I honestly just use GPT models nowadays, Claude models are too restrictive and more of a quitter and fable/whatever is just too expensive to be worth it.
I find it useful for code reviews (spawn a subagent with minimal/no context to review X commit). Of course, this is more or less a shortcut that could be done with a seperate agent. Another use is multiple reviews at once if tokens are not an issue, with seperate "personas" or focuses. As far as implementation goes I have not seen any major usecase.
A degree is not a bad thing. This forum is pretty biased on startup culture but I bet the vast majority would say its not worth it personally but worth it on a career level. Even then, the space to explore things outside of your immediate interest is invaluable and you WILL make connections beyond what you expect. Good luck in your studies.
I echo the sentiment. Most work is described as basic and unimaginative, yet we still have every large company having outages despite employing "the best". Even worse, they game uptime and outages in a way that mirrors gerrymandering.
Most likely, this (reverse engineering) is one of the numerous things these LLM companies target. You can also assume all of the internet has been slurped up in to any frontier model. That doesn't mean what you want will be a one shot prompt though...
> For a significantly shorter critque of the book, check out qntm's critique. I mostly agree with qntm assessment. But it's a bit too emotional and personal and doesn't cover the parts i find the most harmful.
This page seems like an actual critique while the blog post doesn't offer much of one, am I missing something?
edit: There is a github linked towards the bottom of the post... full of LLM emoji exclamations.
It is extremely easy to burn tokens if that is required.
Explore this codebase.
Team x wants y feature, research and generate a full plan.
What does feature x in codebase y actually mean?
Analyze code coverage in x.
Map out code flow and find concurrency bugs in y
and on and on...
Oh and my favorite: Use 5 independent subagents to review code change and summarize the findings, and for any finding determine if they are real concerns
People will reply to you calling you crazy, but SF/bay is the only place I have ever experienced where many people will literally leave their cars unlocked because a broken window isn't worth the hassle. Yes, locking your parked car is a hazard here... and the reason is obvious.
Most of my work has been in core infra at large companies. Having the code written faster does not change rollout velocity all that much... It does help with signals and idiot proofing on bugs but when things break and cost real (very real) dollars AI is not an explanation. In that instance, its not even close. Development might be 10-20 percent of the actual work to get a change out.
I seriously doubt it. Degradation would be in some part related to the conditions the painting was held in, which would be nearly impossible to backtrack outside of one-off case studies. Imagine a painting that was stuck in a room full of smoke -- or was put on some less than good backing paper/framing.
There has been some research on what causes degradation on paper/pigment but as far as I know much of it ends up as a mystery, a fact of time...
The only counter I have to this is that there are some workflows that have test environments, everything can't or shouldn't just run locally. Sometimes these test take time, and instead of babysitting the model to write code and run the build+deploy+test manually, you can send it off to work until the kinks are worked out.
Add to that I have worked on many projects that take more than 20 minutes to fully build and run tests... unfortunately. And I would consider that part of the job of implementing a feature, and to reduce cycles I have to take.
After the "green" signal I will manually review or send off some secondary reviews in other models. Is it wasteful? Probably. But its pretty damn fun (as long as I ignore the elephant in the room.)
distributed something or another engineer at Initech