The human core: mentorship and collaboration in a post-PR world

It’s important to acknowledge that for a generation of engineers, the PR description and its comment threads have been the primary vehicle for knowledge sharing and mentorship. 

There’s a risk that losing the PR queue will deepen engineering silos and create a generation of developers who can prompt, but cannot critically evaluate system design. To prevent this, our approach to collaboration must evolve from asynchronous correction to synchronous co-creation.

Mentorship of intent, not syntax

In the past, a significant portion of code review feedback was syntactical or tactical: "Use a map here instead of a loop," or "we have a utility function for this." AI agents are already exceptional at this level of remediation, so mentorship needs to shift upward to the level of intent, architecture and business domain alignment.

Seniors must guide juniors in framing problems, evaluating trade-offs between competing architectural patterns and questioning the underlying assumptions of the product requirements. We are no longer teaching apprentices how to swing the hammer; we are teaching them how to read the blue-prints and understand the soil mechanics.

From asynchronous review to a return to mobbing

Asynchronous code reviews have always been an inefficient way to collaborate. In an AI-native world, this latency is untenable. We need, then, to leverage established synchronous practices like pair or mob programming.

Pairing changes flavor when an AI is in the room. It becomes a triad: a senior engineer, a junior engineer and an AI agent. The senior engineer models the critical thinking, the junior guides the execution and the AI accelerates the generation. This real-time collaboration ensures that knowledge is shared while the system is being shaped, rather than weeks later in a frantic rush to meet a sprint deadline.

Elevating collective ownership

When code is cheap to produce, it is easy to lose a sense of collective ownership. If you didn’t write or review it, is it really your codebase?

To maintain a healthy, shared mental model of our software, teams need to institutionalize new forms of alignment: this includes replacing stale documentation with lightweight, (perhaps AI-assisted) summaries of systemic changes and periodically reviewing parts of the codebase generated by agents as a team, not to find bugs, but to ensure everyone comprehends the system's current topology.