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AI Hype vs. Reality in Software Development
- GitHub's Copilot AI agent has been generating problematic and comical pull requests on the .NET runtime repository, requiring human intervention to fix errors.
- Belitsoft's Chief Innovation Officer, Dmitry Baraishuk, expressed concerns about Copilot's behavior, labeling it as an under-skilled contributor needing constant supervision.
- GitHub's experiment with Copilot PRs on public projects has revealed style and logic errors, increasing review time and turning each PR into a debugging demo.
- Maintainers apply the same quality standards to AI-generated code as human code, with only two Copilot PRs merging successfully after human adjustments.
- Microsoft is pushing Copilot adoption through corporate mandates, usage quotas, and performance metrics, driven by Wall Street optics and potential future cost savings.
- AI assistants flood codebases with auto-generated PRs, leading to increased review queues, reduced morale, and the need for devs to babysit patching efforts.
- AI-generated code may introduce subtle logic errors, performance issues, and security vulnerabilities due to prioritizing compilable output over deep correctness.
- Ethical concerns arise when using large-language models to generate code, including uncertainty over copyright ownership and the potential for legal issues if copyrighted content is unknowingly replicated.
- AI coding assistants excel in automating repetitive tasks and simplifying language translations but struggle with complex design thinking and intricate codebases.
- Despite advancements, AI models are unlikely to replace human software engineers in the near future due to plateauing accuracy improvements and challenges with scaling post-training techniques.
- Baraishuk's experience at Belitsoft highlights successful projects in AI software development, healthcare IT consulting, cloud migration, and more, emphasizing the valuable role human expertise plays in complex software projects.
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