Today's AI tools follow the same pattern: initial skepticism, early bugs requiring verification, concerns about control -but potentially enabling another leap in abstraction while keeping the option to fine-tune. No çode solutions on the other hand didn't allow us to drop down.

Both transitions faced skepticism about reliability, performance, and loss of control. Both had early versions that required low-level debugging. Yet both ultimately revolutionized programming by raising the abstraction level while still allowing developers to drop down when needed.

Early assemblers were buggy - devs had to verify output bit by bit. Then in the 50s-60s, when FORTRAN arrived, assembly programmers argued 'why waste cycles on a compiler when I can write better code myself?' Early compilers were unreliable, forcing code inspection.

The resistance to AI in coding reminds me of two major transitions in programming history. When assembly language first replaced machine code in the 1940s, programmers insisted 'if you can't write it in binary, you don't understand what you're doing.