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Guide: Understanding AI Engineering for Non-Technical Leaders

Guide: Understanding AI Engineering for Non-Technical Leaders
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Unlock your potential as a non-technical leader. Our guide helps you understand AI, master communication with your tech team, and drive innovation.

Intro

Navigating the AI  landscape can feel like deciphering a new language. But as a leader, a foundational understanding of key concepts and how to communicate effectively with your team is your greatest strategic advantage. This guide is your playbook, designed to make you a more confident, collaborative, and impactful leader.

What Does This Guide Include?

  • Main Concepts: Learn the core terms and a nested hierarchy of concepts like Artificial Intelligence (AI), Machine Learning (ML), Generative AI (GenAI), and Large Language Models (LLMs). You will also learn about the importance of high-quality data and data maturity.
  • Key Roles: Understand the responsibilities of key team members, including Machine Learning (ML) Engineers, Software Engineers (SWEs), MLOps Engineers, and Data Scientists, and how they contribute to building a successful product.
  • Effective Communication: Discover how to communicate your business vision to your tech team by focusing on the "why" and articulating desired outcomes instead of dictating specific technical solutions.
  • A Glossary of Technical Requests: Get a comprehensive checklist of common requests from your tech team and understand the reasons behind them, such as the need for a data maturity roadmap, continuous monitoring, and addressing technical debt.

Intro

Navigating the AI  landscape can feel like deciphering a new language. But as a leader, a foundational understanding of key concepts and how to communicate effectively with your team is your greatest strategic advantage. This guide is your playbook, designed to make you a more confident, collaborative, and impactful leader.

What Does This Guide Include?

  • Main Concepts: Learn the core terms and a nested hierarchy of concepts like Artificial Intelligence (AI), Machine Learning (ML), Generative AI (GenAI), and Large Language Models (LLMs). You will also learn about the importance of high-quality data and data maturity.
  • Key Roles: Understand the responsibilities of key team members, including Machine Learning (ML) Engineers, Software Engineers (SWEs), MLOps Engineers, and Data Scientists, and how they contribute to building a successful product.
  • Effective Communication: Discover how to communicate your business vision to your tech team by focusing on the "why" and articulating desired outcomes instead of dictating specific technical solutions.
  • A Glossary of Technical Requests: Get a comprehensive checklist of common requests from your tech team and understand the reasons behind them, such as the need for a data maturity roadmap, continuous monitoring, and addressing technical debt.

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