Below you will find pages that utilize the taxonomy term “code review”
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Labelbox and Wipro Sell AI Agents That Learn From Reviewed Work and Make the Review Step the Real Bottleneck
Labelbox and Wipro announced a partnership on November 10 to put AI agents into enterprise operations. Wipro’s venture arm also invested in Labelbox’s latest Series E round. On the surface it’s a vendor and a systems integrator agreeing to sell together. Underneath is a claim that should interest any team running agents today: the agent gets better by learning from work a human has already reviewed.
What they’re selling Labelbox has two products in the deal.
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Coding Agent Pull Requests Need Review for Behavior and Ownership
A coding agent can open a pull request in minutes. The reviewer still has to decide whether the change solves the right problem, whether it is safe to operate and who will maintain it. A clean diff and a green test run help, but neither answers all three questions.
Consider a request to add a retry to a payment client. The agent may produce tidy code, add a unit test and describe the change accurately.
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AI Pair Programming Has Not Eliminated Code Review — It Has Made It Harder
The promise was efficiency. Feed the prompt, review the output, merge the diff. What teams discovered instead is that AI-assisted code review is more cognitively demanding than reviewing code written by a colleague — not less — because the nature of the errors has changed.
When a human writes a bug, there is usually a traceable cause: a misunderstood requirement, a missed edge case, a copy-paste error. The bug has an author with intent.