3vidence

(current Googler)

For what it's worth we still use Android Studio as well internally, it is better and faster for doing specific UI stuff because of the tooling and visualization.

On the flip side the Google monorepo is a pretty cool thing and you get used to switching between projects and languages within the same commit chain pretty often. This is part of the reason the cloud IDE is so popular because it's one common editor across many languages compared to language specialized IDEs like Android Studio.

Regarding networking, it's not a big issue day to day. The infra team does a really great job building tools that do efficient caching and integrate well over the network.

It seems to forget about what I do and don't have access to (in terms of apps). I've had to remind it that I have Spotify and YT music more than once.

Other than that agreed going okay so far.

In general I don't disagree that it is a multiplier in the hands of good engineers but it also seems to be a multiplier in the hands of bad engineers (multiples of bad). The question is in larger organizations is having 5x the good commits and 5x the bad commits stable? The answer seems TBD from my perspective.

Honest question what were you doing that could be 100xd

That did the companys revenue / profit significantly change in some way?

Even at a large company if a person 100xd their productivity that would meaningfully move the needle.

This seems like a big HN / VC bubble thing thinking that average people are interested in software at all... they really aren't.

People want to open Netflix / YT / TikTok, open instagram, scroll reddit, take pictures, order stuff online, etc. Then professionals in fields want to read / write emails, open drawings, CADs, do tax returns, etc.

If anything overall interest in software seems to be going down for the average person compared to 2010s. I feel like most of the above normal people are going to stop using in favor of LLMs. LLMs certainly do compete with Googling for regular people though and writing emails.

My manager at work still does this in work chats and it drives me a bit crazy. If I want to k own what an LLMs take on the subject is I can just go ask it.

The chat is for people to discuss people stuff.

I can say at Google we usually just had engineering tip posters in the washrooms they were usually very insightful and just written by other engineers at the company.

Stuff like how to reduce nesting logic, how to restructure APIs for better testing, etc.

People usually like them. I can't say I've seen what the parent post described so I imagine it's "the other" FAANG mentioned here.

The thesis of the article is that software other people have built is bad (frameworks) but software my LLM agent is good (for undisclosed reasons).

I think it just adds to the noise of our industry that reusable patterns and standards don't matter

Yeah honestly I've been racking my brain about the same question (where can I move on to).

HN has been my home for learning about all sorts of things for 10+ years but blockchain + AI has just killed all interesting discussion that can be had.

It's hard to define a community around "not being obsessed" with something. Maybe instead it's worth thinking about what the goal of such a community / forum is. Might be easier to find / define.

If you come up with something I'm happy to check it out.

Every day I feel closer to leaving this industry when I see articles like this.

Is software even a real industry with patterns, safety, design, performance, review, etc.

Or are we just a hype generating machine that's happy to ship the most broken stuff possible the fastest.

Why do we have to constantly relearn the same lessons.

In my experience the lack of joy or difficulty with tests is almost always that the test environment is usually different enough from the real environment that you end up needing to kind of stretch your code to fit into the test env instead of actually testing what you are interested in.

This doesn't apply to very simple functions but tests on simple functions are the least interesting/ valuable.

Most likely the headline was written by an LLM so the irony was lost on it.

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.

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.

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.

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).

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.

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.

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.

This is a really great idea going to try this out. I similarly just cannot mentally stand reviewing vibe coding PRs all day, but this sounds genuinely useful.

This idea sounds somewhat flawed to me based on the large amount of evidence that LLMs need huge amounts of data to properly converge during their training.

There is just not enough available material from previous decades to trust that the LLM will learn to relatively the same degree.

Think about it this way, a human in the early 1900s and today are pretty much the same but just in different environments with different information.

An LLM trained on 1/1000 the amount of data is just at a fundamentally different stage of convergence.

This isn't exactly an answer to your question but I've experienced some efficiency gains in using AI agents for pre-reviewing my PRs and getting it to create tests.

You still get to maintain the core code and maintain understandability but it helps with the tasks the take time that aren't super interesting.

There is a phrase I've heard a number of times in my career that I find relevant here.

"There is nothing more permanent than a temporary demo"

Googler, opinion is my own.

Working on our mega huge code basis with lots of custom tooling and bleeding edge stuff hasn't been the best for for AI generated code compared to most companies.

I do think AI as a rubber ducky / research assistant type has been overall helpful as a SWE.

This is literally it.

High upside (if the AI manages to complete the task it is a time save), relatively low downside (not getting stuck in these AI feedback loops that are ultimately a time waste).

Seems odd to me that people spend so much time promoting some of the least productive aspects of AI tooling.

I've definitely seen a number of files where the implementation is maybe like 500 LOC and the test file is 10000+ LOC.

I agree rigidly defining exactly what the code does through tests is harder than people think.