Product managers who drive strategy, development, and launch of products.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

Building prototypes and MVPs to test ideas quickly before committing to full development.

Using data and metrics to measure performance, run experiments, and inform decisions.

Using AI coding assistants and tools to write, review, and ship code faster.

Identifying opportunities and validating what to build through customer research, experimentation, and prioritization.

Measuring and evaluating AI model performance, quality, and reliability for production use cases.

Automating professional workflows with AI tools — productivity, operations, and task automation.

Using Claude Code to build and ship software through an AI-powered command-line coding workflow.

Model Context Protocol — building tool integrations and server connections for AI agents.

Leverage AI at each step of the product development lifecycle: discovery, prototyping, and delivery.

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