creating-prompts

AI-Enablement Prompts is a collection of advanced AI prompt chains created by Bitovi, a consultancy on the cutting edge of AI-augmented software development. These prompts are designed to help AI agents like GitHub Copilot move beyond simple autocomplete and become valuable, context-aware teammates.

Each prompt or prompt chain is built to guide the AI through specific engineering workflows — analyzing a codebase, generating documentation, implementing features, and more — using clearly defined, repeatable steps that reflect how real engineers work.

Our goal is to bridge the gap between general-purpose AI models and project-specific knowledge, enabling faster, more accurate, and more scalable development.

Repository Structure

Prompts in this repo are organized into high-level categories based on what they help the AI accomplish:

• /understanding-code – Prompt chains that help AI understand and document existing codebases
• /writing-code – Prompt chains that assist with implementing new functionality based on external input (e.g. Jira tickets)

Each subfolder contains one or more prompts or prompt chains, each with its own README.md explaining how to use it.

What's Inside

Here are a few currently available prompt chains:

1. Developer Docs Generator

Path: understanding-code/instruction-generation

Generates a copilot-instruction.md file that helps AI tools operate effectively within your codebase. Ideal for onboarding AI tools (or humans) with deep, structured context.

Features:

• Analyzes the tech stack and architecture
• Categorizes files by role
• Extracts coding patterns and naming conventions
• Documents features and domain logic

→ View prompt chain

2. Jira Ticket Automation

Path: writing-code/generate-feature

Takes a Jira ticket number and walks the AI through implementing the described feature — including gathering Figma designs and file attachments — then writing the code.

Features:

• Pulls ticket data from Atlassian
• Fetches designs from Figma and files from internal systems
• Organizes context for implementation
• Outputs modular, convention-aligned code

→ View prompt chain

How to Use

Requirements

• GitHub Copilot Chat or an equivalent AI chat agent with tool access
• MCP (Model Context Protocol) server access if required (for Jira, Figma, attachments, etc.)
• A valid codebase or ticket to operate on

Getting Started

1. Open the repo: https://github.com/bitovi/ai-enablement-prompts
2. Navigate to the prompt folder you're interested in.
3. Read the README.md for that prompt chain to understand the flow and inputs.
4. Open Copilot Chat and paste the example input provided.
5. Provide the necessary parameters:
   • {TICKET_NUMBER} for Jira-based prompts
   • {OUTPUT_FOLDER} for saving generated results
6. Execute each step in order. These workflows are designed to build cumulative context.

Built by Bitovi, Leaders in AI-Enabled Development

Bitovi is actively integrating AI into real-world software engineering — not just internally, but with clients across industries. From custom training to full-scale workflow automation, we're helping teams embed AI across the stack.

This repo reflects our hands-on experience building practical AI tools, backed by years of consulting expertise in scalable, maintainable software development.

Need help enabling your team? Talk to us

Contributing

Have ideas for new prompt chains? Want to improve an existing one? Check out CONTRIBUTING.md to get started.