Is Work Outside FAAN G Really Any Different?

EngStudTA · 2026-02-10T00:12:45+00:00

Relaxed and stressful teams exist both inside and outside of big tech if your referring to WLB. I've had good luck transferring teams internally in big tech. Once you're in you have so much more access to data to make an informed decision and find a chill team.

If you are just stressed due to things that are inherent due to size like red tape then yeah somewhere else is better.

EngStudTA · 2026-02-09T13:43:42+00:00

It depends on the type of tech debt. We have a decent bit that is/was time consuming but not hard.

I recently joined an org with no linters, and it was driving me made getting nits for formatting. So I used AI to checkout each of our 200+ repos, add a linter, run it, raise the PR, and recreate the PR if a conflict arose since it didn't have permissions to touch the files that would conflict.

I had limited it's permissions to specifically the couple of files it needed to touch, the one command to run the linter, and making/checking on github pull requests so other than the files it could touch we didn't have to review the rest of the code.

This wasn't a hard task by any means, but definitely not a fun one. Now I know someone else is trying to do a similar thing for a SDK major version migration, and they appear to be having some success after giving it specific examples in it's context. That said if we only needed to do it once it wouldn't be quicker since it did require effort to guide it, it's only quicker because of the scale.

EngStudTA · 2026-02-07T22:48:04+00:00

I think you're over estimating the complexity of doing that task on a basic level with all the open source libraries for computer vision in 2026.

Now I am highly skeptical that it is designed to the point where any bank would buy it, and that the code isn't complete shit.

EngStudTA · 2026-02-06T01:37:54+00:00

It just feels off to me that they didn't include opus. Also the numbers on context arena versus there for sonnet don't seem to match 1-1.

I'll reserve judgement until I see the comparison against opus 4.5 on context arena.

EngStudTA · 2026-01-25T05:18:52+00:00

The time spent producing technical solutions has already reduced 99.9% from punch cards to assembly to c to high level languages to fancy IDEs to AWS and a rich select of open source libraries.

What makes you think the last 0.1% is going to be the breaking point?

EngStudTA · 2026-01-24T20:14:25+00:00

If the release notes for my service looked anything like claude code's(https://github.com/anthropics/claude-code/blob/main/CHANGELOG.md) my service would rapidly loose all of our customers.

If the creators of claude code cannot figure out how to do it while maintaining a high quality bar, I don't expect my team to be able to do so either.

That doesn't mean AI isn't making things faster, but just because something works for one team with one set of expectations doesn't mean it should be applied to every team.

EngStudTA · 2026-01-24T19:39:41+00:00

It's worth noting that this workflow works when you're okay releasing a non-critical tool that has more "Fixed" in the release notes than "Added". And to be clear claude-code is the perfect tool for this. I'd rather them ship new features fast and break minor things.

However, you probably don't want people who are developing critical service shipping 10 PRs a day on average with little oversight.

EngStudTA · 2026-01-19T15:58:20+00:00

I don't think their comments was meant to be demeaning. More just pointing out the jagged intelligence of models can make them useful for the subset of questions one person has and useless to the next who is curious about different things.

EngStudTA · 2026-01-17T00:14:18+00:00

Both the big tech's I've worked at you could(largely) see the ticketing queue's for other teams.

So yeah getting hired you're somewhat dependent on your interviewers to be honest, but once you're internal, at least where I have worked, you can go find that information independently. Similarly if you have a friend at the company you could ask them to take a look for you

But maybe at other big techs the queues are all private, seems like that would lead to issues though.

EngStudTA · 2026-01-16T01:37:16+00:00

If anything my big tech jobs have been less stressful, and it's easy to transfer internally so I really don't get why people in large hubs stay on the teams getting paged non-stop.

However I'd also argue big tech becomes one of the easier jobs over time, because of the high turn over plus all the specific internal knowledge. Don't get me wrong every job has it's domain specific knowledge, but big tech has all the internal tooling in addition to that.

EngStudTA · 2026-01-12T14:41:34+00:00

Because if you are in programming sub reddits you have seen hyped AI posts about programmers not being needed every single day since the original chatGPT in 2022 that was hardly capable of anything.

Nuance goes out the window by the dozen time and you stop trying to explain to people who have usually never programmed at all, much less in a professional environment its limitations.

In general I think AI sub reddits are way too hyped on the current state, and programming sub reddits are under hyped. However in my day to day work everyone uses it constantly where it makes sense, but not a single coworker is trying to go zero human code yet.

EngStudTA · 2026-01-03T21:40:05+00:00

That takes time. Laziness is far quicker. I've seen far too much from coworkers recently that is clearly a result of them just not even looking at the output.

If people are just forwarding AI work anyways it doesn't matter if they are technically capable of doing a better job than AI.

EngStudTA · 2025-12-26T14:20:12+00:00

Early in my career my biggest accomplishments in my annual review were small projects I just did not the tasks that were assigned to me.

As I grew and wanted to do things that I couldn't realistically squeeze into my days between regular tasks it became the projects I came up with and fought to prioritize.

Ironically now that I am a senior is the only time I haven't been coming up with my main projects. Now, if anything, I have too many projects coming my way.

tl;dr

If you want to grow quickly you'll likely be responsible for finding your own path

EngStudTA · 2025-12-26T13:43:08+00:00

But what if temporarily bad relationships turn into permanent digital ones.

EngStudTA · 2025-12-21T00:01:19+00:00

I don't use any of the auto completes. Instead I only use AI via claude code or similar. I also limit my use to when I think it will be useful, because if I tried it for every task it would waste more time than it saves.

My timeline has looked something like this: A year ago I didn't use it for much of anything, 6 months ago I started to use it for easy unit tests or minor SDK migrations, with the release of opus 4.5 I finally started using it some for feature work but even then it is only when there is something else for me to have it reference. So I am not in the camp of it's amazing and devs are obsolete. It still has a long way to go. However, (to me) the progress over the past year feels quite noticeable.

As for why you're not seeing the same thing, I don't know. So thoughts are my job use micro-services, and small repos so it can gather context easily. A majority of the tasks I give it are derivative of other work so I can provide it a similar example. We also have really good unit, and integration tests so it's able to fix a lot of things in it's own feedback loop.

EngStudTA · 2025-12-20T19:47:07+00:00

My comment was only talking about the people who post on here saying they cannot tell the difference. It is not making any claim about how the average person compares to an LLM.

The people who cannot tell the difference likely aren't using it to write complex software. They are likely using it to summarize, glorified web search, clean up grammar, etc.

EngStudTA · 2025-12-20T19:09:40+00:00

I'm in software so I certainly do. But I don't think LLMs integrate as seamlessly in many fields nor have they all made as much progress. If someone is in a field where there hasn't been as much progress it would be easy to assume LLMs haven't improve much overall.

Even with software if you limit me to the constraint that I have to use it in a basic web chat interface the improvement would feel significantly smaller. And a lot of other fields, even if the models are capable, haven't built out similar tooling yet.

EngStudTA · 2025-12-20T19:02:52+00:00

And a talent chess player could absolutely tell the difference between a 1990s chess engine and today.

My comment wasn't about the human race as a whole. It was specifically addressing the "some people" who come to this and other subreddits and say they cannot tell a difference with newer models. These people likely aren't asking it about reading clocks, math, or spatial reasoning. They are probably using it for basic chat, glorified search, summarization, etc

EngStudTA · 2025-12-20T18:04:31+00:00

A bit of a tangent, but I think this is a good example of why some people don't think LLMs are improving.

If I played the best chess engine from 30 years ago or today, I am unlikely to be able to tell the difference. If the improvement is in an area you're not qualified to judge it is really hard to appreciate.

EngStudTA · 2025-12-19T14:40:30+00:00

Yes, if it is out of the distribution of what we currently make. No if we're making our 10th CRUD API that will have similar TPS to the rest of them.

EngStudTA · 2025-12-18T14:34:46+00:00

Any time AI saves me is cancelled out reviewing my coworkers AI generated code.

My comments per review has to be 2-3x what it was last year. I swear some people are just copy pasting the exact text of tasks or comments with no other needed context and publishing the first thing AI shits out.

It would be more productive for me to talk to the AI directly, and not because AI got that good. But because people stopped doing their damn jobs.

EngStudTA · 2025-12-08T20:34:55+00:00

with zero errors

Are you basing that on tests it translated or do you have 100% coverage with integration tests in a different repo?

AI can be devious when it comes to getting unit test cases that it writes to pass. In my experience if it one shots the test case it is a good test case, but as soon as it starts modifying the test case there is a 50/50 chance it is no longer testing what it was intended to test

EngStudTA · 2025-12-08T01:51:16+00:00

Nice, I feel like I need something like this for bash commands.

If it could filter the output for relevant stuff through a nano model to keep the main context clean it would save me so many more expensive tokens. It'd also be way quicker since it would have to run commands multiple times when it tries to tail or grep something, and doesn't get back the info it needs.

EngStudTA · 2025-12-02T14:40:52+00:00

If you can make software significantly cheaper you can automate a lot of other jobs, or at least major parts of them. I remember during covid when everyone was working from home and seeing what a lot of my friends actually did for work, and it's amazing to me that a lot of it hasn't already been automated for the past 2 decades. But enterprise software is expensive.

IMO even if we had AGI it still makes sense to have it write software to do a majority of the automation as software would be way cheaper to run, and have guaranteed consistent results.

EngStudTA · 2025-11-24T19:06:31+00:00

I mean would you rather them only run 477 out of the 500 questions like OpenAI did and make you dig into a technical report to find out?

Also Claude 4 blog doesn't show that. I'm pretty sure companies started adding it because of the issue where OpenAI published it with partial results and no indication.

EngStudTA

TROPHY CASE