If you’ve ever sat through an AI strategy meeting and felt that not everyone was on the same page, you’re not alone. Engineers might be excited about the latest LLM updates while compliance teams flag potential issues, and leadership pushes for bold innovation. This disconnect often means progress stalls when it’s time to move into production.
To bridge that gap, I recommend a structured approach known as The Art of AI Product Development. Built on practical mental models, this framework guides your team through discovery, development, and adoption. Some models work universally across all projects, while others are designed to tackle specific challenges.
This guide introduces four key models that can help you streamline your workflow. You’ll get a clear picture of why these models matter, how to put them into practice, and what pitfalls to steer clear of. With this actionable insight, you can ensure that your team not only talks the talk but also walks the walk towards crafting effective AI systems.
