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GenAI is being hailed as a revolutionarycodingtool.
The idea that AI will take over app development overlooks a core aspect of a developers job.
Theres a reason we call them developers or engineers and not code typists.
Writing commands has never been the hard part.
The challenge lies in ensuring the code solves the problem at hand within the products constraints and domain.
The current generation of GenAI doesnt accomplish this.
The developer role is not dead its evolving.
VP of Engineering at Prismatic.
GenAIs limitations in software development
Developers have long used code templates, generators and auto-complete to expediteprogramming.
For example, GenAI can create a code that calculates total sales revenue.
The code technically works, but it does not actually solve the problem.
Additionally, GenAI tools often generate bad code.
AI-generated code can also introduce vulnerabilities and compromise data security by neglecting to follow security protocols.
This risk is made more dangerous by many developers' misplaced confidence in the algorithms.
In light of these challenges, experienced human developers will always be necessary in tool development.
What does the developer of the future look like?
The cooperative relationship between AI and humans could resemble pair programming.
This approach enhances code quality, reduces the risk of errors and maintains consistency.
While GenAI can deliver many benefits, it presents a conundrum for the professional pipeline.
With AI functioning as a junior developer, companies may need to hire fewer entry-level developers.
This scenario remains a problem without a solution one that needs to be answered soon.
Critical thinking and adaptability will become even more essential for success.
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