This second installment in the “You don’t know HTML” series is going to be all about the ways that we put collections of things together. We’re skipping over the MDN and W3Schools introductory pages and instead we’re going into the kind of stuff you discover after accidentally taking your cousin’s Ritalin right before you open up the W3C specs. Let’s dive deep into lists.

The first thing I usually do when I pick up a new codebase isn’t opening the code. It’s opening a terminal and running a handful of git commands. Before I look at a single file, the commit history gives me a diagnostic picture of the project: who built it, where the problems cluster, whether the team is shipping with confidence or tiptoeing around land mines.

Modern CSS code snippets, side by side with the old hacks they replace. Every technique you still Google has a clean, native replacement now.

HTTP Headers are a great booster for web security with easy implementation. Proper HTTP response headers can help prevent security vulnerabilities like Cross-Site Scripting, Clickjacking, Information disclosure and more.

In this cheat sheet, we will review all security-related HTTP headers, recommended configurations, and reference other sources for complicated headers.

In this post, we will try to build a text summarizer using an LLM in a Python environment. If we can set up the LLM in an interactive environment, we can extend the functionalities to build an interface for this task using Gradio.

Prompt chaining can enhance the effectiveness of AI assistance in various domains. By breaking down complex tasks into smaller prompts and chaining them together, developers can create more personalized and accurate responses tailored to individual users’ needs. This approach not only improves the overall user experience but also allows for greater customization and adaptability in response to changing user requirements or application scenarios[3].

Dotprompt is an executable prompt template file format for Generative AI. It is designed to be agnostic to programming language and model provider to allow for maximum flexibility in usage. Dotprompt extends the popular Handlebars templating language with GenAI-specific features.

Traditional approaches waste precious development cycles on parsing and validating LLM outputs. .txt's products make data flow seamlessly through your system by providing complete control over LLMs' outputs.

Our products ensure LLMs consistently generate outputs matching any JSON Schema, regular expression, or grammar—without significant overhead.

qqqa is a two-in-one, stateless CLI tool that brings LLM assistance to the command line without ceremony.

The two binaries are:

• qq - ask a single question, e.g. "qq how can I recursively list all files in this directory" (qq stands for "quick question")
• qa - a single step agent that can optionally use tools to finish a task: read a file, write a file, or execute a command with confirmation (qa stands for "quick agent")

Argh provides a wrapper for argparse. Argparse is a very powerful tool; Argh just makes it easy to use.