Over the past few months, we've been actively using Cursor and integrating AI agents into our development workflow. One insight stood out: while the tools are new, the fundamental software engineering process hasn’t really changed.
What has changed is when and how we involve AI — and what that does to our role in the process.
We now bring the AI agent in from the very beginning. Together, we go through the familiar early steps: discussing the task, outlining the architecture, selecting technologies, and breaking the project into stages and actionable items. This early collaboration has proven valuable — it gives the agent context. As a result, it can generate useful artifacts and stay grounded in the structure of the project as it evolves.
Once the groundwork is set, the agent handles a large part of the implementation. It writes code, runs basic tests, and corrects issues in real time. At that point, our focus shifts. Instead of writing code ourselves, we spend more time reviewing — making sure the output matches the original intent, spotting logical inconsistencies, and guiding the agent through complex scenarios.
This doesn’t always make things faster. Iterating with the agent takes time. Instructions need to be clear. And some back-and-forth is inevitable, especially on non-trivial tasks. But the upside is significant: we avoid a lot of routine work and preserve mental energy for areas where human judgment matters most — design decisions, abstraction, and long-term direction.
In short, AI tools like Cursor don’t eliminate engineering — they rebalance it. We move from execution to oversight, from implementation to intent. We’re still following the same principles. But our time is spent differently.
That shift has been the most notable change — and, arguably, the most valuable one.
Curious to hear how others are adapting. Are you involving AI in early-stage planning too?
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