Why IT Teams Struggle with Code Documentation and How to Fix It
434Most IT teams know that poor documentation can turn into a big headache. When legacy systems are involved, lack of clear records makes fixing bugs, upgrading systems, and onboarding new staff much harder. But what’s less discussed is why teams tend to skip documentation in the first place. The truth is, a lot of the blame falls on the managers who were in charge when the code was written. They often didn’t prioritize or enforce thorough documentation, setting a pattern that continues today.
Why Developers Avoid Documenting Their Work
Developers generally dislike documenting their code. It’s not the fun part of their job. Coding is creative and rewarding; documentation feels like a tedious chore after the excitement of building something. Once they finish a project, most want to move on to the next task quickly. Spending extra time explaining each decision or detail feels like an unnecessary slowdown.
Another big reason is self-preservation. Developers know that if their code isn’t well documented, managers might hesitate to lay them off later. Good documentation can make a coder’s work more visible and easier to understand, which might protect their job. Conversely, if they leave the company, poor documentation means someone else has to spend time figuring out their work. This can lead to more consulting gigs for the departing coder, who might be incentivized to leave things vague.
This pattern isn’t new. It’s a cycle that repeats with each generation of developers. The same reasons for avoiding documentation apply to the original programmers who wrote legacy code decades ago. Today’s managers often complain about outdated documentation, but historically, they might have made the same choice—to skip documenting in favor of moving on to the next project.
The Role of Management and AI in Fixing the Issue
It’s often the case that managers want developers to produce comprehensive documentation, but their actions suggest otherwise. They prefer their teams focus on delivering new features or fixing urgent bugs. Documentation is seen as a low priority, and developers are rewarded based on their output, not the quality of their records.
There’s also a psychological element at play. Many developers see documentation as tedious and unnecessary. They believe that good code should be understandable without lengthy explanations. Because of this mindset, they resist spending time on detailed records, especially when deadlines are tight and performance is rewarded.
Some wonder if AI tools could help. Generative AI can assist in creating documentation by analyzing code and generating summaries. But there’s a catch. Developers often don’t want to create documentation themselves, and they may not trust AI to fully understand their intentions. AI tools could help after the fact, but only if they work closely with the coder throughout the development process. Otherwise, the AI might produce vague or inaccurate records, which defeats the purpose.
Could AI also help fix legacy code? Some experts believe that advanced AI might identify problems in old systems and suggest fixes. If AI could reliably do this, it might reduce the need for extensive documentation. However, AI still struggles to fully grasp complex, outdated code without human context. Plus, developers might resist letting AI take over their work, especially if it threatens their job security.
Research managers like Adam Resnick point out that poor documentation hampers efforts to modernize legacy systems, perform security audits, or troubleshoot bugs. He emphasizes that companies often prioritize quick delivery over good records. Incentives tend to reward coding speed and feature delivery, not documentation quality. Developers see documentation as boring and unnecessary, which leads to it being neglected, especially in older systems that haven’t been updated in years.
Resnick suggests that one way to improve the situation is to incentivize developers financially. Tie bonuses or promotions to good documentation practices. If companies value documentation as much as they do new features, teams might change their habits.
In the end, fixing this problem involves changing priorities across the board. Recognizing that good documentation saves time and effort in the long run can motivate better habits. Incorporating AI thoughtfully and rewarding thorough record-keeping could help break the cycle of neglect and make legacy systems more manageable.
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