LLM-Based Development Workflow

Overview

This document outlines our approach to LLM-based software development, optimizing the flow from idea generation to code implementation.

Workflow Stages

1. Ideation and Planning

  • Use LLMs for brainstorming and feature exploration

  • Generate comprehensive feature specifications

  • Create architectural designs and component relationships

2. Prompt Engineering

  • Design modular, reusable prompts

  • Include context and constraints

  • Maintain prompt versioning

3. Code Generation

  • Generate code in manageable chunks

  • Integrate with existing codebase

  • Maintain consistent coding style

4. Testing and Refinement

  • Generate test cases

  • Debug with LLM assistance

  • Optimize performance

Best Practices

  1. Context Management

    • Maintain clear checkpoint system

    • Track conversation state

    • Preserve important context

  2. Code Organization

    • Use consistent file structure

    • Maintain clear dependencies

    • Document integration points

  3. Quality Control

    • Regular code review

    • Automated testing

    • Performance monitoring

Integration with Priority Queue

The LLM workflow integrates with our priority queue through:

  1. Automatic priority assessment

  2. Dependency tracking

  3. Resource allocation

  4. Timeline estimation

Templates

Feature Development Template

# Feature: [Name]
## Context
- Current system state
- Related components
- Dependencies

## Requirements
- Functional requirements
- Performance requirements
- Integration requirements

## Implementation Plan
- Component changes
- New modules
- Integration points

## Testing Strategy
- Unit tests
- Integration tests
- Performance benchmarks

Debugging Template

# Debug Session: [Issue]
## Context
- Error description
- System state
- Recent changes

## Analysis
- Error patterns
- Component interactions
- Performance impacts

## Resolution
- Code changes
- Configuration updates
- Verification steps

Workflow Optimization

  1. Continuous Learning

    • Track successful patterns

    • Identify common issues

    • Refine prompt templates

  2. Automation

    • Automate repetitive tasks

    • Generate boilerplate code

    • Maintain documentation

  3. Quality Metrics

    • Code quality scores

    • Implementation speed

    • Bug reduction rate