03/02/2026
This is the side of programming many developers avoid discussing… where blind dependence on AI can quietly ruin an application if the fundamentals are missing.
AI-generated code often works, but working code is not the same as secure, scalable, or maintainable code.
When developers rely on AI without understanding:
• authentication and authorization flows
• data validation and sanitization
• API exposure and access control
• state management and error handling
they unknowingly introduce attack vectors.
Common issues in AI-generated applications include:
• Insecure endpoints with no proper access control
• Poor input validation leading to injection attacks
• Hardcoded secrets or unsafe environment handling
• Overexposed APIs that are trivial to exploit
Hackers don’t need zero-day exploits.
They exploit assumptions, defaults, and ignorance.
AI should be used as an accelerator for developers who already understand:
• system architecture
• security principles
• how data moves through an application
If you can’t explain your system without opening the code, you don’t fully control it.
Build with understanding first.
Then use AI to move faster but not blindly.
*This same principle applies far beyond software development.*
"Engineers, designers, writers, analysts, accountants, doctors, and business owners" do not need to depend on AI to think through the entire process of their work.
AI can assist ex*****on, but it cannot replace:
• professional judgment
• accountability
• domain knowledge
• ethical responsibility
When AI makes decisions you don’t understand, you also lose control of the outcome.
AI is a tool and not a substitute for thinking.
Understand your craft first.
Then let AI amplify your skill, not replace it.
