useful, reliable, and repeatable - Rapid prototyping and iteration: develop and test your first working version, with coaching support to debug, refine, and improve - Deployment and integration: launch your agent in an environment where it can be accessed and used (cloud hosting, internal tools, or team platforms) - Documentation and next steps: create clear instructions and a roadmap so you can maintain, extend, or scale your agent beyond this package Outcome: By the end of the package, you will walk away with a working AI agent tailored to your goals, plus the resources and knowledge to confidently extend its capabilities on your own.
Hands-on coding support during sessions
Starter templates and code examples
Customized recommendations for tools and integrations
A curated resource library with guides and frameworks
A fully functioning AI agent built around your use case
Coaching delivered via live sessions.
Services included:
AI Agents
AI Automation
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
Get help with AI Ethics & Responsible AI, AI Research, and .

Joined November 2025
5.0
Production AI Agents at Live Nation | Databricks, MCP, & Vertex Expert
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.
10h of coaching