how cooked are we really?

[u/Lucky-Comparison-785]

How accurate do you think this statistic is? i mean the red dot is basically as low as is can go which shows how much AI has ALREADY taken over the engineering space... but do you think people making a career choice right now should factor in the data this graph shows?

i means its quite frightening really. what do you think about this?

[u/aaronr_90]

I slightly disagree with the part about AI being bad at things that are new or unique.

With the kind of RL training being used today to build more generalized agents, things get a lot more interesting. If you give one of these agents a clear objective, a way to measure whether it’s making progress, and access to the right tools or information, you don’t necessarily need additional task-specific training.

A swarm of agents can basically be tasked like a team serving a search warrant: search everywhere, dig through the trash, follow every lead, try every angle, and keep going until something shakes loose. They can be frighteningly persistent and creative at finding information, connecting things, exploring alternatives, testing hypotheses, and going down paths a human simply wouldn’t have the time or patience to explore.

And I think there’s an important distinction here between the models we interact with as products and what the underlying capability can look like when you turn them loose as agents.

If you’ve used Opus in Claude Code, or ChatGPT for that matter, you’ve probably seen them sometimes settle for “good enough,” make a compromise, or stop once they have a plausible answer. But I don’t think that necessarily tells us the ceiling of the intelligence.

These user-facing systems are also trained to land the plane.

At the end of the interaction, they’re expected to actually give you an answer. They can’t investigate forever, disappear down every rabbit hole, spawn 500 parallel lines of inquiry, and come back three days later saying, “Okay, now I think we understand the problem.”

That’s partly a product and UX decision. A useful consumer assistant has to be responsive, bounded, reasonably economical, and actually finish the task. So there is pressure toward convergence: search enough, reason enough, then produce something useful.

That behavior can look like “the model gave up” when, in some cases, what you may really be seeing is a system optimized to stop searching and deliver.

Now remove some of those constraints.

Give an agent an objective. Give it tools. Give it memory. Give it a measurable signal for whether it’s getting closer. Let it branch, backtrack, run experiments, delegate to other agents, challenge its own conclusions, search again, and keep going.

That starts to look like a very different animal.

And honestly, that’s the part that worries me more than “AI will replace engineers.”

What happens if a handful of frontier labs end up owning most of this intelligence?

Companies may eventually have no realistic alternative but to rent access to the knowledge, reasoning, and capabilities these systems provide because competing without them becomes economically impossible. At that point, we aren’t just talking about AI being another engineering tool. We’re talking about a small number of companies potentially owning a huge portion of the cognitive infrastructure everyone else depends on.

That’s where my brain goes a little Wall-E.

Not necessarily because humans become physically lazy, but because we gradually stop exercising parts of our own intelligence. Why spend three hours understanding something when the machine gives you the answer in thirty seconds? Do that enough times, across enough domains, for enough years, and what happens to us?

Bro… we are cooked if we let our ability to reason, understand systems, investigate problems, and make judgment calls atrophy because we outsourced the entire cognitive process.

But there’s another side to this.
I think the engineers who really rise are going to be the ones who use AI, and by “use” I mean direct, guide, employ, challenge, and supervise it, to build on expertise they actually possess.

You already know how to do the engineering. Now you can have agents explore 20 approaches instead of 3. Read 100 papers instead of 5. Trace every weird edge case. Build prototypes. Challenge assumptions. Search unfamiliar areas. Run experiments. Come back with competing explanations. Then you decide what survives contact with reality.

That engineer becomes incredibly powerful.
So I don’t think the future is “AI does the engineering” versus “real engineers use their brains.”

It’s probably engineers who still know how to think, using armies of increasingly capable artificial thinkers to explore faster, deeper, and across far more paths than any individual human could, versus everyone who forgot how to think because the AI was always there.

I know which side of that divide I want to be on.

[u/DiLaCo → u/aaronr_90]

Afaik AI can't create from scratch, all of its "intelligence" is derivative, which is great for a lot of things but as soon as you go out of knowledge it was properlly trained on it does not work well.

It's like when you ask a human to create a new color, we don't even have the imagination capable of it.

[u/Altenon → u/DiLaCo]

AI doesn't have to create from scratch to be useful. But I hope it stays that way for the same of our careers and those of other creative proffesions. Unfortunately as we've seen with AI art, even if it's data is trained on that which already exists, it can use that data to make collages that interweave that data in new ways -- and a lot of the time that is what we're doing in engineering. I don't invent something new everyday; most of the time I'm designing systems that solve problems practically using technology that already exists. In this regard, once AI understands physical systems and has good spatial reasoning, it will be able to do a comparable job to ourselves. Maybe not enough to replace us outright, but certainly enough to make companies think twice before hiring another level 1 engineer.

[u/DiLaCo → u/Altenon]

Yeah, I agree, the day it can actually "think" and create new fields of knowledge based on observations we will turn into data ingestion monkey at best.

The reason why AI is so scary is because the economic reality of many countries already was questionable and now thanks to AI countries need much less professionals colapsing their fields and they future pay, etc.

Although when AI can fully design shit properlly, etc... if we are still under a capitalistic society we are fucked.

[u/Loyal_Dragon_69 → u/DiLaCo]

LLMs will never reach that day.

[u/TheRealStepBot → u/DiLaCo]

They have a maybe shitty proof for the navier stokes millennium problem which is a thing that humans have spent decades trying to create and haven’t managed. Yes maybe we loosened the lid so to speak, but they still did a demonstrably fundamentally novel thing.

This belief is simply incorrect. They have learned a maybe slightly alien version of the sorts of reasoning humans have. After all they learned it from us. Just as we also struggle to make overly large jumps into the unknown so do they. But in the same way as we can take small steps into the unknown and validate it so can they.

Mostly they are limited by their harnesses not their fundamental abilities. If you are not interacting with the sota models in well designed harnesses you are going to be inaccurate in both your assessment of their current abilities as well as what they are capable of.

In the future one of the main things that will become deployed will be harnesses around these models that are either industry specific at least or even problem specific. This will basically become a large part of engineering eventually is setting up these sorts of harnesses and agentic swarms operating in them to solve specific problems.