As a software developer with over 15 years of experience, I can appreciate the tangible benefits of AI. From Googling errors, to browsing Stack Overflow, Reddit threads, and more, we now have AI-powered IDE assistants that help resolve issues across a vast range of programming languages and paradigms—seemingly without limits.
Having an IDE "assistant" that advises you in real-time on strategies to choose, paths to follow, and best practices to adhere to is a game-changer. However, there's a catch: AI, while incredibly helpful, can sometimes suggest too many things. Its capacity is enormous, and it often provides solutions too quickly, leaving us with little time to process the ideas before blindly accepting them.
The Challenge of Too Many Suggestions
While having numerous suggestions is great and saves time, it can also be overwhelming. If you don't fully understand why these suggestions are being made, how can you decide which option is the best? You risk ending up with a "blind solution" code that you don't fully comprehend or control. This lack of understanding can escalate into deploying solutions that operate in the "unknown zone," where the scope and impact of our changes are unclear.
The Issue of Quick Suggestions
Quick suggestions are fantastic, especially at first. After all, our goal is to solve problems efficiently. However, the danger lies in skipping the critical steps of understanding the problem, comprehending the solution, and learning from the resolution. Without this process, you're not truly learning you are just finding "quick fixes". Over time, this can lead to a lack of growth and a "AI dependency" to do the thinking for (or over) us.
Conclusion
In the past, developers would deeply think, investigate previous similar solutions, and debate the best approaches before settling on a well-voted or widely accepted answer.
Today, we often assume that AI will immediately provide the best solution without requiring our own investigation or critical thinking. Consequently, generating a long term dependency.
AI is, with no doubt, here to stay, and as software developers, we must adapt and evolve to thrive in this new modern AI-driven era.
However, we must also remain "mindful and curious". As, while AI can be an incredible tool, it should complement our skills and knowledge—not replace them. The key is to strike a balance: leveraging AI's power while ensuring "we maintain control, deepen our understanding, and continue to grow as developers". By doing so, we can harness the benefits of AI without losing the "critical thinking" and "problem-solving skills" that define great software engineering.
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