This playbook shows how to use LangGraph workflows to generate campaign configs from simple inputs. We'll build a system that transforms product descriptions into complete campaign strategies with audience segments and ad variations, while preserving human approval before execution.
This playbook shows how to use configuration-driven campaign matrices to automate Meta Ads at scale. We'll build a system that transforms campaign configs into complete ad variations with targeting, budgets, and creatives, eliminating manual setup across dozens of ads.
In this tutorial, I will teach you LangChain as efficiently as possible by breaking down the framework into seven key components you need to understand to start developing more advanced LLM applications.
This tutorial will explore building dashboards using Large Language Models (LLMs) and LangChain. We will use LangChain chains to extract insights from BigQuery by first generating SQL and then pushing the generated SQL to BigQuery as views, forming the basis for interactive dashboards.
This guide helps data analysts, data scientists, and developers leverage LLMs for generating SQL queries from natural language questions, making complex data wrangling in BigQuery and other SQL databases more accessible and intuitive.
This playbook shows how to use LangGraph workflows to generate campaign configs from simple inputs. We'll build a system that transforms product descriptions into complete campaign strategies with audience segments and ad variations, while preserving human approval before execution.
This playbook shows how to use configuration-driven campaign matrices to automate Meta Ads at scale. We'll build a system that transforms campaign configs into complete ad variations with targeting, budgets, and creatives, eliminating manual setup across dozens of ads.
This playbook shows how to build Pydantic models that enable agents to create Meta ad campaigns programmatically. We'll implement the complete workflow from image upload to live ads, with automatic validation for budgets, content safety, and platform requirements built into every step.
This playbook walks you through building an AI-powered cohort analysis system that automatically discovers which customer segments have the highest retention rates. The LangGraph pipeline dynamically analyzes multiple dimensions and delivers AI-generated insights for targeted retention strategies.
This playbook walks you through building an AI-powered CLV analysis system that reveals which customers drive long-term profitability. The LangGraph pipeline applies statistical models to predict behavior and delivers AI recommendations for optimization.
This playbook walks you through building an AI Flow that dissects ecommerce revenue drivers across a customer base. The LangGraph-based system breaks down top-line metrics into their component parts, identifies root causes, and delivers prioritized recommendations to improve performance
