Situation: Data shows that in 12% of cases the agent skips get_customer and calls lookup_order using only the customer’s name, which leads to incorrect refunds.
Which change is most effective?
lookup_order and process_refund until an ID is obtained from get_customer [CORRECT]
When you setup GitHub pages, by default your content is available at https://<GITHUB_USERNAMNE>.github.io/<REPO_NAME>/.
However, if you create a repo with the exact name <GITHUB_USERNAME>.github.io, GitHub will automatically turn GitHub Pages on, and make this content avialable at https://<GITHUB_USERNAME>.github.io/. Kind of like your GitHub home page!
For example, I set up a sample at:
https://github.com/codeadamca/codeadamca.github.io
The repo is avilable as a website at:
Bienvenido al curso Java Fundamentals, un programa diseñado para introducirte en los conceptos esenciales de la programación utilizando el lenguaje Java.
Este curso forma parte de una ruta de aprendizaje progresiva y está orientado a desarrollar habilidades básicas en programación estructurada y orientada a objetos.
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
Every repo from my series, newest first. I keep this same link updated — save it.
Follow me on Instagram for the next one: @angelotrifanoff.ai
https://github.com/MadsLorentzen/ai-job-search (MIT, ★36K+)
