operation and exploration
if a task is repetitive, routine, mechanic, it should be hard programmed, no llm/genai needed. that will be efficient, stable, and scalable.
if a task is abstract, ambiguous, high level, open ended, one-time, explorative, then llm/genai is needed.
genai can help to build and improve code.
many operational tasks are routine and repetitive, those tasks should be programmed
writing, solving a new problem, improving are not repetitive, they are explorative
program is like cache, data, that are repetitively retrieved (and then executed). it’s data for a certain procedure. potentially highly optimized.
evolving code is explorative, genai can be a good helper or sometimes can do better than human
so genai can be viewed as a good tool to speed up building
but not good at executing
it’s a multiplicator to human intelligence
human + genai can build more things, better things, faster
then it poses challenges on resources
as running more things needs more resources
that’s why power shortage is the bottleneck
as genai is 1) not efficient, 2) human are generating more resource demand (solving more problems) by using genai, 3) more things build need more resources to run.
but some resources are limited
like human attention
so content created by genai could potentially leads to worse overall quality
as genai content is cheap, and more worse quality content are made
code has the same quality risk
time will be shifted to code review, high level design and quality eval
research / science / solving problems has no limit
once a problem is solved, it’s solved, no need to resolve the problem
and there are limitless problems
so they will benefit the most