Learning paths
Curated, ordered sequences of episodes — from foundations to advanced practice. Each path is auto-generated from the show library and refreshed as new episodes drop.
The AI Readiness Roadmap
This path establishes the essential mindset and foundational tools needed for individuals and organizations to begin their AI journey.
- • Develop a foundational understanding of AI's current impact on work
- • Master basic prompt engineering techniques for personal productivity
- • Identify specific areas where AI can enhance your daily professional tasks
Leading the AI-Augmented Workforce
Focuses on the leadership skills required to guide humans and AI as they integrate into high-performance teams.
- • Adapt leadership styles to manage teams of mixed human and AI contributors
- • Foster a culture of transparency and trust during AI workforce transitions
- • Design roles that leverage human judgment as the core value proposition
Strategic AI Operations for Small Business
A targeted curriculum for entrepreneurs and small business leaders to move from interest to implementation and measurable ROI.
- • Design an AI implementation strategy tailored for a small business environment
- • Deploy no-code AI tools to automate customer engagement and operations
- • Calculate and track the ROI of AI pilots within your organization
The Governance and Ethics Framework
Essential training for leaders on managing the risks, biases, and ethical implications of deploying AI at scale.
- • Evaluate AI systems for potential bias and ethical risk
- • Implement effective AI guardrails to prevent system hallucinations or misuse
- • Draft a Responsible AI governance policy for your department or company
Architecting Enterprise AI Agents
An advanced deep dive into the transition from simple chat interfaces to autonomous multi-agent systems that perform complex tasks.
- • Distinguish between simple chatbots and sophisticated agentic orchestration
- • Design human-in-the-loop workflows for autonomous AI tasks
- • Architect the data foundations necessary to support enterprise-grade AI agents
Software 3.0: Engineering in the AI Age
A path for developers and technical leaders to understand how AI is fundamentally changing the software development lifecycle.
- • Transition from manual coding to supervising AI-driven development agents
- • Deploy automated evaluation frameworks to maintain code quality in Software 3.0
- • Realign engineering career paths with the new values of judgment and system architecture