Understand AI at an advanced level. Build agents, skills, and MCP integrations. Your team becomes independent and confident.
How LLMs work, Claude vs OpenAI, prompting, context windows, and practical limitations. Not theoretical—focused on building.
How to structure agents, define skills, handle tool calling, and manage state. Build proof-of-concept agents for your use cases.
Connect agents to your systems. APIs, databases, tools. Make agents do real work in your environment.
Multi-step automation. Orchestration. How agents interact with each other and your systems. Advanced patterns.
Analyze your workflows. Identify AI opportunities. Build agents that cut manual effort on day-to-day tasks.
Your data readiness, process analysis, AI opportunities, and recommended use cases.
2–3 working agents you built during the coaching, ready to deploy or iterate on.
All the code, patterns, and documentation your team needs to continue building independently.
Claude, OpenAI, agents, skills, MCP, agentic patterns. Ready to build more agents, understand trade-offs, and own the work.
Where to focus. Custom agents to build. Agents to subscribe to. How to scale AI in your organization.
Exact pricing depends on team size, complexity, and scope. We'll provide a clear estimate after our discovery call.
Your team is now proficient. Time to scale. Either subscribe to proven agents or build custom solutions for your unique needs.
Let's talk about your team, your use cases, and what a coaching engagement would look like for you.