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Comment by fwlr | Hacker News Reader

    GPT-Synopsys brings together OpenAI frontier models with Synopsys' EDA technology and domain expertise, enabling the specialized model [to] directly operate Synopsys' tools. Engineers will delegate design objectives … with agents running tools, interpreting results, implementing changes, and iterating toward verified outcomes for engineer review.

“Agents will do all the engineering work. Engineers will delegate and review.” Lol, no, what the engineers are gonna do is get laid off.

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The problem with "engineers will review" is: Critical review requires expertise. Expertise requires experience. Experience comes from building. Builders build because they like to build. So when builders are asked to do nothing but review, they will eventually tire of their jobs and leave, sometimes not just the job, but the industry entirely. The lower the quality of the agents' output, the faster this will happen.

> So when builders are asked to do nothing but review, they will eventually tire of their jobs and leave, sometimes not just the job, but the industry entirely.

I do agree that a lot of engineers who want to do everything the old manual way are about to get really frustrated.

I don't think this is as universal as you say. There are a lot of engineers who are excited and happy to use these tools. Leave the bubbles of Hacker News, Lobsters, and similar sites and a lot of people are embracing these tools.

You also skipped the step where someone needs to direct the design. In the pre-LLM era it was commonly accepted that engineers who advanced to very senior roles would become less connected to the implementation details and more connected to steering, reviewing, and directing. Only a few years ago Hacker News was full of anecdotes about staff engineers who barely wrote code any more. Those people will have no problem switching to a new world where LLMs are handling implementation details.

The point stands, though. Senior engineers can detach themselves from implementation details because more junior engineers still do the hard parts. In the AI case, agents are the "engineers". Eventually all competency will be within AI domain and none within human one.

Why people are so eager to surrender their birthright to the machines for the mess of pottage?

If people want to build stuff they can, they just may not be paid for it. But if we don't need to pay anyone to do anything then it also doesn't matter that you aren't being paid, as you'd have all you need, and you can spend your time tinkering away on low tech/cottagecore enterprises like designing an ASIC or making bread.

I am very skeptical about benevolence of our future overlords, humans or AI, towards people they don't need anymore.

In cartoons you'd have this concept where someone is sawing away with great energy on a branch while sitting on the dead side of the saw. This is that concept, but on a much larger scale.

Why does this sound very much like the argument toward full self-driving? If drivers need to be watchful of mostly autonomous ones, they get bored and lose attention or sometimes take nap in front of the steering wheel. Waymo came out of an extension of this argument..

You can do this for any company now. Any company not announcing this to boost their stock is foolish, ride the train with the crowd.

GPT-Company name brings together frontier AI models with Company's XYZ technology and domain expertise, enabling the specialized model [to] directly operate Company's tools. Engineers will delegate design objectives … with agents running tools, interpreting results, implementing changes, and iterating toward verified outcomes for engineer review.

We're not Hershey's the Chocolate company based in Hershey PA...

We're WWW.hersheys.COM the fully Web integrated Global Information cocoa delivery company.

Chocolate lovers will delegate chocolate eating objectives, GPT-Hersheys will automatically eat the chocolate.

Don't hate the player hate the game

Eventually... But it is materially relevant if that happens in 2 years or 10.

While I think SWEs(yeah, not HW/chip but that's not my field) are cooked in 5 years, I think we'll be quite busy in the meantime fixing all the bugs that AI finds.

> we'll be quite busy in the meantime fixing all the bugs that AI finds.

Maybe that's the job of software engineering moving forward.

Client: Hey, we have got these 125 microservices created by our agents and for the last 25 days they got stuck and can't add any new feature without breaking things, can you take this?

Eng: Sure, lets sign a 24 month contract, my rate is 250$/hr

Client: Sounds good

Do you think that even today's frontier models are unable to handle this task?

Today’s frontier models create the problem.

What problem? They keep finding security bugs that humans couldn't for decades.

That isn't actually relevant. They create problems, but when confronted with them and asked to fix them, my experience is that they can fix them very effectively. I haven't had an AI session get "stuck" on me, not being able to solve a problem in over a year.

The challenge as I see it is in shifting checks further left, but actual mitigation is just not really an issue any more.

Actually, I do this too, but I find the first round and the fix round are still way more complex than an original right round. If that makes sense.

So ask them to fix the problems in a targeted way.

Today's frontier models can't even handle 100% of the SWE benchmarks that have been around for longer than they've been training the models. Companies that are benchmaxxing their models against the benchmarks haven't even been able to get them to 100%.

I've been using Astra and Opus 5.5 all week and I still have to intervene and tell them to do something different all the time.

I think the people whose SWE jobs consisted of simple features, bug fixes, or tweaking .toml until the server works are on their way out.

Someone needs to steer the LLMs around for now, though. There is a very long tail of non-trivial work and expertise that can't yet be replaced by a CEO telling the LLM to make the product work. There are many CEOs trying to do that right now and, outside of very simple CRUD apps, it doesn't work yet.

> Today's frontier models can't even handle 100% of the SWE benchmarks that have been around for longer than they've been training the models. Companies that are benchmaxxing their models against the benchmarks haven't even been able to get them to 100%.

Is average developer 100% the benchmarks ?

Given how flawed the benchmarks are (see for example https://epoch.ai/benchmarks/deepswe/review), not even the mythical 10x developer is gonna get 100% on these benchmarks.

Well, I let him do some stuff in kube. The architecture is a complete mess.

Eng: So I prompted Claude to turn the 125 microservices into a single Erlang program. Better not tell the client.

Chips design is expensive. Partly because of engineering costs, partly because of manufacturing costs.

If costs go down enough,because of LLM's and possible manufacturing innovations, more chips will be designed, so maybe this will partially offset job loses.

The wish granting machine won't need the engineers for that. You'll just end up paying for the devices.

> more chips will be designed, so maybe this will partially offset job loses.

This is HN mentality. But it is not how it always works. The first thought isn't we can make more money tomorrow by building more faster. It is we can make more money today by laying off all the people that we don't need now. Short-termism is the rule.

I think that’s more the norm in stability, where the economy when not a lot is happening/changing/improving, and so the economy is focused on efficiency as a method of competition. We are squarely not in efficiency mode right now, we’re in explore as fast as possible mode, as a lot of old underlying assumptions have changed, and there’s a huge amount of work to be done in reworking everything for the new assumptions. That means lots of opportunities, lots of money flying around, and bean counters getting outcompeted by people who’re focused on doing new things. Being too conservative does not serve you well in this regime. My two cents, anyway, I don’t think overall massive job losses are on the menu anytime soon, but massive job displacement/swapping, very likely.

For each Design Engineer, there are 3 Design Validation Engineers because going to fabrication is very expensive and it is unlike software where you can just do a git push and wait for the CI/CD pipeline to deploy code within minutes at no additional costs.

So let's see.

When TSMC capacity is already sold out for a couple of years, and demand just for plain RAM is through the roof, where will these "more chips" be actually fabbed?

My observation is even if AI takes 80-90% of my job, the remaining 10% is still going to be more relevant to keeping the company going than other people's 100%.

I wish this was hubris, but no. I would genuninely be happy to not have to do other people's work for them on top of mine.

You wouldn't be the first person to believe himself indispensable who learns otherwise.

I’m glad my colleagues and I are all mediocre , because if the alternative is having someone with your arrogance around then no thanks.

I wish I was arrogant. Or alternatively I wish I was surrounded by arrogant coworkers who at least took some pride in the quality and quantity of their work.

Not saying everyone is like this, but plenty enough are.

But hey, at least folks unburdened by the pressure to ship anything have plenty of time to play office politics.

> the remaining 10% is still going to be more relevant to keeping the company going than other people's 100%.

Right. Because skills don't atrophy at all.

you are in luck cause you’ll be obsolete and unemployed so you won’t have to worry about anyone’s work on top of yours :)

Exactly. How 'bout “economize” chip design by reducing / eliminating human chip designers ... Go figure.

Aren't hardware design issues incredibly costly? I highly doubt they're going to "dark software factory" it or they'll be eaten alive by failed launches, product recalls, lawsuits.

https://en.wikipedia.org/wiki/Pentium_F00F_bug

I worry that even the electronics industry is falling into the fear of being agentic or being left in the dust. AI slop is already weird for programs.. I wouldn't want that in hardware.

Already happening:

https://ashutoshveriprajna.substack.com/p/ai-code-chip-bug-f...

Can't vouch for the source though.

Most of them anyway, and the cutoff bar will continue to rise.

And then the shit won't work, and then they will hire them again lmao

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