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No—not necessarily. Egor Kraev’s case for reading less agent-generated code is not a case for blind trust: it is a first-person account of a workflow built around explicit plans, tests, reviews, automated checks, and trying the finished software. It explains one developer’s choice, not a proven rule for every team.
What Kraev means by reading less code
In his DEV Community essay, “Why I no longer read code (much)”, Egor Kraev describes reducing how much of the code produced by coding agents he personally reads. He does not describe stepping away from the work. Instead, he puts oversight into several stages and still tries the finished software for its intended purpose.
That distinction matters. The question is not simply whether to inspect generated code or trust it. It is how to check that a change matches its intended behavior, works in practice, and fits the system as a whole—and how much direct code reading is useful alongside those checks.
How his workflow is organized
Kraev separates planning, test writing, implementation, and review rather than asking one agent session to handle everything at once. He uses fresh sessions between stages and describes this sequence:
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- Plan the change. He records the goals, implementation details, and other task context he can think of. Claude, using Fable, interviews him about design decisions, edge cases, and things he may have missed. Codex reviews the resulting plan; it is then converted into OpenSpec artifacts and validated.
- Write tests from the specification. In a fresh session, an agent writes tests based on the specification. Codex reviews the tests, and Kraev incorporates feedback he considers valid.
- Implement against the agreed materials. A separate fresh session implements the change using the goals, design, and tests. Kraev says the agent asks before pushing or creating a pull request.
- Run an iterative review loop. Once the pull request exists, the process gathers CI results, reviews from Codex, Sonar, and CodeRabbit, and deterministic-script results. Feedback is triaged and addressed in further iterations until the gates report no issues. The OpenSpec artifacts are then archived and the change merged.
- Use the feature. Kraev says he still “kick[s] the tires” by trying the software for its intended purpose, even when doing so does not require reading the code.
In this arrangement, reading less code is paired with scrutiny of the plan and tests, automated and review feedback, repeated fixes, and hands-on use of the result. The essay describes Kraev’s process; it does not measure how reliably those controls catch defects.
What the essay says the process achieves—and what it does not establish
Kraev says the workflow has surfaced and addressed more edge cases and choices than he can count. He also believes the resulting code is more reliable than code he previously wrote by hand. Those are his assessments: the essay provides no benchmark, comparison group, failure rate, or study design that would establish a measured improvement.
That makes the essay useful as a description of one way to organize oversight, but not evidence that other developers or teams should stop reading code. A process can make review more systematic without proving that its gates will catch every important problem.
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Why architecture still needs attention
Kraev identifies architectural erosion as a weakness his process does not yet address cleanly. Individual pull requests can appear sound while their combined effects make a system harder to maintain. Passing checks on one change does not, by itself, show that many changes continue to fit a coherent design.
His current response is to conduct periodic interactive reviews and make refactors in separate pull requests, guided by high-level principles. He says he is exploring more reproducible architecture representations and a principles-first design, but does not report results from those ideas. This is a separate oversight concern from whether an individual feature behaves as specified.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to decide how much code to read
Kraev’s account points to useful questions for evaluating an agent workflow, rather than a universal reading quota:
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- What is the change supposed to do? Can the goals, design choices, and edge cases be stated clearly enough to guide implementation and review?
- How are tests and other checks assessed? Tests derived from a specification and automated gates provide signals, but their presence alone does not establish that the specification or coverage is adequate.
- Who checks the decisions behind the change? The workflow described by Kraev includes review of both the plan and the tests, not only the finished implementation.
- Has the feature been tried as users will use it? Kraev includes exercising the software for its intended purpose as a distinct check.
- Who watches the system across multiple changes? His discussion of architectural erosion shows why reviewing each pull request in isolation may not answer whether the design remains maintainable over time.
These questions are practical ways to think about oversight, not a validated scoring framework. How much direct code reading remains valuable depends on what a change affects and what other checks can actually establish. Kraev’s essay invites debate; it does not settle that decision for every project.
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