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For software engineer André Degaspari, thoughtful code reviews made development work more enjoyable by helping teammates, keeping code understandable, and catching problems before they became emergencies. That is his personal experience—not proof that reviews make every developer happier. His account offers a practical way to think about review: serve the customer, support the author, and leave something a future maintainer can understand.
Why reviews changed Degaspari’s experience of the job
In his September 21, 2026 essay, André Degaspari describes code review as more than checking whether a pull request passes. He considers the person who will use the feature and the colleague who may need to modify its code later. A review is useful when it helps deliver the intended behavior while keeping the change consistent with the codebase and understandable over time.
That outlook also made the work feel more collaborative to him. Degaspari says that helping colleagues improve a change—and seeing the codebase remain easier to work with—made his own job more enjoyable. He estimates that a good review takes him “30 minutes to an hour of focused attention.” That is his estimate of his own review time, not a general benchmark.
What he looked for in a review
Degaspari’s questions connect the immediate change to the people affected by it:
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- Does the change deliver the feature the client needs?
- Does it meet the quality standards and architectural expectations of this codebase?
- How can I help my colleagues with my review?
- How can I make my life easier in the future if I have to work on this code?
The questions shift attention from personal preference to purpose: the feature’s requirements, shared engineering standards, the author’s understanding, and the future cost of changing the code.
How reviews helped his team share architectural knowledge
Degaspari gives the example of a microservice initially built with hexagonal architecture and domain-driven design. As team membership changed, he used reviews to point out code that he felt belonged elsewhere and to explain why. Some discussions continued on calls when a pull-request comment was not enough.
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He observed that teammates began thinking more carefully about their submissions, producing better pull requests, and taking greater interest in reviewing each other’s work. Those are observations about his team, not independently measured results. The example does show how a review can transfer context: a comment that explains an architectural boundary can help a colleague make a better decision next time, rather than merely moving one line of code.
What human review should—and should not—do
Degaspari draws a distinction between judgment and mechanical checks. Linting and code-coverage checks can be automated; people can then spend review attention on whether the change meets its requirements, fits the design, and will remain maintainable. Automation and human review complement each other: automated checks handle repeatable rules, while reviewers reason about intent and context.
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AWS makes a related recommendation in its Well-Architected Framework guidance on manual code reviews: include review in the development flow so the author is not the only person checking the code. AWS identifies possible benefits such as consistency, knowledge transfer, and finding issues earlier, and notes that review can be supported by testing and automation. This is practice guidance, not evidence that reviews guarantee those outcomes or make developers happier.
How to make a review useful to both people and the codebase
- Start with the intended behavior. Check the change against the feature the customer needs, rather than treating a passing build as sufficient.
- Apply shared standards consistently. When requesting a change for architectural or quality reasons, explain the reasoning so the author can use it in future work.
- Think about the next maintainer. Ask whether someone unfamiliar with today’s discussion could understand the code and change it later.
- Let tools handle repeatable checks. Use automation for mechanical issues such as linting, leaving people more room to assess requirements, design, and maintainability.
- Use the team’s existing change flow. Fit review into the branch, pull-request, and merge practices the team already uses, rather than making feedback an unrelated last-minute gate.
What the happiness claim does—and does not—mean
Degaspari connects review to fewer bugs reaching QA and code that is easier to understand and change. He also describes a personal motivation: avoiding pressure and late-night emergency work. In his words, “The company benefits from that too, but that’s not why I do it, I do it because it can be the difference between a job I survive and a job I actually enjoy.”
That is a clear account of one engineer’s experience, not a demonstrated causal effect for developers generally. AWS guidance supports manual review as a quality and knowledge-sharing practice, but it does not establish a universal link between reviews and happiness. How review feels will depend on how a team conducts it: comments that explain and teach are different from unexplained demands, and a process that fits the team’s workflow is different from an avoidable bottleneck.
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