How AI Has Helped Me at Work

What surprised me most is that the biggest benefit was not writing code faster. In reality, AI has changed the way I approach software development as a whole. It has helped me analyze problems more effectively, understand complex systems more quickly, and spend less time on repetitive tasks.

These are the five areas where AI has had the greatest impact on my daily work.

AI Helps Me Plan Better

One of the most unexpected changes in the way I work has been the growing importance of planning. I have found that the quality of the responses I get from AI is directly related to the quality of the information I provide. When my requirements are ambiguous or incomplete, the results tend to be mediocre. In contrast, when I clearly define the expected behavior, edge cases, and acceptance criteria, the responses improve considerably.

As a result, I now spend more time analyzing problems before I start coding. In many cases, I begin by writing a detailed specification and use AI to identify scenarios I might have overlooked. This process forces me to think through the solution before writing a single line of code.

Paradoxically, AI has made me think more in order to write less code.

AI Writes a Significant Part of the Code

AI has drastically reduced the amount of code I need to write manually. I frequently use it to generate boilerplate, utility functions, API integrations, and repetitive backend tasks.

In many projects I find myself implementing features that require well-known patterns or large amounts of repetitive code. I used to spend a significant part of my time writing these structures from scratch. Today I can generate a first version in a matter of minutes and focus on adapting the solution to the real needs of the project.

This does not mean I can fully delegate the technical work. I still have to make engineering decisions, validate my implementations, and review every solution to make sure it meets the project requirements. I also have to verify that the generated code is maintainable, efficient, and consistent with the existing architecture.

However, many repetitive and mechanical tasks now take only a fraction of the time they used to require. Thanks to this, I can spend more time designing solutions and less time writing repetitive code.

AI Helps Me Debug Faster

For a long time, debugging was one of the most frustrating parts of my work. Problems that seemed simple could easily turn into hours of investigation.

Today I use AI to analyze error messages, understand unexpected behavior, and explore possible root causes. When I run into unclear errors or behavior that is hard to reproduce, I usually provide context, code snippets, and error messages to get possible explanations and lines of investigation.

AI is not always right, but even when its suggestions are not correct, it usually helps me narrow the search space and find a solution faster. Many times it does not give me the exact answer, but it does help me ask better questions and steer the investigation toward the right area.

AI Makes It Easier to Understand Legacy Projects

One of the most valuable benefits I have found in AI is its ability to help me understand legacy systems.

In my work it is common to come across projects developed years ago, where multiple developers have made changes over time. Before, understanding these systems meant reading large amounts of code, following dependencies manually, and mentally reconstructing how the different components interacted.

Today I can use AI to analyze entire sections of code, explain relationships between components, and generate summaries that help me understand the architecture much more quickly.

Although I still need to develop a deep knowledge of the codebase, I now reach that level of understanding in much less time.

AI Helps Me Automate Testing and Accessibility Reviews

Another area where AI has brought enormous value to my work is automation.

I use Playwright together with AI to generate automated tests and reduce the effort required to validate how applications work. Instead of writing every test from scratch, I can generate an initial base and spend my time refining it and adapting it to the specific scenarios of the project.

I also use AI to perform accessibility reviews based on the WCAG guidelines. This allows me to identify potential issues, document them, and generate reports that make the work of development teams easier.

In addition, tools like Figma MCP help me automate visual validations and comparisons between the implementation and the original designs.

Together, these tools allow me to save time, improve the consistency of processes, and focus on tasks that generate greater value for the project.

What AI Does Not Do for Me

Although AI has become a fundamental tool in my work, it is far from perfect.

I have received incorrect answers, recommendations that did not apply to the project context, and code snippets that looked correct at first glance but contained important errors. For that reason, I never assume an answer is correct simply because it was generated by an AI.

I remain responsible for validating the result, understanding the code I use, and making sure that every technical decision makes sense within the project. AI speeds up many tasks, but it does not replace experience, technical judgment, or business knowledge.

Conclusion

If I had to summarize the impact of AI on my work in a single sentence, I would say it has shifted my focus from writing code to solving problems.

I still code every day, but now I spend much more time analyzing requirements, defining specifications, making technical decisions, validating implementations, and ensuring that the solutions meet business needs.

Research, debugging, understanding systems, and testing remain fundamental parts of software development. The difference is that today I can carry out all of those activities much more efficiently thanks to AI.

For me, the biggest benefit of AI is not coding faster. It is the ability to spend more time on solution design and problem solving, and less time on repetitive tasks.