Readit NewsMy boss said we were gonna fire a bunch of people “because AI” as part of some fluff PR to pretend we were actually leaders in AI. We tried that a bit, it was a total mess and we have no clue what we’re doing, I’ve been sent out to walk back our comments.
VP->Public: "We'll replace all our engineers with AI in two years"
Boss->VP: "I mean we need to fire VPs because AI"
VP->Public: "Replacing people with AI is stupid"
Without this, AI is going to be limited and kloodgy. Like if I wanted to have AI run a FEA simulation on some CAD model, I have to wait until the FEA software, the CAD software, the corporate models repo, etc., etc. all have AI integrations and then create some custom agent that glues them all together. Once AI can just control the computer effectively, then it can look up the instruction manuals for each of these pieces of software online, and then just have at it e2e like a human would. It can even ping you over slack if it gets stuck on something.
I think once stuff like this becomes possible, custom AI integrations will become less necessary. I'm sure they'll continue to exist for special cases, but the other nice thing about a generic computer-use agent is that you can record the stream and see exactly what it's doing, so a huge increase in observability. It can even demo to human workers how to do things because it works via the same interfaces.
I cannot take seriously most of what I read over there. The comments are also often toxic, the whole business is... just weird.
What's funny as a personal anecdote, I've found more jobs through Twitter (pre-X) than through LinkedIn.
Seriously. And I've tried using LinkedIn for job hunt.
The way it's headed, it feels like AI is going to be writing 99% of posts at some point, and who wants to be a consumer of that? IDK, maybe lots of people, or at least maybe lots of people will continue to consume it because of how good AI will get at fine-tuning to your eyeballs, even though the people know they hate reading it.
I think Elon's takeover of twitter set something of a precedent too: if he could reduce headcount as much as he did and still have a functioning product, then why can't I?
BTW I also don't think it has much to do with that engineering tax deferral code change that people keep talking about. My cynical hunch is that that topic keeps getting seeded by the billionaires who have the most to gain by reversing it, and hey maybe they'll hire an extra engineer or two afterward just to be good sports, but it's not going to reverse any major employment trends.
Setup: a maze generator generates a square maze and puts the start and end on opposite corners. It doesn't show the full maze to the LLM, just has the LLM explore it one square at a time like a text adventure. It tells the LLM which directions of its current position has walls (relative direction: front, back, left, right). The LLM then chooses between move forward, turn left, turn right. That's pretty much it.
First attempt: Just maintain all the above in a chat, step by step. It'd get lost pretty quickly and start re-exploring already-explored area quite readily. Not very surprising, as we all know they can get lost in long chat threads. The chat model seemed to just go forward or turn right forever (which can work in some mazes), whereas the thinking model did seem to avoid backtracking until it got to T-junctions of a wrong way, where it always seemed to go back and forth forever.
Second attempt: After each step, tell the LLM to "externalize" everything it knew about the maze, and then feed that to a brand new LLM context. The idea was to avoid long chat context problems and see if the LLM could adequately represent its internal state and knowledge such that a "new" LLM could take over. This really didn't end up working any better. The biggest problem was that sometimes it would think that "turn left" would also change the position, and sometimes not. There were other issues too, so I didn't go much further with this approach.
Third attempt: Tell the LLM the premise of the game, and tell it to create a python state machine that stores all the state information it would need to represent its progress through the maze, and then to emit specific keywords when it needed to interact with it (and I added some code that served as a proxy). This also didn't work great. The state machine was close, but one thing it always forgot to do was relate index with direction. So if it's "in cell (5, 5) and facing up", it wouldn't know whether "forward" would be an increase or decrease in the x or y index.
I was also humored by its sycophancy here. I'd ask it
"Would adding a map to the state machine output be useful?"
"Yes, that is a great idea, let's do that!"
It'd do a great job of adding the map, but then I'd ask, "Does a map create more opportunity confusion?"
"Yes, that's an excellent insight, let's remove it!"
"No, really, you're the LLM, you're the one who's going to be using this app. I'm asking you, what do you think?"
"Whatever you want to do, just tell me"
Eventually, as the OP pointed out, these costs do add up pretty quickly. All I was after was "does externalizing the state help solve some of the long chat context problems", and the answer was "no" enough for me.
EDIT: Note that in all cases, they 100% emitted valid commands. And also I never noticed a case where "move forward" was chosen when there was a wall in front of them, nor "turn" when they were in the middle of a corridor.
This seems to happen a lot: Someone writes some highly exaggerated career advice that has good intent at the core but turns into overly weird suggestions by the end. They might be trying to be memorable or to make an impact by exaggerating the advice.
Then some people, often juniors, take it literally and start practicing it. They think they’re doing some secret that will make them the best employee. Their coworkers and managers are more confused than impressed and think it’s just a personality quirk.
As a manager I found it helpful to skim Reddit and other sites for semi-viral advice blogs like this. With enough juniors in a company there’s a chance one of them will suddenly start doing the thing written in a shared post like this. Knowing why they’re doing it is a good way to help defuse the behavior (assuming they don’t really benefit but rather do it because they perceive it will look good)
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(Tangentially, I'm so so so so angry that universities stopped offering remote classes after covid. I'd been wanting to take a bunch of classes for a long time, but it's just not feasible when you've got a full-time job in the 'burbs. I managed to get through measure theory and quantum mechanics while the window was open, and it was great. I planned to get through a few more in differential geometry and algebraic topology, but then the window closed. Feels like I'll pretty much have to wait until retirement at this point. Oh well, first-world problems.)
Edit: oh and actually, follow-up question: are these tools useful for _learning_ advanced mathematics? I looked up in Lean and its approach to topology is very non-standard, which makes me question whether I'd actually be learning math or whether I'd mainly be learning how to finagle things into Lean-friendly representations but missing the higher-level concepts.
We pre-allocate a bunch of static buffers and re-use them. But that leads to a ton of ownership issues, like the append footgun mentioned in the article. We've even had to re-implement portions of the standard library because they allocate. And I get that we have a non-standard use case, and most programmers don't need to be this anal about memory usage. But we do, and it would be really nice to not feel like we're fighting the language.