ai-engineer

Name: ai-engineer
Availability: InStock
Author: Aviskaar

Orchestrate full-stack development from research papers to production software products.

6|1|Updated Feb 20, 2026

Search Tags:#full-stack #ai #orchestration #engineering #product #research-to-product

Ready to run

npx skills add https://github.com/aviskaar/open-org --skill ai-engineer-aviskaar

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-engineer
Source: https://github.com/aviskaar/open-org/tree/main/skills/ai-engineer
Command: npx skills add https://github.com/aviskaar/open-org --skill ai-engineer-aviskaar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill bridges the gap between research breakthroughs and production-ready software, orchestrating the end-to-end development process from initial research concepts to a fully scaled product.

Core Features & Use Cases

End-to-End Product Development: Manages the entire software development lifecycle, including PRD creation, tech stack selection, AI/ML integration, backend development, and UI delegation.
Research-to-Product Translation: Ensures research findings are accurately translated into product requirements and implemented correctly.
Orchestration of Sub-skills: Coordinates specialized skills like auto-website-builder and lead-researcher for a cohesive build process.
Use Case: A research team has developed a novel image recognition model. The AI Engineer skill takes the research paper, defines the product requirements, selects the tech stack, integrates the model, and orchestrates the build of a web application that leverages this model, delegating the UI to auto-website-builder.

Quick Start

Use the ai-engineer skill to transform the research paper 'novel-image-model.pdf' into a production-ready web application.

Frequently Asked Questions about ai-engineer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I turn an AI research paper into a production-ready software product?▼

To turn an AI research paper into a production-ready software product, orchestrate the full-stack development lifecycle by translating research findings into PRDs, selecting a tech stack, integrating AI/ML models, and coordinating backend development.

What is research-to-product engineering and how does it work?▼

Research-to-product engineering bridges the gap between AI research breakthroughs and production software. It works by managing the end-to-end development process, accurately translating novel models into product requirements, and integrating them into scalable backend architectures.

How do I manage AI integration and backend development for a new ML model?▼

Managing AI integration and backend development for a new ML model requires defining product requirements and designing a full-stack architecture. You orchestrate the integration of the model into the backend while delegating UI tasks to specialized sub-skills.

Can I automate tech stack selection and PRD creation from research findings?▼

Yes, you can automate tech stack selection and PRD creation from research findings. The orchestration process translates research data into structured product requirements and selects appropriate architectures to build a scalable web application.

Does full-stack AI orchestration work with delegated UI and frontend builds?▼

Yes, full-stack AI orchestration works with delegated UI builds by using specialized sub-skills like auto-website-builder. The engineering lead coordinates backend AI integration while delegating frontend web application creation to these tools.