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What You Need to Know About Technical Debt?

Michael Kisilenko, founder and CEO of UVision, explains when it's not advisable to rush with AI development and what you should do to do it efficiently and in a high-quality way

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Michael Kisilenko, founder and CEO of UVision
Michael Kisilenko, founder and CEO of UVision
Michael Kisilenko, founder and CEO of UVision
Michael Kisilenko, founder and CEO of UVision
In collaboration with UVision
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What is Technical Debt?
Technical debt is similar to financial debt. It allows you to get things done faster in the short term, but at the cost of future issues and chaos. Skipping tests, documentation, or planning to release a product quickly creates hidden "debt" that will need to be repaid, usually at a higher price with interest.

How To Manage Technical Debt Responsibly in the AI Age?
The critical question in the technology world centers on companies' need to use advanced automation to accelerate development processes and overcome technological challenges. With that, developing quality code is not a luxury, and it's not something you can compromise on, especially in the long run. The result is still the most important thing.

Are There Cases Where Technical Debt is Necessary or Beneficial When short deadlines or urgent requirements need to be met without delay to gain market knowledge, and where a proof of Concept needs to be built for an investor. If you are lucky, you can produce a working prototype and raise a first investment. Even if you eventually need to start over, it might be worth it.

On which occasions should you hold back rather than rushing ahead In a private survey conducted by the UVision development team, they found that by dedicating one additional hour of code review per day, they could prevent future technical debt. While AI is a tool that can help write quality code, especially in repetitive and well-known code patterns, at critical points, a human should review the code and write the system architecture.

How Can Technical Debt Be Prevented?
The first step is to understand that you need to hire experienced, quality-oriented developers. Using AI to assist development is fine, but AI shouldn't be involved in making critical decisions. AI can write code but cannot understand it, and advanced knowledge is required.

Using automation to test parts of the code is possible, but theoretical foundations need to be investigated, learned, and implemented. The second stage is to execute code reviews on the written code before merging it into the development branch. It's essential to note that nearly every developer has their own development patterns.

Don't immediately trust the system. If code reviews for the project are needed, check if a pattern is too loose or too rigid to implement.

Is there a formula for companies to ensure quality?
Each company has its own methodology. At UVision, we build using modular components and define a transparent development process with frequent testing. We also create internal documentation and guides tailored to the systems we build, which makes maintenance easier and improves the quality of the end product.

The writer is the CEO and founder of UVision, a company specializing in advanced software and artificial intelligence development and creating customized AI solutions for businesses.

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