Claude Skills aren't limited to natural language instructions; they can reference and execute Python scripts. This enables developers to enforce consistency for technical tasks like data cleaning or validation, preventing the variability that occurs when the LLM generates code on its own.

While Claude's built-in 'create skill' tool is clunky, its output reveals a highly structured template for effective prompts. It includes decision trees, clarifying questions for the user, and keywords for invocation, serving as an invaluable guide for building robust skills without starting from scratch.

Instead of prompting a specialized AI tool directly, experts employ a meta-workflow. They first use a general LLM like ChatGPT or Claude to generate a detailed, context-rich 'master prompt' based on a PRD or user story, which they then paste into the specialized tool for superior results.

LLMs often get stuck or pursue incorrect paths on complex tasks. "Plan mode" forces Claude Code to present its step-by-step checklist for your approval before it starts editing files. This allows you to correct its logic and assumptions upfront, ensuring the final output aligns with your intent and saving time.

Claude Code's terminal-based interaction within a specific folder allows it to automatically read and reference local files. This makes "context engineering" drastically faster and more powerful than manually pasting information into a traditional chat interface, as the context is implicitly understood.

Instead of writing Python or TypeScript to prototype an AI agent, PM Dennis Yang writes a "super MVP" using plain English instructions directly in Cursor. He leverages Cursor's built-in agentic capabilities, model switching, and tool-calling to test the agent's logic and flow without writing a single line of code.

While "vibe coding" tools are excellent for sparking interest and building initial prototypes, transitioning a project into a maintainable product requires learning the underlying code. AI code editors like Cursor act as the next step, helping users bridge the gap from prompt-based generation to hands-on software engineering.

To get consistent, high-quality results from AI coding assistants, define reusable instructions in dedicated files (e.g., `prd.md`) within your repository. This "agent briefing" file can be referenced in prompts, ensuring all generated assets adhere to a predefined structure and style.

Don't pay for Claude's most expensive tier just for coding. A hybrid approach uses the cheaper Claude Pro plan for its superior file-handling and writing. For heavy coding, switch to the terminal inside Cursor, which provides access to top models like Opus for only $20/month, creating a powerful stack for under $40.