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After a decade in backend engineering, Rudratosh Shastri says he stopped treating clever code and visible output as proof of good work. In his personal essay, he argues that solving the underlying problem, building trust, simplifying code, and helping a team succeed matter more. These are lessons from one engineer’s experience, not universal rules—but they offer a useful way to reconsider what junior developers are taught to prize.

Shastri’s essay, “10 Years In, Everything I Was Proud Of As a Junior Was Wrong”, describes a shift in how he judged his work. Its “wrong” is deliberately provocative: the point is not that technical skill or ambition is bad, but that visible signs of cleverness can distract from whether a system works and a team can deliver.

Measure the problem solved, not the code produced

Shastri recalls valuing lines of code shipped and clever abstractions. With experience, he came to prioritize identifying the actual problem and avoiding unnecessary work. Code volume is easy to notice; whether the right failure stopped happening is a more meaningful measure of the result.

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He puts the distinction memorably: “Nobody has ever thanked me for a clever abstraction. They’ve thanked me for making the thing that kept breaking stop breaking.” That is his account of what colleagues valued in his work, not a finding about every engineering team. Abstractions remain useful when they make a system easier to change or reason about; cleverness alone is not evidence that one is needed.

Trust can matter more than winning an argument

The essay contrasts winning technical disagreements with becoming someone colleagues trust to handle difficult projects and mistakes. Shastri presents trust as a professional judgment formed through collaboration, not as a guaranteed route to promotion or a measurable career formula.

In practice, this framing puts weight on how engineers work through disagreement: explain trade-offs, listen to relevant constraints, and take responsibility for outcomes. A technically defensible position can still be delivered in a way that makes collaboration harder.

Hard assignments can be formative

Shastri recalls taking on a high-stakes data migration and an external architecture audit. He describes these as intimidating assignments that shaped his experience. They are personal recollections, not independently verified case studies or evidence that every engineer should accept every risky task.

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The useful distinction is between a stretch assignment and an unsupported gamble. A difficult project can teach judgment when its risks are understood, responsibilities are clear, and appropriate review or help is available. The essay’s examples illustrate the value he found in challenge; they do not establish that saying yes is always the right choice.

Treat code as work product, not personal identity

Another change Shastri describes is becoming more willing to delete or simplify code when the required behavior remains intact. If a solution can be made smaller without losing necessary behavior, keeping it solely because you wrote it serves authorship rather than the system.

This is not an argument for removing code without checking consequences. The decision depends on what the code does and what callers, tests, and maintainers rely on. The underlying lesson is to evaluate a solution by its effect, rather than defend it as an extension of the author.

Technical leadership includes people work

Shastri’s view of engineering broadens beyond individual coding. He includes unblocking colleagues, speaking with kind candor, and absorbing some of a team’s chaos among the work that helps a group function. Those activities may produce less visible output than a feature, but they can change whether other people are able to do their work.

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That does not mean one person should quietly carry every team problem. His essay describes the value he places on support and communication; it does not set a boundary for how much operational or emotional load an engineer should take on.

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Stay willing to be a beginner

Shastri closes with the idea of deliberately learning about AI agents and accepting the discomfort of being bad at a subject again. The point is not that every engineer must pursue the same technology. It is that seniority need not mean protecting an image of competence by avoiding unfamiliar work.

Across these reflections, the recurring shift is from proving personal cleverness to making useful outcomes more likely. The essay offers one engineer’s perspective after ten years, rather than a universal scorecard for careers; its strongest invitation is to question which forms of recognition actually correspond to better work.

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