zlacker

>>tablet+(OP)
Can we get a video of a workday conducted by these people?

Unless there's a significant sense of what people are working on, and how LLMs are helping -- there's no point engaging -- there's no detail here.

Sure, if your job is to turn out tweaks to a wordpress theme, presumably that's now 10x faster. If its to work on a new in-house electric motor in C for some machine, presumably that's almost entirely unaffected.

No doubt junior web programmers working on a task backlog, specifically designed for being easy for juniors, are loving LLMs.

I use LLMs all the time, but each non-trivial programming project that has to move out of draft-stage needs rewriting. In several cases, to such a degree that the LLM was a net impediment.

>>mjburg+q4
I have done everything from architecture design for a DSP (Qualcomm), to training models that render photos on Pixel phones, to redoing Instagrams comments ranking system. I can't imaging doing anything without LLMs today, they would have made me much more productive at all of those things, whether it be Verilog, C++, python, ML, etc. I use them constantly now.

>>mgracz+M9
I use LLMs frequently also. But my point is, with respect to the scepticism from some engineers -- that we need to know what people are working on.

You list what look like quite greenfield projects, very self-contained, and very data science oriented. These are quite significantly uncharacteristic of software engineering in the large. They have nothing to do with interacting systems each with 100,000s lines of code.

Software engineers working on large systems (eg., many micro-services, data integration layers, etc.) are working on very different problems. Debugging a microservice system isn't something an LLM can do -- it has no ability, e.g., to trace a request through various apis from, eg., a front-end into a backend layer, into some db, to be transfered to some other db etc.

This was all common enough stuff for software engineers 20 years ago, and was part of some of my first jobs.

A very large amount of this pollyanna-LLM view, which isnt by jnr software engineers, is by data scientists who are extremely unfamiliar with software engineering.

>>mjburg+7b
> it has no ability, e.g., to trace a request through various apis

That's more a function of your tooling more than of your LLM. If you provide your LLM with tool use facilities to do that querying, i don't see the reason why it can't go off and perform that investigation - but i haven't tried it yet, off the back of this comment though, it's now high on my todo list. I'm curious.

TFA covers a similar case:

>> But I’ve been first responder on an incident and fed 4o — not o4-mini, 4o — log transcripts, and watched it in seconds spot LVM metadata corruption issues on a host we’ve been complaining about for months. Am I better than an LLM agent at interrogating OpenSearch logs and Honeycomb traces? No. No, I am not.