Prinevo: when review capacity is full, stop starting new agent work
Oct 29, Sohit Kumar of Prinevo argues that adding coding agents won't shrink a review queue: define what a change needs before handoff, give review and QA agents separate jobs, and stop starting work when qualified reviewers are saturated.
Source: How to Reduce Code Review Bottlenecks When Coding Agents Write the Code
In How to Reduce Code Review Bottlenecks When Coding Agents Write the Code, Sohit Kumar of Prinevo opens with a blunt line: adding another coding agent will not help the review queue. His first step is diagnostic. Follow a few recent PRs from implementation to merge and record what actually held each one up, because "code review" hides different jobs: finding the requirement, starting the app, asking whether anyone checked a background worker, or waiting for the one owner qualified to approve.
He then separates the work agents can do before a human sees the change. A review agent checks the implementation against the requirement, contracts, and conventions. A QA agent runs the behavior in a named environment and reports what happened. Findings go back to the implementation owner with the revision, the expected and observed behavior, and the evidence, and the relevant checks run again on the corrected revision. Earlier findings stay visible rather than being replaced by a final green result. Loops get limits: if agents disagree about the requirement or can't reproduce a failure, they escalate with evidence instead of retrying forever.
"Ready for human review" becomes a short handoff record: the accepted requirement, affected components and related PRs, the tested revisions and environment, findings and fixes, checks that failed or never ran, and the decisions still waiting on the named reviewer. The post is partly a pitch for Prinevo's own workflow, and its trial-status example is illustrative rather than measured.
Why it matters for code review
The sharpest advice is about intake. When agent work arrives faster than qualified owners can assess it, Kumar says to put agents and engineers on closing findings, reproducing failures, and preparing existing changes, and not to keep starting work simply because code generation is available. That is a direct answer to the pull of keeping agents busy around the clock: steady output only compounds if review capacity grows with it, so he suggests watching waiting time and unfinished work rather than PR counts.