I used to use NERD tree for quite a while, then switched to CtrlP for something a little more lightweight. My setup now includes zero file browser or tree view, and instead uses native Vim fuzzy search and auto-directory switching.
There is a super sweet feature in Vim whereby you can fuzzy find your files using **/*, e.g.:
:vs **/*<partial file name><Tab>
To start using this site you need to have a GitHub account to sign in. Once signed in it will create your profiles information based on your GitHub account and return you to your brand new profile page. Click the profile editor button to enter in if you want to be a student, partner or teacher. You should also enter in what skills you have and what skills you are looking to learn on this page.
Once you have your profile how you like it, head on over to the search page to look for what you want to use on your next project and what kind of partner you are looking for. After hitting the search button we will find the very best matches for you to begin your pair programming journey!
This is a simplified, but fairly thorough, set of scripts and configuration to enable Heroku Release Phase for Rails apps.
Further, this particular set up plays nicely with Heroku Review Apps in that the release phase script will:
bin/rails db:version) is 0.For a "normal" app that usually means it will run the DB migrations.
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.