How can feedback be passed between AI design and engineering agents?
Pass useful feedback between AI design and engineering agents with shared references, precise issues, resolved decisions, and clear verification steps.
How can feedback be passed between AI design and engineering agents?
Feedback between AI design and engineering agents should be treated as an explicit handoff. Each message needs enough context for the receiving agent to understand the problem without reconstructing an entire conversation.
Use a shared specification
Identify the feature, approved design version, implementation version, and relevant requirement. Keep field names, user roles, and interaction states consistent across the design and engineering documents.
For task management, both agents should agree on supported statuses, whether assignment is optional, and which users can edit. If the design shows a priority field that the data model does not support, record that mismatch as a decision to resolve.
Express feedback as an actionable issue
Describe the observed state, expected result, and constraint. An engineer might report: “The mobile task form needs space for inline date errors; the current layout hides the save action when an error appears.” The design agent can respond with an adjusted layout and interaction guidance.
In the other direction, a design agent might identify unclear completion feedback and specify the intended pending, success, and failure states. Avoid forwarding vague comments such as “make it cleaner” without explaining the affected journey.
Close the handoff with a recorded outcome
A responsible developer decides whether feedback changes scope, resolves conflicting suggestions, and updates the authoritative references. The receiving agent should acknowledge the agreed change through an implementation or revised specification.
After implementation, verify the exact scenario that prompted the feedback. Share the result and any remaining limitations. This creates a useful cycle of observation, decision, correction, and verification, while preventing agents from repeatedly reopening the same question or implementing different interpretations of the feature.
No. Provide a concise issue with current references and the agreed outcome. Long histories often contain superseded ideas that can confuse the receiving agent.
The responsible product owner or developer makes that decision. Agents can explain implications, but a suggestion should not silently become a new release requirement.
Reproduce the original scenario against the updated design or implementation and compare it with the expected result. Record the outcome instead of relying only on acknowledgment.
Related learning resources
Ready to master AI completely?
Want to upskill yourself, crack your next interview, and get your dream job? Join our comprehensive course to dive deeper with high-quality video tutorials, solve interview questions, and a premium community.
Master AI
Want to upskill yourself, crack your next interview, and get your dream job? Join our comprehensive course.

