Glossary

What Is a Prompt Pack?

A Prompt Pack is a set of structured, phase-based prompts generated from your architecture spec and implementation plan. Each prompt is written for a specific stage of the build, in dependency order, and tailored to the AI coding platform you're using, whether that's Lovable, Cursor, or Bolt.new.

Why prompts need to be phased

Most vibe coders prompt as they go. They describe a feature, wait for the output, react to what breaks, and repeat. This works for the first hour, but it becomes the reason the build collapses later.

AI coding agents don't understand dependency order unless you tell them. If you prompt for payments before your auth layer is solid, the agent will build payments against assumptions that auth will invalidate. If you prompt for multi-user features before your data schema accounts for multiple users, you'll rewrite the schema after you've already built against it.

A Prompt Pack solves this by sequencing prompts to respect your architecture's actual dependencies, so each stage of the build is stable before the next one starts.

What a Prompt Pack contains

  • Phased prompts: One prompt per build stage, ordered by dependency (foundation first, complex integrations last)
  • Platform-specific wording: The same instruction written differently for Lovable vs. Cursor vs. Claude Code, because each tool interprets prompts differently
  • Architectural grounding: Each prompt references the relevant parts of your Architecture Design Document, so the agent always knows which constraints apply to this stage
  • Explicit boundaries: Each prompt states what the agent should not touch, not just what it should build

How it works with an ADD

A Prompt Pack and an Architecture Design Document are generated together. The ADD defines the system. The Prompt Pack is the execution plan for building it. It's the ADD in action, one phase at a time.

Used together, they replace the prompt-and-react loop with a planned build sequence that an AI coding agent can follow from first feature to production-ready app without losing architectural consistency.

Zalcro generates a prompt pack as a final output reflecting the decisions captured in the ADD and the implementation plan

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