[ej88]

I am personally of the opinion that ML will end up being 'normal technology', albeit incredibly transformative.

I think you can combine 'Incanters' and 'Process Engineers' into one - 'Users'. Jobs that encompass a role that requires accountability will be directing, providing context, and verifying the output of agents, almost like how millions of workers know basic computer skills and Microsoft Office.

In my opinion, how at-risk a job is in the LLM era comes down to:

1: How easy is it to construct RL loops to hillclimb on performance?

2: How easy is it to construct a LLM harness to perform the tasks?

3: How much of the job is a structured set of tasks vs. taking accountability? What's the consequence of a mistake? How much of it comes down to human relationships?

Hence why I've been quite bullish on software engineering (but not coding). You can easy set up 1) and 2) on contrived or sandboxed coding tasks but then 3) expands and dominates the rest of the role.

On Model Trainers -- I'm not so convinced that RLHF puts the professional experts out of work, for a few reasons. Firstly, nearly all human data companies produce data that is somewhat contrived, by definition of having people grade outputs on a contracting platform; plus there's a seemingly unlimited bound on how much data we can harvest in the world. Secondly, as I mentioned before, the bottleneck is both accountability and the ability for the model to find fresh context without error.

[aphyr]

> I think you can combine 'Incanters' and 'Process Engineers' into one - 'Users'

I wanted to talk about this more but couldn't quite figure out how to phrase it, so I cut a fair bit: with "incanters" I'm trying to point at a sort of ... intuitive, more informal practitioner knowledge / metis, and contrast it with a more statistically rigorous approach in "statistical/process engineers". I expect a lot of people will fuse the two, but I'm trying to stake out some tentpoles here. Users integrate a continuum of approaches, including individual intuition, folklore, formal and informal texts, scientific papers, and rigorously designed harnesses & in-house experiments. Like farming--there's deep, intuitive knowledge of local climate and landraces, but also big industrial practice, and also research plots, and those different approaches inform (and override) each other in complex ways.

[xienze]

> Hence why I've been quite bullish on software engineering (but not coding). You can easy set up 1) and 2) on contrived or sandboxed coding tasks but then 3) expands and dominates the rest of the role.

Why can't LLMs and agents progress further to do this software engineering job better than an actual software engineer? I've never seen anyone give a satisfactory answer to this. Especially the part about making mistakes. A lot of the defense of LLM shortcomings (i.e., generating crappy code) comes down to "well humans write bad code too." OK? Well, humans make mistakes too. Theoretically, an LLM software engineer will make far fewer than a human. So why should I prefer keeping you in the loop?

It's why I just can't understand the mindset of software engineers who are giddy about the direction things are going. There really is nothing special about your expertise that an LLM can't achieve, theoretically.

We're always so enamored by new and exciting technology that we fail to realize the people in charge are more than happy to completely bury us with it.

[simplyluke]

Who is better positioned to pilot the LLM than a domain expert?

"Software engineer" as a job title has included a lot of people who write near-zero-code, at least at the higher levels of the career ladder, for years prior to LLMs. People assuming the only, or even primary, function of the job is outputting code reveal a profound lack of understanding of the industry in my opinion. Beyond the first year or two it has been commonly accepted that the code is the easy part of the job.

[rootusrootus]

> has included a lot of people who write near-zero-code, at least at the higher levels of the career ladder

This is something that I would have thought HN readers were pretty familiar with. LLMs can make my code work faster or more prolific, but with 30yoe I spend a fairly significant chunk of my work time doing anything but code.

[simplyluke]

I'm occasionally reminded the HN's commenting base is much larger than my niche in the industry (VC backed startups + large public tech companies is my background). I had a similar reaction to people thinking Peter Bailis going from CTO at workday to "member of technical staff" at Anthropic was him trading a leadership position for closing jira tickets.

[Steppphennn]

> Why can't LLMs and agents progress further to do this software engineering job better than an actual software engineer?

Because a machine can never take accountability. If a software engineer throughout the entire year has been directing AI with prompts that created weaker systems then that person is on the chopping block, not the AI. Compared to another software engineer who directed prompts to expand the system and generate extra revenue streams.

[xienze]

> Because a machine can never take accountability.

A business leader can though.

> Compared to another software engineer who directed prompts to expand the system and generate extra revenue streams.

I think you're missing the point. Why can't an LLM advance sufficiently to be a REAL senior software engineer that a business person/product manager is prompting instead of YOU, a software engineer? Why are YOU specifically needed if an LLM can do a better job of it than you? I can't believe people are so naive to not see what the endgame is: getting rid of those primadonna software engineers that the C-suite and managers have nothing but contempt for.

[ej88]

> A business leader can though.

If a 'business leader' is prompting out software through their agents, ensuring it works, maintaining it, and taking accountability... they're also a software engineer

These titles are mostly semantics

[rdevilla]

By this definition, pre-LLM "business leaders" circa 2008 with not even an understanding of Excel were already "software engineers" this whole time - just prompting out software through their meatspace agents, instead of their silicon ones.

Dismissal of arguments as "just semantics" is high school level argumentation.

[ej88]

clearly not the same when they were abstracted from the realities of building software and.. directly taking accountability for it!

by semantics, i mean the definition and pool of tasks, responsibilities, and outcomes a job is comprised of is shifting so fast that the borders of what is a 'software engineer' and 'business person' are melding together. software engineers are business people in their own way

[nradov]

It's funny, that's why COBOL was originally developed in 1960: so that business people could write software themselves without needing software engineers. And it sort of worked, to an extent. History repeats itself.

[doubled112]

Between then and now, what ever happened to "no code development" or whatever they called it, where all of the world's APIs could be connected with lines in a diagram?

[nemomarx]

why would it be a manager? hire a cheap intern to be the scapegoat, if the job market is bad enough. no reason for liability to fall on the suits

[cucumber3732842]

That's how things work already in every workplace where there's any real danger. The companies construes its policies and paper trail in bad faith so that the employees are always operating contradictory to policy/training and then when something happens blame can be shifted on them.

[mattmanser]

You can say this about every single role.

Why can't VCs feed your pitch deck into an AI and get a business they own 100%?

If the only thing you're paying for is compute time...

Some.people are claiming it's about taste. Why can't an AI learn taste?

[nradov]

It's funny how we see some people who claim to have "taste" walking around in public wearing horrible Balenciaga shoes. Are they really just tasteless, or are they doing it ironically to troll the rest of us? I guess we'll never know. Maybe someday AI robots will achieve the same level.

[ej88]

It's not about whether they make mistakes (they do! although the exact definition of a mistake is nuanced), but whether they can take accountability if the software fails and millions are lost or people die. A large part of the premium paid on software engineers is to take accountability for their work. If a "business person" directs their agent to build some software and takes accountability -- congrats! They are also now a software engineer :)

The lines between a software engineer / business person / product / design and everything else will blur, because AI increases the individual person's leverage. I posit that there will be more 'software engineers' in this new world, but also more product people, more business people, more companies in general.

[guzfip]

> It's why I just can't understand the mindset of software engineers who are giddy about this brave new world. There really is nothing special about your expertise that an LLM can't achieve, theoretically.

They’re stupid or they’re already set up for success. The general ideas seems to be generalists are screwed, domain experts will be fine.

[icedchai]

Many experienced software engineers will move into infrastructure or architect roles, if they haven't already. Experienced engineers are in the best position to use LLMs because they can validate the output as actually being correct, not just looking like it works. Newer folks are going to be in a bad spot.

[monknomo]

The optimistic spin is, I think, software developer as a career dies, just like sysadmin. But just like dev-ops, a new to-be-named role (or set of roles) will arise

[ThrowawayR2]

> "...software developer as a career dies..."

Web front-end and backend developer as a career dies, probably desktop/mobile application development too. However, some of the more specialized software developer roles are likely to survive; none of the people on the Linux kernel team have anything to worry about and the same goes for the GCC folks.

[xienze]

> domain experts will be fine

But I don't see how this holds up to even the slightest amount of scrutiny. We're literally training LLMs to BE domain experts.

[bwestergard]

I think these arguments tend to reach impasse because one gravitates to one of two views:

1) My experiences with LLMs are so impressive that I consider their output to generally be better than what the typical developer would produce. People who can't see this have not gotten enough experience with the models I find so impressive, or are in denial about the devaluation of their skills.

2) My experiences with LLMs have been mundane. People who see them as transformative lack the expertise required to distinguish between mediocre and excellent code, leading them to deny there is a difference.

[georgemcbay]

I was at 2) until the end of last year, then LLM/agent/harnesses had a capability jump that didn't quite bring me to be a 1) but was a big enough jump in that direction that I don't see why I shouldn't believe we get there soonish.

So now I tend to think a lot of people are in heavy denial in thinking that LLMs are going to stop getting better before they personally end up under the steamroller, but I'm not sure what this faith is based on.

I also think people tend to treat the "will LLMs replace <job>" question in too much of a binary manner. LLMs don't have to replace every last person that does a specific job to be wildly disruptive, if they replace 90% of the people that do a particular job by making the last 10% much more productive that's still a cataclysmic amount of job displacement in economic terms.

Even if they replace just 10-30% that's still a huge amount of displacement, for reference the unemployment rate during the Great Depression was 25%.

[xienze]

Not sure that's what I was getting at. People in camp 2 don't think an LLM can take over the job of a real software engineer.

It's people in camp 1 that I wonder about. They're convinced that LLMs can accomplish anything and understand a codebase better than anyone (and that may be the case!). However, they're simultaneously convinced that they'll still be needed to do the prompting because ???reasons???.

[TheGRS]

One explanation is that some think we might be getting to the limits of what an LLM can reasonably do. There's a lot of functions of any job that are not easily translated to an LLM and are much more about interacting with people or critical thinking in a way LLMs can't do. I'm not sure if that's everyone's rationale but that's my personal view of the situation. Like the jobs will change but we likely won't be losing them to AI outright.

[paleotrope]

I was thinking today that I need to pivot to making and selling shovels, but then other issue is is anyone going to need shovels in the future.

[jandrewrogers]

An enormous amount of domain expertise is not legible to LLMs. Their dependence on obtaining knowledge through someone else's writing is a real limitation. A lot of human domain expertise is not acquired that way.

They still have a long way to go before they can master a domain from first principles, which constrains the mastery possible.

[vharuck]

People need to be careful about buying into the shorthand lingo with LLMs. They do not learn like we do. At the lowest level, they predict which tokens follow a body of tokens. This lets them emulate knowledge in a very useful way. This is similar to a time series model of user activity: the time series model does not keep tabs on users to see when they are active, it has not read studies about user behavior, it just reflects a mathematical relationship between points of data.

For an LLM and this "vague" domain expertise, even if none of the LLM's training material includes certain nuggets of wisdom, if the material includes enough cases of problems and the solutions offered by domain experts, we should expect the model to find a decent relationship between them. That the LLM has never ingested an explicit documentation of the reasoning is irrelevant, because it does not perform reasoning.

[jandrewrogers]

The domain expertise I'm referring to isn't vague, it literally doesn't exist as training data. There are no cases of problems and solutions to study that are relevant to the state-of-the-art. In some cases this is by intent and design (e.g. trade secrets, national security, etc) long before for LLMs arrived on the scene.

We even have some infamous "dark" domains in computer science where it is nearly impossible for a human to get to the frontier because the research that underpins much of the state-of-the-art hasn't existed as public literature for decades. If you want to learn it, you either have to know a domain expert willing to help you or reinvent it from first principles.

[bauerd]

>They still have a long way to go before they can master a domain from first principles, which constrains the mastery possible.

Mastery isn't necessary. Why are Waymos lacking drivers? Not because self-driving cars have mastered driving, but because self-driving works sufficiently well that the economics don't play out for the cab driver.

[netcan]

In some sense, technology is "not normal" regardless.

If we think of the digitization tech revolution... the changes it made to the economy are hard to describe well, even now.

In the early days, it was going to turn banks from billion dollar businesses to million dollar ones. Universities would be able to eliminate most of their admin. Accounting and finances would be trivialized. Etc.

Earlier tech revolution s were unpredictable too... But at lest retrospectively they made sense.

It's not that clear what the core activities of our economy even are. It's clear at micro level, but as you zoom out it gets blurry.

Why is accountability needed? It's clearly needed in its context... but it's hard to understand how it aggregates.

[bobthepanda]

Accountability is really a way to address liability. So long as people can sue and companies can pay out, or individuals can go to jail, there is always going to be a question of liability; and historically the courts have not looked kindly at those who throw their hands up in the air and say “I was just following orders from a human/entity”

[netcan]

Yes. I agree. There is a context and it makes sense within this context. But, the economy or industry is not there to produce accountability, liability, court-legibility. These are support structures, not end goals.

I said this in response to the example above, that humans are needed where accountability is a concern. This is pretty distant from the macro.

If we think of the 19th century economy... it was mostly about food, household products and suchlike. Now the economy is a lot harder to reason about and it's easy to miss the forrest for the trees... when talking about how technology will affect it.

Accountability is required to work with your payment processor, which works with visa and mastercard, that also have requirements, etc. Depending on where (of anywhere) paradigm shifts occur... we may or may not even need these functions.

That's why it's so hard to reason our way to predictions about upcoming Ai-mediated changes.

[pixl97]

>nd historically the courts have not looked

This is dependent on having a court system uncaptured by corruption. We're already seeing that large corporations in the "too big to fail" categories fall outside of government control. And in countries with bribing/lobbying legalized or ignored they have the funds to capture the courts.

[bobthepanda]

While this is true, this is somewhat mitigated by the fact that few sectors are truly monopolized and large corporations also sue each other.

[cucumber3732842]

A huge component of compulsory (either by statute or de-facto as a result of adjacent statute, like mandatory insurance + requirements thereof) professional licensure is that if you follow the rules set by (some entity deputized by) government the government will in return never leave you holding the bag. The government gains partial control and the people under it's control get partial protection.

"oh I'm sorry your hospital burned down mr plantiff but the electrician was following his professional rules so his liability is capped at <small number> you'll just have to eat this one"

I would wager that a solid half if not more of the economy exists under some sort of arrangement like that.

[bobthepanda]

Right, but usually that also involves verifying that the electrician actually followed the professional rules, and if not, they have liability

[cucumber3732842]

So the court checks if they were "just following orders"?

Sounds to me like following orders is in fact this magical thing that causes courts to direct liability away from the defendant.

[johngunderman]

I think the point is supposed to be that "following the practices and procedures that limit their liability" = "doing their due diligence to reduce risk in accordance with their credentialing body".

We generally don't hold people liable for acts of God or random chance failures. For example, malpractice suits generally need to prove that a doctor was intentionally negligent on their responsibility.

Everything in real life has quantifiable risk, and part of why we have governing bodies for many things is because we can improve our processes to reduce the risk.

It's not just following orders :) it's recognizing that the solution to risks isn't to punish the actor but to improve the system.

[mlsu]

Sort if like how one could be held liable for copyright infringement?

[g9yuayon]

> How much of the job is a structured set of tasks vs. taking accountability?

More accurately, how many jobs are probabilistically mechanical. That is, how many jobs are really the execution of a serious Bayesian decisions with a strong prior. LLMs are really great at displacing such jobs.

[dyauspitr]

Throw on a wizard hat and robe at some of the voice only vibe coders you see on YouTube and it’s essentially “incanters”. Hilarious.