How to Leave a Thorough Design Doc Review Comment in English

A useful design doc comment does more than say “I don’t think this will work” — it names the specific assumption in question, states why it’s a concern, and ideally offers a way to resolve the uncertainty.

Questioning an Assumption

Surface an assumption the document takes for granted.

• “This section assumes the downstream service can handle the increased request volume — has that actually been confirmed with their team?”
• “I want to flag an assumption here: the doc treats this data as always arriving in order, but I don’t think that’s guaranteed upstream.”
• “Is it a hard requirement that this runs synchronously, or is that an assumption we could revisit if it simplifies the design?”

Flagging a Risk or Edge Case

Name specific scenarios the design might not handle.

• “What happens in this design if the third-party API is temporarily unavailable — is there a fallback, or does the whole flow fail?”
• “I don’t see this addressing what happens if two requests for the same resource arrive concurrently — is that considered out of scope?”
• “This seems to assume a single region, which could be a problem if we ever need to run this multi-region — worth noting as a known limitation, at least.”

Proposing an Alternative Approach

Suggest a different direction without dismissing the existing plan outright.

• “Have you considered an event-driven approach here instead of polling? It might reduce the load described in the risks section.”
• “One alternative worth considering: instead of a new service, could this logic live inside the existing service as a new endpoint?”
• “I’m not saying this approach is wrong, but I’d like us to at least compare it against a queue-based design before committing.”

Asking About Scope and Trade-offs

Clarify what the design is explicitly choosing not to solve.

• “Is backward compatibility with the old API version explicitly out of scope here, or just not mentioned yet?”
• “This design trades some latency for simplicity — is that trade-off intentional, and has it been validated against our latency requirements?”
• “What’s the plan for migrating existing data, or is that being handled in a separate document?”

Closing With a Clear Recommendation

Summarize your overall position so the author knows where you stand.

• “Overall I think this is a solid direction — my main concern is the concurrency edge case, which I’d want addressed before implementation starts.”
• “I’m supportive of this approach as long as the fallback behavior for the third-party outage gets documented explicitly.”
• “I don’t think this is ready to move forward yet — the open questions around data migration feel significant enough to resolve first.”

Vocabulary Reference

Key Takeaways

• Name specific assumptions in a design doc explicitly, rather than vaguely saying something “feels off.”
• Flag edge cases and failure scenarios concretely, asking what the design does in each specific case.
• Propose alternatives as options to compare, not as a dismissal of the existing approach.
• Ask directly about scope boundaries and trade-offs so they’re documented rather than left implicit.
• Close with a clear overall recommendation so the author knows whether their design is ready to proceed.

Navigating Nuances: Refining Your Approach with Precise Language

Let’s be honest – even the most brilliant designs can benefit from careful scrutiny. When reviewing a design document, it’s not just about spotting errors; it’s about engaging in a productive conversation that clarifies assumptions, mitigates risks, and ultimately strengthens the final product. Often, native English speakers find themselves hesitant to directly challenge or suggest alternatives within this formal context, fearing they might sound critical or uninformed. This hesitation can lead to vague comments like “looks good” or “needs work,” which offer little actionable feedback for the designer. To truly contribute effectively, you need a toolkit of precise phrases and vocabulary that demonstrate thoughtful engagement without appearing overly judgmental.

One key area is acknowledging potential risks before leaping to solutions. Instead of simply stating “This could fail,” try phrasing it as: “I’m wondering if we’ve fully considered the implications of [specific scenario]. Perhaps exploring a fallback mechanism for [feature] would provide added resilience.” This approach subtly highlights your concern without immediately prescribing a fix. Similarly, when questioning an assumption – say, regarding user data privacy – avoid statements like “Are you sure about this?” Instead, use phrases like: “Could we elaborate on the data retention policies associated with this module? It’s important to ensure alignment with GDPR regulations.” Framing questions around clarification and best practices demonstrates your commitment to quality.

Another crucial element is offering constructive alternatives. Don’t just point out what’s wrong; suggest how it could be improved. Instead of “This isn’t scalable,” consider: “For future growth, would it be beneficial to architect this component with a microservice approach, allowing for independent scaling?” The addition of ‘would it be beneficial’ softens the suggestion and invites discussion rather than presenting it as an absolute requirement. Finally, remember that clear communication extends beyond written documents. A quick Slack message after reviewing a PR description can be just as impactful: “Just wanted to flag that the API endpoint documentation is missing some key parameters – could we add those in before merging?” This proactive approach shows you’re invested in the process and helps avoid misunderstandings down the line. Practicing these phrases will not only improve your English but also significantly elevate your contributions within a technical team.