Today, Prefect is the codification of the patterns we observe in modern data engineering. We’ve worked very hard to build a system that can automatically enable best practices, even for data applications it’s never seen before. To see how this works, consider how you can immediately recognize that “the sky is blue” is right

and “sky is blue the” is wrong without memorizing every combination of words in the English language. Just as your brain has broad rules for language, Prefect can detect when something is wrong even when we can’t pinpoint exactly what or why. This capability makes negative engineering much easier and saves our users unbelievable amounts of time and headache.

Prefect is an exercise in simplicity. Negative engineering problems are not always complex, or sophisticated, or difficult. On the contrary: they are often minor, annoying, and repetitive. Consequently, they fall through the sieve we use to identify core issues, even though their aggregate impact is extraordinary. At Prefect, our discovery has been that most data applications can be decomposed into a simple vocabulary, and by focusing on those basic building blocks, we can solve negative issues without sacrificing any of the power or sophistication that positive engineering demands. Our users are granted a creative license to combine those blocks in fascinating and unexpected ways, and Prefect serves as the lighthouse keeping them safe.

At our core, we provide two things. One is our open-source framework, which operates like a hardware store: stocked with all the necessary components for building great data applications. The other is our platform logic, which we think of as the store manager: guiding users to the right tools and making sure their projects are successful. With these two things working together, we can offer a compelling solution for both positive and negative engineering problems.

We’ve posted a brief technical introduction to Prefect here, and can’t wait to share more very soon.

Happy engineering!