Why Big Tech Sticks to Outdated Tech: Code Chaos and Process Pitfalls
The article examines why many large, well‑known tech companies suffer from messy code, chaotic development processes, and reliance on outdated technologies, exploring the underlying personnel dynamics, reconstruction costs, and the tension between business and technical value.
Background
Many recent graduates aim to join large, listed, well‑known companies, believing that bigger firms are more stable, use modern technologies, and have standardized processes. However, after joining, they often encounter a reality that differs sharply from these expectations.
(1) Code Chaos
I. Multiple implementations of the same utility, e.g., different Http request wrappers, coexist in the codebase.
II. Frequent copy‑and‑paste without proper attribution, leading to duplicated code.
III. Inconsistent logging styles, with some critical steps lacking logs.
IV. Extremely large classes, missing comments, and methods with dozens of parameters are common.
(2) Development Process Chaos
I. Inconsistent IDE and JDK setups; developers upload personal configuration files to the server. II. Lack of documentation; debugging often requires reverse‑engineering existing code. III. Developers spend most of their time fixing bugs, treating work as a routine rather than striving for quality.
(3) Technological Lag
I. Use of outdated technologies such as JSP with massive Java codebases. II. Architectural oversights, like message queues without persistence or encryption, risking data loss and security. III. Performance tuning is done ad‑hoc without systematic analysis.
Reasons
Personnel Levels
In large firms, senior talent often leaves, leaving behind average engineers who perform repetitive, "screw‑driving" tasks without skill growth. Two types of employees emerge:
Average employees complete requirements without caring about code quality.
High‑performing engineers care deeply about code, but their expertise is underutilized, leading them to leave for better compensation.
Because salary growth is tied to rigid company policies, high‑performers often feel underpaid and move on.
Reconstruction Cost
Legacy code becomes "ancestral code" that is difficult to refactor. Attempts to improve performance may be outweighed by the cost of maintaining such code, especially when management prioritizes short‑term delivery over long‑term quality.
Company Nature
Many companies prioritize business value over technical value. Product managers may earn more than engineers, and decisions are driven by deadlines rather than architectural soundness.
Self‑Reflection
Readers are encouraged to examine why they end up in companies that use outdated technologies and to consider how to improve their own skills and career choices.
Conclusion
The author hopes readers will continuously improve themselves, reduce complaints, and focus on meaningful growth rather than merely following the status quo.
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