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The full A/B testing lifecycle — from hypothesis to decision framework — with power analysis, validity checks, and rollout strategy.
How a multi-agent system plans, researches, writes, and reflects to produce an academic report. Based on Andrew Ng's agentic-ai-public repo.
How to turn CRM and marketing data into a predictive lead score — from feature engineering to sales alerts.
How LangGraph builds stateful multi-agent systems — state, nodes, conditional edges, memory, and human-in-the-loop.
How Anthropic's Model Context Protocol lets AI apps connect to any external tool, database, or data source through a standardised interface.
How Retrieval-Augmented Generation lets an LLM answer questions from your own documents with citations.
From brief to published — research, draft, image generation, review, and approval in one agentic workflow.
How media mix modeling turns channel spend into revenue attribution and budget recommendations.
Hypothesis to decision — how an agent generates variants, scores outputs, and picks a winner.