`GitHub Copilot` Your AI Pair Programmer? `#discuss`

A non-coder (learning to code) friend messaged me this morning with the following question:

## "_I just read an Economist article about this. I'd be interested to get your thoughts._"

https://github.com/features/copilot 🤖

I'm on the record https://github.com/nelsonic/nelsonic.github.io/issues/733 as saying that I think **`AI`** will ***replace*** most "***knowledge work***" jobs,
or at least the "junior level" ones in the coming years. `GitHub Copilot` and `ChatGPT` are only the very beginning. ⏳
`AI` isn't science fiction, it's [_inevitable_](https://youtu.be/x5m1A7zoIcc).

I was an **_early_ `Alpha` tester** for `Copilot` a `while` back (invited by `GitHub` as I _appear_ to have amassed quite a few _thousand_ hours of [`JavaScript`](https://github.com/orgs/dwyl/repositories?q=&type=all&language=javascript&sort=stargazers) experience over the years ... who would have thunk it? [Deliberate](https://jamesclear.com/deliberate-practice-theory) [Practice](https://github.com/nelsonic/practice) pays off ... _eventually_! ⏳)

I found it more _frustrating/annoying_ than _useful_ so I stopped using it.
Like an overly enthusiastic puppy that keeps getting in the way instead of being useful.
But as with all things in Tech they keep iterating and _eventually_ become useful.
I haven't looked at it this year simply because I haven't had time.

The writing is very much on the wall: people who are "average" at their job
or just don't have much experience will not be required in _most_ companies
because a handful of _excellent_ engineers will use "AI"
(Language Learning Models: https://www.mlq.ai/what-is-a-large-language-model-llm )
to _assist_ in writing the "boring" bits of code. i.e. any "CRUD" or tests that are generic.
We will reach the point where a skilled (technically literate) Product Owner and _one_ (senior) engineer
can do the work a team of 10+ people because the hardest part is defining the problem that needs to be solved.
As we've seen recently `ChatGPT` can write `SQL` queries: https://news.ycombinator.com/item?id=34521149
So given access to the dataset the _junior_ DataScientist job might be at risk too.

The brilliant @0atman put it _superbly_ in his recent **`No Boilerplate`** episode: "***1,000 AI interns for everyone***": https://youtu.be/glpR1MD1UoM

[](https://youtu.be/glpR1MD1UoM)

> Read through the comments on YouTube, they are insightful.
If you don't already subscribe to his channel, do it _now_. You won't regret it!

Bottom line is this: tools like `GitHub Copilot` will be the "intern" that can do research and make suggestions for you.
But it won't be the **20+ year experienced full-stack engineer** with battle scars and Design Experience that _knows_ ***What*** to build and what to reuse from elsewhere. The best engineers know what code _not_ to write.
Unless `Copilot` also knows how to evaluate 3^rd Party Libraries (which isn't a stretch given the data they have from @dependabot ...) and know when to _resuse_ a function that is available from a dependable/maintained lib ...
I'd say that the job of the _senior_ engineer is "safe" for now.

`GitHub Copilot` is the _How_ not the "Why?" or "What?"
Understanding the organisation/industry problems and teasing out requirements is still going to be the "hard" part.
Crafting [great UX](https://github.com/dwyl/product-roadmap/issues/43) will _eventually_ be automated, but the responses of `AI` tools are still to generic to compete.