For me it's really goddam satisfying having good autocomplete, especially when you are just writing boilerplate lines of code to get the code into a state where you actually get to work on the fun stuff (ther harder problems).

Also if your code gets sent to someone else's cloud?

Have you ever had your code repository hosted by Github, Bitbucket, Gitlab or similar?

If so, all your code is sent to cloud.

Answer: yes, some code. But other code I and my company like to keep private.

Where exactly is the repo hosted if there is one?

There are alternatives out there for self-hosted git. I have a Gitea instance running on a mini PC at home for my own projects.

Do you have backups of that as well? If something were to happen to your mini pc would you lose your code?

Great question, yeah I do. Right now it backs up to a separate NAS on my home network. Every once in a while I'll copy the most important directories onto a microSD card backup, but its usually going to be at least a few weeks out of date.

Own servers.

Do they manage their own servers? I wonder what proportion of companies would have in house servers managed by themselves.

They are colocated in a data center and you need physical keys to access the rack.

It's common for companies to have something like self-hosted GitHub Enterprise or self-hosted GitLab hidden behind the company's VPN.

But where is the box where it's hosted? Is it in-house?

Internally hosted gitlab instances are a thing.

They are, but frequently the boxes where they are hosted are in AWS or similar. Or do frequently companies have actual in house servers for this purpose?

Not in house, but in a "segmented" part of the cloud that comes with service level agreements and access control and restrictions on which countries the data can be hosted in and compliance procedures etc. etc.

An extreme example of this would be the AWS GovCloud for government/military applications.

I don't care. The vast majority of code written in the private space is garbage and not unique. Products are usually not won because of the code.

Would I send the source of a trading algo or chatgpt to a third party, probably not but those are the outliers. The code for your xyz SAAS does not matter.

I am probably an outlier in that I don't really care what corpus a LLM trains off of. Its its available in the public space, go for it.

The problem being that the time spent fixing the bugs in that 25% outweighs the time saved. Now that tools like Copilot are being widely used, studies are showing that they do not in fact boost productivity. All claims to the contrary seem to be either anecdotal or marketing fluff.

https://www.techspot.com/news/104945-ai-coding-assistants-do...

As far as I know, LLMs are a genuine boost for junior developers, but still not close to what senior/principal engineers get up to.

It'd be interesting to know how much of Google's code is written by junior engineers. I can't imagine 25% of the code is from juniors, at which point Google's CEO is either exaggerating what he considers LLM-generated code or more than just juniors are using it.

I agree with your take though, it does seem helpful to juniors but not beyond that (yet), and this OP stat seems dubious unless juniors are doing a big portion of the work.

I have around 7 YOE, and I have found LLMs useful for very specific questions about syntax whenever I am working in a new language. For example, I needed to write some typescript recently and asked it how can I make a type that does X.

It is not as good with questions about API documentation for popular java libraries though and it will just hallucinate APIs/method names.

If I ask it a generic question like "how can I create a class in Java to invoke this API and store the data in this database" it is pretty useless. I'm sure I could spend more time giving it a better prompt but at that point I can just write the code myself.

Overall they are a better search engine for stackoverflow, but the LLMs are not really helping me code 30% faster or whatever the latest claim is.

The AI tap complition is >100000% better than the coding assistants, it just saves you typing and doesn't introduce new bugs you need to fix instead of writting buggy shitty code from a text description.

25% is a great win if you are prone to RSI. And for quicker feedback. But in terms of the overarching programming goal? Churning out code is a small part of it.

Code is often a liability.

"rm re[TAB]" to remove a file called something like "report-accounting-Q1_2024.docx" is really helpful, especially when it adds quotes as required, but not exciting enough to get me out of bed any earlier in the morning.

I feel it's a bit like the old "measuring developer productivity in LoC" metric.

As I hinted at in another comment, in Java if you had a "private String name;" then the following:

    /**
     * Returns the name.
     * @return The name.
     */
    public String getName() {
        return this.name;
    }

and the matching setter, are easy enough to generate automatically and you don't need a LLM for it. If AI can do that part of coding a bit better, sure it's helpful in a way, but I'm not worried about my job just yet (or rather, I'm more worried about the state of the economy and other factors).