> The most important question for an IA tool is: does it grow the person? Or does it create a dependency which ultimately weakens them? While this is easy to

> The most important question for an IA tool is: does it grow the person? Or does it create a dependency which ultimately weakens them? While this is easy to agree with, there is a counterpoint (and a counter-counterpoint to that): EVEN a bicycle could weaken a person (assuming they're going the same distance). And LLM's can act as amplifiers (skilled devs can learn even faster). The counterpoint can be found in failure, alignment, dependency, and control. - (failure) We know how bikes fail, but think of Crowdstrike, or the Ford Pinto explosions. People have much less of an intuition for failure possibilities of cars, computers, and especially LLM's. - (alignment) Faster = more fatigue, long trips = usually healthy, more weight = more effort, etc. A bike replacing running still keeps all those things true. The amounts are different, but the relationships are the same. With a car though, longer trips ≠ healthy, higher speed = 0 additional fatigue (100mph while falling asleep), more weight ≈ unnoticeable. Amplification isn't always aligned, and misalignment isn't always bad (books don't align with what they replaced). But when a replacement detaches a human from their instincts, there's a major risk. - (dependency) The author mentioned dependency, but its important to point out that if a bike breaks, 99 times out of 100 times it's still possible to walk. Bikes rarely create a dependency. But think of Crowdstrike; there was no backup plan for many 911 services. Cars, computers, and LLM's are often dependency-forming (its good business for them to be) - (control) Manufacturers have very limited control of a bike. Sure, people can't realistically manufacture their own bike. But once a bike is purchased the manufacturer is still pretty much cut out of the picture. Computers and cars used to be more that way, but now they're increasingly less so.