A self-driving agent loop for Claude Code. It turns an issue description into a workplan, implements it one task at a time, runs the verification commands the project already uses, fixes what fails, and commits as it goes.
benman1/wiggumSoftware resources
Everything here is public on GitHub, free to read and to use. The tools come out of consulting work. The rest is the code that goes with the books.
Tools
Human-in-the-loop for LangGraph. A workflow pauses, asks a person to fill in a form, and resumes with their answers, talking to KirokuForms over the Model Context Protocol.
ChelseaAIVentures/langgraph-kirokuformsCode from the books
Each repository holds the worked examples for one book. Start with the book page for what it covers, or go straight to the notebooks.
Notebooks working through the papers that retrieval augmented generation is built on, one implementation per paper.
Companion to Retrieval Augmented Generation: The Seminal Papers, Manning 2026
benman1/rag-seminal-papersCode for building LLM applications and agents with Python, LangChain and LangGraph, covering the examples in the book end to end.
Companion to Generative AI with LangChain, 2nd Edition, Packt 2025
benman1/generative_ai_with_langchainForecasting and time-series modelling in Python, from classical methods through to deep learning.
Companion to Machine Learning for Time Series, Packt 2021
benman1/Machine-Learning-for-Time-Series-with-PythonRecipes across the breadth of applied AI in Python: supervised and unsupervised learning, probabilistic modelling, computer vision, language and speech.
Companion to Artificial Intelligence with Python Cookbook, Packt 2020
benman1/Artificial-Intelligence-with-Python-Cookbook