snarktank/ai-dev-tasks
Ai Dev Tasks
This project is an AI agent workflow orchestrator and software development framework designed to transform high-level feature descriptions into executable implementation steps for AI assistants. It provides a structured system of prompt templates that guides large language models through the transition from product drafting to technical planning and code execution.
The framework focuses on a methodology for decomposing product blueprints into sequenced lists of technical sub-tasks. It employs a system of prompt engineering to standardize outputs, ensuring that abstract requirements are converted into concrete, granular implementation steps.
The system covers the full development lifecycle, including the drafting of product requirement documents, the generation of technical task lists, and the methodical execution of those tasks. Each step in the implementation process includes a requirement for review and verification before proceeding to the next task.
Features
- AI Development Workflows - Provides a complete AI-driven development workflow from product requirements drafting to final technical execution.
- AI Software Development Frameworks - Provides a structured framework of prompt templates for guiding LLMs from requirements to technical task execution.
- AI Workflow Orchestrators - Orchestrates multi-step reasoning and operational sequences to transform feature descriptions into executable AI tasks.
- Prompt Chaining - Uses a modular prompt chaining pattern to pass context from one AI-driven phase to the next.
- Prompt Engineering - Applies structured prompt engineering patterns to convert abstract requirements into concrete implementation steps.
- Prompt Engineering Templates - Employs structured prompt templates to standardize AI outputs from abstract requirements to concrete tasks.
- Sequential Orchestration - Transforms feature descriptions into a linear sequence of executable steps for AI assistants.
- Verification Loops - Provides an iterative execution loop with mandatory review and verification cycles for each implementation step.
- AI-Driven Development Workflows - Manages the full transition between product drafting, technical planning, and code execution using LLM workflows.
- Task Execution - Directs AI assistants to implement technical tasks sequentially with mandatory verification steps.
- Automated Task Decomposers - Automates the decomposition of product blueprints into sequenced lists of technical sub-tasks.
- Requirement to Task Decomposition - Implements a methodology for breaking down high-level product requirements into granular technical implementation tasks.
- Product Requirements Generation - Guides AI assistants to synthesize high-level descriptions into formal product requirement documents.
- Implementation Assistants - Facilitates the execution of technical tasks via AI assistants with a strict step-by-step verification process.
- AI Coding Assistant Guidance - Provides structured instructions and patterns to guide AI agents in executing technical tasks according to standards.
- Requirement Traceability Frameworks - Links specific product requirement definitions to their corresponding technical task sets for full traceability.
