For recurring AI tasks, such as loading project-specific diagrams or switching models in Claude Code, create short shell aliases (e.g., 'cdi' for 'Claude diagram load'). This avoids retyping long commands and allows you to quickly switch contexts or modes.
Related Insights
The power of tools like Claude Code comes from giving the AI access to fundamental command-line tools (e.g., `bash`, `grep`). This allows the AI to compose novel solutions and lets product teams define new features using simple English prompts rather than hard-coded logic.
Instead of manually providing context in each prompt, use Claude Code's 'append system prompt' command. This preloads crucial information, like architectural diagrams, at the start of a session, leading to faster and more accurate AI responses without repeated file reads.
Instead of managing prompts in a separate library, save them as custom commands directly within your Claude Code project folder. This lets you trigger complex, multi-file prompts with a simple command (e.g., `/meeting_notes`), embedding powerful, recurring workflows directly into your development environment.
The terminal-first interface of Claude Code wasn't a deliberate design choice. It emerged organically from prototyping an API client in the terminal, which unexpectedly revealed the power of giving an AI model direct access to the same tools (like bash) that a developer uses.
Keep AI context fresh by automating the generation of documentation and diagrams. Set up a GitHub action to create these assets when a pull request is closed, ensuring your AI assistant always works with the latest application logic without manual updates.
When prototyping new AI-powered ideas, build them as command-line interface (CLI) tools instead of web apps. The constrained UI of the terminal forces you to focus on the core workflow and logic, preventing distraction from visual design and enabling faster shipping of a functional version.
To gain data ownership and enable AI automation, Teresa Torres built a personalized task manager using Claude Code and local Markdown files. This allows her to prompt the AI to directly see and execute items from her to-do list, a capability not possible with third-party tools like Trello.
Run separate instances of your AI assistant from different project directories. Each directory contains a configuration file providing specific context, rules, and style guides for that domain (e.g., writing vs. task management), creating specialized, expert assistants.
Teresa Torres defined a `/today` slash command in Claude Code. This shortcut triggers a detailed, pre-written prompt that scans her task files, checks for team updates, and generates a prioritized daily to-do list in Obsidian, automating a repetitive and complex morning routine.
For complex, one-time tasks like a code migration, don't just ask AI to write a script. Instead, have it build a disposable tool—a "jig" or "command center”—that visualizes the process and guides you through each step. This provides more control and understanding than a black-box script.
