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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.

> 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.

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.

> 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.

> 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.

> 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

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.

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

I don't understand why humans abstract a business leader away from the realities of building software, while LLMs do not.

If the rhetoric is to be believed, the set of responsibilities falling to the role of "software engineer" is shrinking to zero, and all engineers are being forcibly "promoted" to the managerial class of shepherding around agents.

i would say theres more nuance than that (disclaimer: dont have a crystal ball)

software engineers who are comfortable doing business work - managing, working with different stakeholders, having product and design taste, being sociable, driving business outcomes are going to be more desired than ever

likewise, business leads who can be technical, can decompose vague ideas into product, leverage code to prototype and work with the previous person will also be extremely high value.

i would be concerned if i was an engineer with no business acumen or a business lead with no technical acumen (not counting CEOs obviously, but then again the barrier to starting your own business as a SWE has never been lower)

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.

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?

low code / no code, and it's been around in one form or fashion since the 1990's, at least.

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

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.

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?

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.

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.

> 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.

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.

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

> "...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.

> 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.

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.

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%.

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???.

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.

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.

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.

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.

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.

>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.