Deploying Agents: The Easy Way
In this playbook, I will provide you with a template for quickly and effortlessly deploying AI Agents for a wide array of business use cases using serverless cloud functions.
Benjamin Falkeborg
AI Engineer & Architect. I designed the personalization architecture for the world's largest jewelry company and automated claims handling for the leading insurance company in the Nordics
Check out the latest posts
Let's Build a DeepSeek Agent in Pure Python
In this tutorial, we will build a DeepSeek AI agent in pure Python. The solution is flexible and can easily be extended to a variety of real-world applications.
Product Analytics with LangGraph
This playbook walks you through building an ecommerce product analytics agent using BigQuery and LangGraph. The agent helps identify opportunities to increase average order value through product combinations, category analysis, and bundle recommendations.
Make Your Agent Work Like a Developer
In this tutorial, we will build a LangGraph AI Agent designed to interact with Git and GitHub, simulating the workflows of professional developers.
Two Ways to Execute Python With AI Agents
This tutorial will dive into the mechanics behind executing Python code with AI Agents. We will set up and agent with LangGraph, generate and then execute Python code in two distinct ways.
Repeat Purchase Analytics with LLMs
This playbook will walk you through building a repeat purchase analytics library. We'll cover everything from writing SQL queries to creating a Python class for your analysis tools. We'll then create a suite of LangChain tools out of the class and let LLMs figure out how to use the different tools.