Classic machine learning researcher trick: just select your test example from the training set! It certainly saves a lot of effort.

Mgmt at every company is asked - what are you doing to be agentic ?

so, they organize hackathons where devs build a hypothetical agentic framework nobody will dare use. So, mgmt can claim, look here what i have done to be agentic.

you should ask: would you dogfood your agent, and the answer is no way. these are meant purely for marketing purposes, as they dont meet an end user need.

I think the process could be better, but if you want good quality you really shouldn't expect it to just jump at the "obvious" thing. Just like you wouldn't want the developer to just make the error to away in the quickest way. Getting more context is always going to be a good idea, even if it wastes some time in the "trivial" cases.

it takes more time to watch the video than fix the bug

All the project/product managers that think they are the ones responsible for team success are going to get a rude awakening. When they try to do the job of an entire team, it's going to come apart pretty quickly. LLMs are a tool, nothing more, they don't magically imbue the user with competency.

I don't care. I swore to myself that if the time comes my skills will no longer be needed, I'd gracefully ride into the sunset and do some other thing.

Developers are not going to go away, but the cushy high salaries likely will. Skill development follows a logarithmic curve where an AI boost to junior devs will be much more than the boost given to senior devs. This discrepancy will pull down the value of devs as you will get "more band for you buck" from lower tier devs, since the AI is comparatively free.

Although I also wonder about the development of new languages that may be optimized for transformers, as it seems clumsy and wasteful to have transformers juggle all the tokens needed to make code readable by humans. That would be really interesting to have a model that outputs code that functions incredibly but is indecipherable by humans.

It will suck to babysit LLMs as a job. In one sense perhaps it will be nice to have models do the chores. But I fear we’ll be 90% babysitting. Today I was in an hour long chat with ChatGPT about a problem when it circled back to its initial (wrong) soliton.

I have very little fear for my own job no matter how good models get. What happens is that software gets cheaper and more of it is bought. It’s what happened in every industry with automation.

Those who can’t operate a machine though (in this case an AI) should maybe worry. But chances are their jobs weren’t very secure to begin with.