Compound Engineering: How Every Codes With Agents by Dan Shipper, CEO and cofounder of Every:

In traditional engineering, you expect each feature to make the next feature harder to build—more code means more edge cases, more interdependencies, and more issues that are hard to anticipate. By contrast, in compound engineering, you expect each feature to make the next feature easier to build. This is because compound engineering creates a learning loop for your agents and members of your team, so that each bug, failed test, or a-ha problem-solving insight gets documented and used by future agents. The complexity of your codebase still grows, but now so does the AI’s knowledge of it, which makes future development work faster.

You have two jobs as an AI-supported software engineer. Engineering software is one of them. Engineering the machine that engineers the software is the other. Equally important.

Today, if your AI is used right, a single developer can do the work of five developers a few years ago, based on our experience at Every.

I’ve been informally polling software engineers for a couple of years now on what they’d estimate is the AI multiplier on their work. 5x is on the high-end of the responses I get, but the mean is going up and up.