Technology

Exactly same thinking. I can usually type it out faster than AI (when taking into account latency, context building, prompt writing, prompt fixing, AI hallucination review) if I know what exactly needs to be done.

When you're out of your depth, it shines in providing beautifully confident and a botanical garden of a code piece that wil most likely be broken and break in new and exciting ways. Great for incompetent sycophantically-challenged managers that forgot how to code, or never actually had any experience.

Large-scale code transformations, taking into account the bigger picture of the repository are most likely hallucination free (not generative, just transformative, as per the actual LLM model) and a very exciting use-case.

Also it's currently a very nice pragmatic tool for checking for any mistakes, because it can connect the larger context of the repository quickly to the diff. Terrible if done by a manager without understanding of copilot and workflow, but a great tool if done through claude and cli as a pre-commit step with just quick checklists. Makes plenty of mistakes, but allows to catch your own big mistakes nicely quickly.

After seeing what happened to windows because of this "tool" I think many of us are rightfully skeptical of what will happen to this community.

It happened before, why are we okay with it happening again?

C/C++ compilers are non deterministic due to support of super macros that change run to run, non-deterministic optimisation strategies or ordering due to parallelism, and linkers often produce different outputs every time they are run where subtle bugs can cause crashes when addresses don't line up how you expect. And that's without mentioning projects that use a configuration step.

It's actually a big problem in producing reproducible builds for security.

Or one that pretends compilation was a success when it wasn't.

Technically, LLMs (and most ML models) are deterministic with the same input and same seed.

I get what you mean though.

An LLM is not inherently non-deterministic though - if you don't randomly sample and instead have a fixed rule (which is what the recent fingerprint embedding approach does), if applied in all cases the output is deterministic, as the neural net at its core is deterministic function. A lot of the randomness beyond that is due to optimizations [source].

LLMs are however unreliable at 'compiling'. Whether or not it will be able to complete the requested task (translate human language into code) correctly it not guaranteed - at least nowhere near the compilers we use.

Productivity = Doing more things Efficiency = Doing the right things

I wrote a whole thesis on the subject AMA

So it looks like the source originally used that awful title misrepresenting the article it self. In other words the source needs to be blacklisted for spreading bullshit. Dose this community have a blacklist yet?

I know blacklisting sources is a steep slope to censorship, but at a certain point if the source feels they need to click bait people with tabloid headlines they are not worth our time.

The URL they posted has the same title as the post here so it's the source that changed their title after the fact.

I don’t get the impression he’s fallen in the trap at all.

More so, he sees it for what it is. It’s a tool that can help, but needs smart people that can validate its output. It can’t design entire systems nor effectively solve real world business problems on its own. It’s not going anywhere, so may as well adapt to our new reality.

Source did change the title if you look at the URL matches what OP posted