When agents generate code, the volume of changes can overwhelm human reviewers. Line-by-line diff review doesn't scale - and for many changes, it's the wrong level of abstraction. What reviewers often need is: what did this change accomplish, logically? Intent-based review surfaces that instead of (or in addition to) the raw diff.
People in sales, marketing, operations, and communications could benefit from custom tools - dashboards, scripts, automations - but lack the programming skills to build them. AI agents change that. With an agent as a collaborator, non-engineers can describe what they want in natural language, iterate with the agent, and ship. The design challenge: how do you build products for builders who don't code?
Autonomous agents can execute high-risk operations: database drops, production deployments, payment API calls. Blocking all such operations defeats automation. Allowing them unsupervised creates unacceptable risk. The solution is human-in-the-loop approval: systematic gates for designated actions, with lightweight feedback that doesn't stall the entire workflow.