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AI Place Hub
@aiplacehub moderator
Maintainer account. Publishes the baseline library that ships with the site.
Joined September 2026
23
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Published
Codex CLI
The OpenAI terminal coding agent. It reads a repository, plans a change and runs commands in a sandbox, and by default asks your approval before…
Tested on GPT-5 · Jun 2026
Aider
A terminal pair programmer that edits files straight in your working tree and commits each change with a generated message. No copy-paste loop.
Tested on Claude Sonnet · Jun 2026
AnythingLLM
A desktop app for chatting with your own documents against a local or hosted model. The retrieval pipeline is built in, so you do not assemble it…
Tested on Llama 3.3 70B · Jun 2026
Windsurf
A standalone code editor forked from VS Code and built around an agent. The assistant plans and runs multi-file changes and does more than suggest…
Tested on Claude Sonnet · Jun 2026
Raycast AI
AI commands inside the Raycast launcher on macOS. Rewrite a selection or answer a question without switching apps.
Tested on GPT-5 · Jun 2026
Cody
A coding assistant built on Sourcegraph code search. Its context comes from an index of your whole repository and not only the open file.
Tested on Claude Sonnet · Jun 2026
Continue
An open-source editor extension for VS Code and JetBrains. You plug in any model, hosted or local, and stay free of one vendor.
Tested on Claude Sonnet · Jun 2026
GitHub Copilot
Inline code suggestions and a chat panel in the editor, backed by a choice of models. Most developers try it first, for better or worse.
Tested on GPT-5 · Jun 2026
- GuideUniversal
Why prompt injection is not solved
What the problem is, why filtering does not fix it, and what does help. Written for someone about to give a model access to something real.
Tested on Claude Sonnet · May 2026
- PromptUniversal
Audit a prompt for injection risk
Reviews your own system prompt the way an attacker would read it, and points to the exact sentence that gives something away.
Tested on Claude Sonnet · May 2026
- ConfigUniversal
System prompt hardening block
A paragraph to add to any system prompt that reads user-supplied content. It cannot make injection impossible. It makes the common attempts fail…
Tested on Claude Sonnet · May 2026
Fetch MCP server
Lets the model retrieve a URL and read it as text. Simple and useful, and the plainest case of untrusted input in the whole protocol.
Tested on Claude Sonnet · May 2026
GitHub MCP server
Issues, pull requests and code search without leaving the conversation. Scope the token to what you need.
Tested on Claude Sonnet · May 2026
PostgreSQL MCP server
Lets the model query your database directly. Read-only is the setting that counts, and it is not the default everywhere.
Tested on Claude Sonnet · May 2026
Filesystem MCP server
Gives the model read and write access to directories you name. The most useful MCP server and the one that deserves the most thought before you…
Tested on Claude Sonnet · May 2026
No-padding everyday default
The one to set if you set only one. Answer first, nothing before it, nothing after it, and no offer of further help.
Tested on Claude Sonnet · May 2026
- CheatsheetUniversal
Forcing an output format that holds
Phrasings that really constrain output, and the popular ones that do not. I asked for the same thing twenty times and counted the failures.
Tested on Claude Sonnet · May 2026
- CheatsheetChatGPT
ChatGPT commands and keyboard shortcuts
The commands and shortcuts the interface never shows you, in one table. Mostly keyboard, mostly undocumented.
Tested on GPT-5 · May 2026
Collections
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4 items
First week with a coding model
Read these in order if you only just started using a model on a real codebase. Four entries, about an hour.
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3 items
Going local
How to stop paying for an API: the hardware maths, the install, and the two tools that matter.
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5 items
Set up your AI once
Stop retyping the same rules. Five lessons on moving them into a config file for Claude Code and Cursor, and on picking a model…
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5 items
AI on a budget
Five free lessons, from the free ways to use AI through choosing a model to running one on your own computer. You spend nothing.
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6 items
Prompt engineering: zero to fluent
Six lessons. You start with what a single prompt is made of and end with few-shot examples and a self-critique pass. No…
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5 items
AI for study and everyday work
Five free lessons on turning a messy task into a clear prompt, getting summaries you can trust, and studying without handing the…
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5 items
Use AI without getting burned
Five free lessons about checking answers, keeping private data out of chats and dealing with prompt injection. No sign-up.
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5 items
Work with a coding assistant
Five free lessons: how to brief an assistant, where to keep your rules, and how to review what it changed.
Glossary contributions
Agent
A model with tools and a goal that picks its own next steps in a loop and does not answer just once.
API key
A secret string that identifies you to an AI service and lets your code call it. Whoever has the key can spend your money.
Chain of thought CoT
Prompt the model to write out its intermediate steps before giving the final answer.
Connector
A link between an AI app and an outside service, such as a drive, calendar or chat tool, that lets the model read your data from there.
Context window
The most text, counted in tokens, that a model can consider at once. Your prompt and its answer share that space.
Embeddings
Lists of numbers that stand for text, built so that similar meanings end up close together. Semantic search runs on them.
Few-shot prompting
Put two or three worked examples of the task in the prompt, on top of the description.
Fine-tuning
More training for an existing model on your own examples. It changes how the model behaves, not what it knows.
Hallucination
A fluent, confident answer that is plain wrong: an invented citation, function, statistic or fact.
Inference
Running a trained model to get output. It happens every time you send a prompt.
Large language model LLM
A model trained on huge amounts of text to predict the next token. That one skill lets it write, summarise, translate and reason over text.
Model Context Protocol MCP
An open standard that lets an AI app connect to outside tools and data, such as files, databases or services, through small programs called servers.