Everyone says AI will replace programmers and make coding effortless… but the real truth is very different.
AI is generating more code than ever, but the quality is dropping fast — more bugs, more duplicate code, more technical debt, and longer PR reviews.
In this video, I break down why AI makes you feel productive, but can actually slow teams down if you rely on it blindly.
AI is powerful, but only when you use it like a tool — not like a replacement for engineering thinking.
✅ Watch till the end to learn how real engineers use AI correctly: for boilerplate, tests, docs — but not architecture or core logic.
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Tags:
ai coding,ai replacing developers,ai for programmers,chatgpt coding,github copilot,ai software engineering,ai developer productivity,ai code quality,ai bugs,technical debt,software architecture,clean code,refactoring,code review,pr review,engineering mindset,developer skills,system design,ai tools,programming career,developer future,ai vs developers,coding with ai,ai programming truth,software development
HashTags:
#AI #SoftwareEngineering #Programming #Developers #ChatGPT #GitHubCopilot #SystemDesign #CodeQuality #TechCareer #coding
Chapters:
0:00 AI will replace developers? The real truth
0:10 AI writes more code, but quality is dropping
0:25 The “just prompt it” lie
0:38 Code churn + duplicate code problem
0:55 Feeling fast vs shipping slow
1:10 AI code = more bugs + more PR review time
1:30 The “crooked bricks” analogy
1:48 AI can’t see the full system
2:05 Merging code you don’t understand is dangerous
2:25 The right way to use AI as an engineer
2:40 Final lesson: system - code
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