Learning Journeys
Choose your journey below. Sprint 2: Workflow Automation starts April 7.
AI Foundations
For non-technical roles. Learn to use Claude effectively in your daily work.
Introduction to Claude, prompt engineering, and automating your first workflow.
AI strategy, governance, team enablement, and organizational transformation.
Contract review, compliance monitoring, and regulatory analysis with AI.
AI-powered forecasting, expense categorization, and financial reporting.
Campaign creative, brand-as-code, content production, and AI-powered marketing workflows.
AI-assisted recruiting, onboarding, performance cycles, and employee experience.
Agentic ops system: sprint coordination, OKR tracking, cross-squad reporting, and process automation with Claude Code.
AI-assisted moderation, support triage, community safety, and CRM workflows.
Content production, community engagement, multi-platform publishing, and AI-powered creative workflows.
AI-powered ad optimization, campaign analysis, bid management, and monetization workflows.
Dual-user CRM automation: onboarding flows, engagement scoring, re-engagement triggers for marketplace platforms.
Technical Journeys
For engineering, design, data, QA, and product roles. CLI-first with Claude Code.
Context engineering, AI-assisted product management, and specification-driven development.
Context engineering for backend systems, API documentation, and AI-assisted server-side development.
Context engineering for UI components, design systems, and AI-assisted frontend development.
Cross-layer context engineering, API contracts, and AI-assisted full-stack workflows.
Context hierarchies for multi-agent systems, evaluation frameworks, and agentic architecture.
Context engineering for test strategies, AI-assisted testing, and quality automation.
Brand-as-code, design token automation, and AI-powered creative workflows.
Interaction design, wireframes, user flows, prototyping, and AI-assisted UX research.
Context engineering for data pipelines, metrics, dashboards, and AI-assisted analysis workflows.
Context engineering for ML experiments, training scripts, and AI-assisted model development.
Extracurricular
Optional intensive tracks. Build real products, ship prototypes, test with users.