The New Era Of
Software Engineering

Ever since AI, coding agents have increased how much code engineering teams can produce. AI makes it easy for teams to optimize for speed of delivery.

Yet, engineers and business owners are still the ones responsible for software, the direct outcome of that code.

Before AI, code review served two main purposes: 1. Catch bugs before they hit production. 2. Build a mental model of the change and the system. Code Reviews spread understanding across the entire engineering team.

But as more and more code gets written every day, and with less time to review it all, understanding falls behind.

Engineers begin approving work they can’t fully explain. They introduce codebase changes without full confidence in what each change actually does.

They lose context for each change: the logic behind new architectural designs, how new tools are being used and why they’re being introduced to the codebase, the security constraints involved, and so on…

Over time, trust in individual changes (and thus the entire codebase) declines.

And that problem will only grow and spread, until it affects every single codebase ever written or touched by coding agents.

That’s why we built Assay. We believe AI can’t restore human understanding of forever changing software on its own, and engineering teams are desperate for a new way to understand, verify, and take ownership of AI-made code.

Agents can perform the work and gather evidence. But engineers must still own and judge the intent, architecture, risk, and acceptance of each software change.

The next era of software engineering must scale human understanding alongside machine output.

And that’s what Assay was designed to do.