{"slug": "code-review-in-the-ai-era", "title": "Code Review in the AI Era", "summary": "An engineer at Snappfood discusses how AI is transforming code review processes in large engineering teams. The engineer notes that AI-generated code increases pull request sizes and speed, but emphasizes the need for engineers to focus on system-level context and define operational boundaries for AI agents. The future of code review, they argue, should shift from evaluating code quality to understanding system impact.", "body_md": "One thing I have been thinking about a lot recently is how AI is changing not only the way we write code, but also some of the engineering processes we have built around software development.\n\nOne of the most interesting ones, in my opinion, is **Code Review**.\n\nFor a long time, Code Review was never just about reviewing a few lines of code.\n\nIn large engineering teams, it has been a mechanism to:\n\nEspecially when multiple teams with different experience levels and working styles contribute to the same product, Code Review becomes one of the ways to keep the codebase consistent and the teams aligned.\n\nOver the past few years working on a large-scale product at Snappfood, I have seen how important this process can be.\n\nWith multiple teams and engineers working on different parts of the product, we gradually evolved our Code Review process:\n\nBut now, with AI becoming a bigger part of software development, a new question has emerged:\n\nIs the Code Review process we built for the pre-AI world still enough for today's development workflow?\n\nOne of the first things we noticed after adopting AI coding tools more heavily is that the amount of generated code increased.\n\nPull Requests became larger.\n\nChanges became faster.\n\nAnd understanding the full impact of a change became harder.\n\nBut I don't think larger PRs are necessarily a bad thing.\n\nThey can even be a sign that teams are moving faster and delivering more value.\n\nThe real challenge starts when the amount of change grows faster than our understanding of that change.\n\nA PR can:\n\nBut still leave important questions unanswered:\n\nI think one of the biggest mindset shifts in the AI era is that our goal should not simply be producing more code.\n\nThe goal should be improving our ability to:\n\nOne interesting behavior I have noticed while working with AI coding assistants is that they often try to find the easiest path to complete a task.\n\nFor example, in our projects, we use tools like **Husky** and **lint-staged** as part of our development workflow.\n\nThey help us catch issues before commits:\n\nThis creates a faster feedback loop and keeps our history cleaner.\n\nHowever, sometimes AI agents try to bypass these steps to complete the task faster, for example by suggesting ways to skip hooks.\n\nThis taught me an important lesson:\n\nWe should not only tell AI what to build. We also need to define how it should operate.\n\nJust like onboarding a new engineer requires:\n\nAI agents also need:\n\nManaging AI behavior will become part of engineering work.\n\nOne of the most interesting and dangerous things about AI-generated code is that it often looks very trustworthy.\n\nThe code is clean.\n\nThe naming is good.\n\nThe structure makes sense.\n\nBut there is a fundamental limitation:\n\nAI makes decisions based on the context we provide.\n\nHere is a real example.\n\nIn one of our tasks, we needed to keep some data inside the codebase instead of a URL, while also making sure the data would survive page refreshes.\n\nAI suggested using **Session Storage**, and from an implementation perspective, it worked perfectly.\n\nThe problem was that AI did not know our system context.\n\nAt Snappfood, we work with thousands of vendors.\n\nIf we stored data for every vendor in Session Storage, this decision could create performance issues at scale or introduce bugs that would be extremely difficult to reproduce and debug.\n\nThe problem was not that AI wrote bad code.\n\nActually, the implementation was reasonable.\n\nThe problem was that AI saw the problem within the boundaries of the code, not within the boundaries of the system.\n\nAnd this is exactly where engineering judgment becomes valuable.\n\nEngineers need to:\n\nHistorically, a large part of Code Review was focused on questions like:\n\nMany of these checks can now be automated.\n\nThe things that still require human thinking are different:\n\nI believe the future of Code Review is not about reviewing less.\n\nIt is about reviewing differently.\n\nMoving from:\n\n\"Is this code written well?\"\n\ntowards:\n\n\"Is this the right engineering decision?\"\n\nOne of the most valuable parts of Code Review has always been learning.\n\nWhen engineers discuss implementation choices, alternatives, and trade-offs, the whole team becomes better.\n\nWith AI generating more code, we need to be careful not to lose that learning process.\n\nInstead of only asking AI to complete tasks, we should use it to improve our thinking:\n\nAI should make us better engineers, not just faster code producers.\n\nI don't think Code Review will become less important in the AI era.\n\nI actually think it will become even more important.\n\nBut the focus needs to change.\n\nWhen producing code becomes faster and cheaper, the real value of engineers will be their ability to understand context, see the bigger picture, and make better decisions.\n\nI would love to hear your experience:\n\nHow has AI changed your team's coding and Code Review process?\n\nWhat has improved, and what challenges are you still facing?", "url": "https://wpnews.pro/news/code-review-in-the-ai-era", "canonical_source": "https://dev.to/leopold2/code-review-in-the-ai-era-105c", "published_at": "2026-08-23 18:37:22+00:00", "updated_at": "2026-08-23 19:13:55.141477+00:00", "lang": "en", "topics": ["artificial-intelligence", "developer-tools", "ai-agents", "ai-products"], "entities": ["Snappfood", "Husky", "lint-staged"], "alternates": {"html": "https://wpnews.pro/news/code-review-in-the-ai-era", "markdown": "https://wpnews.pro/news/code-review-in-the-ai-era.md", "text": "https://wpnews.pro/news/code-review-in-the-ai-era.txt", "jsonld": "https://wpnews.pro/news/code-review-in-the-ai-era.jsonld"}}