Amazon’s recently launched SageMaker artificial intelligence service is an exciting new development, but the program doesn’t do it all. There’s a distinct gap between innovative AI technology that exists and AI solutions that will help drive business results in your specific case.

Using products such as SageMaker is like having a brand-new Tesla Model S: It’s an awesome car, but it’s a giant electric paperweight if you don’t know how to drive. We discussed “walking” with AI in a prior Entrepreneur article; now it’s time to hit the ground running.

At Manifold, we work with clients using a method called “Lean AI.” Our method is inspired by many other popular processes, including human-centered design by IDEO, agile software development, the Lean Startup methodology and CRISP-DM. Lean AI has six steps: understand, engineer, model, acquire feedback, deploy and validate.

Here, I’ll focus on three key pieces that any entrepreneur will need to follow to optimize AI. Related: 10 Artificial Intelligence Trends to Watch in 2018 Because AI engineering is software engineering, you need to use good practices such as source control, code reviews and clean interfaces, among others.

Many data scientists are guilty of “playing in the sandbox,” but you should always build as if you’re going to production. At Manifold, one of the most important steps we’ve implemented involves using Docker to take advantage of containerized data science. Read more from entrepreneur.com…

thumbnail courtesy of entrepreneur.com