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Ironically I feel like our QA team is busier than ever since most e2e user-ish tests require coordinating tools that is just beyond current LLM capabilities. We are pumping out features faster that require more QA to verify.

Would this be a problem if you can write E2E tests just like unit tests, like with Django+playwright?

https://github.com/mxschmitt/python-django-playwright/blob/m...


this is just an intermediate thing until the tooling and models catch up

Progress is not always linear, Until it actually does it we can't say anything. This assumption is only peddled by AI companies to get the investments and is not a scientific assumption.

Just a couple more weeks and a couple more trillion to Altman.

I wonder if that's only really true for "pre-LLM" engineers though. If all you know is prompting maybe there's not a higher quality with more focused that can really be achieved.

It might just all meld into a mediocre soup of features.

To be clear not against AI assisted coding, think it can work pretty great but thinking about the implications for future engineers.


>If all you know is prompting maybe there's not a higher quality with more focused that can really be achieved.

That's true of any particular individual but not for a company that can decide to hire someone who can do more than prompting.

>It might just all meld into a mediocre soup of features

I don't think the relative economics have changed. Mediocre makes sense for a lot of software categories because not everyone competes on software quality.

But in other areas software quality makes a difference it will continue to make a difference. It's not a question of tools.


Thank you for putting this so succinctly, this is what I'm observing as well.

Feels like this combination (usually) creates a race to the bottom instead of expansion of new ideas.

LLMs kind of feel somewhere in the middle


This analogy has always been bad any time someone has used it. Compilers directly transform via known algorithms.

Vibecoding is literally just random probabilistic mapping between unknown inputs and outputs on an unknown domain.

Feels like saying because I don't know how my engine works that my car could've just been vibe-engineered. People have put 1000s of hours into making certain tools work up to a give standard and spec reviewed by many many people.

"I don't know how something works" != "This wasn't thoughtfully designed"

Why do people compare these things.


There has been a very public announcement that OpenAI will start exploring ads in their models https://openai.com/index/our-approach-to-advertising-and-exp...

To be fair there seems to be a weird dissonance between the marketing (fire your workers because AI can do everything now) and the reality (actually you need to spend time and effort and expertise to setup a good environment for AI tools and monitor them).

So when people just Yolo the ladder they don't get the results they expect.

I'm personally in the middle, chat interface + scripts seems to be the best for my productivity. Agentic stuff feels like a rabbit hole to me.


Googler opinions are my own.

If agentic coding worked as well as people claimed on large codebases I would be seeing a massive shift at my Job... Im really not seeing it.

We have access to pretty much all the latest and greatest internally at no cost and it still seems the majority of code is still written and reviewed by people.

AI assisted coding has been a huge help to everyone but straight up agentic coding seems like it does not scale to these very large codebases. You need to keep it on the rails ALL THE TIME.


Yup, same experience here at a much smaller company. Despite management pushing AI coding really hard for at least 6 months and having unlimited access to every popular model and tool, most code still seems to be produced and reviewed by humans.

I still mostly write my own code and I’ve seen our claude code usage and me just asking it questions and generating occasional boilerplate and one-off scripts puts me in the top quartile of users. There are some people who are all in and have it write everything for them but it doesn’t seem like there’s any evidence they’re more productive.


as a second annectdote, at amazon last summer things swapped from nobody using llms to almost everyone using them in ~2months after a fantastic tech talk and a bunch of agent scripts being put together

said scripts are kinda available in kiro now, see https://github.com/ghuntley/amazon-kiro.kiro-agent-source-co... - specifically the specs, requirements, design, and exec tasks scripts

that plus serena mcp to replace all of gemini cli's agent tools actually gets it to work pretty well.

maybe google's choice of a super monorepo is worse for agentic dev than amazon's billions of tiny highly patterned packages?


I would think this is reasonable. My general understanding at Amazon is that things are expected to work via API boundaries (not quite the case at Google).

Just wanted to say I've felt very similarly recently. Honestly feels like we need a place to continue to discuss post-tech career paths for mid-career engineers.

I've been considering becoming an electrician but it is also quite a career shift.


Restarting a career seems so hard. Looking at engineering programs and having to spend thousands just doesn’t sit well. I suspect many of us will just keep doing “software” until they won’t pay us anymore.

That's currently my plan. I have kids, so I need to squeeze software dry.

That argument seems completely nullified by the fact that the president unilaterally changes his mind on tariffs every other day and setting up a manufacturing basis can take 10+ years.

Seems safer for many business to just continue to operate outside of the US and get a more consistent business relationship with every other country in the world.


I hate to say it but I completely agree, don't want to be a downer I'm sure OPs project is cool, but I legitimately could not understand what it was based on this landing page. No videos, demos or details.


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