u/CoroteDeMelancia

Uma galera respondeu nesse post (https://www.reddit.com/r/brdev/s/8xvhfpo7G3) o que eles fazem como DevOps. Queria entender melhor.

Sou SWE padrãozinho, pau pra toda obra, e isso inclui construir infra, mexer terraform, CircleCI e Kubernetes, configurar VPC e IAM, etc etc.

O que eu provavelmente não sei fazer que você que é DevOps sabe, ou que eu talvez sei mas você faz melhor?

Tô perguntando por curiosidade mesmo, não quero desafiar ninguém nem soar ofensivo. Tô 100% aberto a respostas totalmente honestas.

> If you are a senior, don’t tell juniors to do something that you aren’t certain that is right and that you believe that it is right because another senior told you to do that when you were a junior. Don’t be a parrot.

Excerpt from https://lucasoshiro.github.io/posts-en/2024-04-08-please\_dont\_squash/

I don't think I'm unreasonable to believe that engineering judgment should demand reasoning and evidence. And yet, across five companies, including big tech, I have repeatedly watched engineers choose instinct, convention, and authority. Many barely skim the documentation, much less read books or papers. Yet they confidently repeat “facts” they cannot explain with anything more substantial than:

- “This is how we do it.”

- “I believe I’m right.”

Or, God forbid:

- “Claude said it.”

More recently, I met self-described “AI engineers” who had not seriously studied prompt design or evaluation practices; they just winged it and hoped for the best.

The best engineer I ever worked with frequently said, “I don’t know.” He had a doctorate, more than ten years of experience as a professor, and years of company experience. He spoke less, but when he did, you could trust him.

He also had enough intellectual independence to disagree directly with our manager (sometimes abrasively) and enough humility to change his mind when the evidence demanded it.

I am not defending impostor syndrome; quite the opposite:

> Pride is not the opposite of shame, but its source. True humility is the only antidote to shame.

—Uncle Iroh

“I don’t know” is not the same as “I should have known.”

I am tired of status performance replacing epistemic responsibility and confidence being rewarded more than accuracy.

I want to ask those with more experience: am I being naive about what software engineering truly is in the market? Is it possible to become a senior engineer who values intellectual honesty, evidence, and willingness to say “I don’t know without undermining my career?

Edit: these responses are giving me a lot of hope. Thanks everyone!

Which of these companies would you choose, or rather, what would make you regret your choice?

• Company 1 pays enough for me to live comfortably. It has an office, but the job is full remote. Its culture has an excellent reputation for being healthy and humane, and it has a balanced workload, diverse projects, and tons of benefits. Engineers there are known to be strong in soft skills, business and problem-solving; the company rewards wide generalization over deep technical expertise. Lately, this company had been pushing hard in AI markets, but measures impact in actual profit generated rather than tokens burned; despite its positioning, it actually posts against indiscriminate AI use in their blog posts and is quite reasonable about why such projects fail.
• Company 2 pays 2.5x more. It is hybrid, ~40 min commute. Its culture is known for being harsh, competitive and adversarial. The workload is intense (up to 12-14h, daily). Engineers that thrive there are elite in traditional technical expertise for large scale reliable systems.

Both companies are major global players in their respective niches.

I am mostly concerned about long-term learning, especially given the latest market trends, and mental health is a plus, but... eeeh money?

edit: added specifics on pay diff

I recently joined a team tackling a difficult frontier problem and I am deeply concerned. My team is treating a very difficult, research-heavy engineering project as if it were a normal go horse project where we can just keep winging it until it works.

People are opening large PRs and rubber-stamping them. Some bugs show that changes appear not to have been run even once before being submitted.

The system does not work, at all, plain and simple, but we just keep adding more features. There is a growing gap between the stable branch and the dev branch; every day the dev branch seems to be moving further away from something we can actually ship.

We routinely face basic avoidable mistakes. Most issues we're facing are not "this is genuinely hard and solving this is the million-dollar question" problems, but "I didn't bother doing the bare minimum research before gut feeling some stuff I don't actually understand" kind of problems. Our bugfixes are like a heavy layer of duct tape in a building made of wet cardboard.

I tried raising my concerns politely. I thought "maybe I am missing something", "maybe there is delivery pressure I do not understand", "maybe this is a leadership call", "maybe this is normal in this kind of project and I am over-indexing on correctness too early".

But then I keep getting no concrete evidence. When I point to materials from experts, there is zero acknowledgement and the direction does not change.

Then I had a surreal conversation. After a mind-boggling conversation where I kept refuting vibes with actual reasoning and evidence, I asked essentially: are we optimizing for something that looks plausible rather than something that is correct? The answer was, no joke: yes, because what matters is a good story, not what is real.

WTF?

I am still trying to process what I just heard.

I know, tradeoffs, “perfect” is not an option, you ship an MVP, learn, and iterate, yadda yadda; I agree.

This is not it. We are building something we do not understand faster than we are can get evidence for what works. Where's the learning?

I do not have capital or authority to change this alone.

What is going on? More importantly, what is the right professional move for someone who values reality-based decision making in such a context?

I want to know: what is going on here?

I recently joined a new company and do not know exactly how to interpret what I'm seeing. Logic, evidence and credible sources are dismissed here; people base decisions on "I feel like" and "my gut feeling is that" without any clear explanation of what are we even trying to solve, let alone how does this make us get there. My team acts as if "more words = more smart" with no sound reasoning. Consensus is that our product has a coherent and achievable vision grounded by solid data and thorough market/academic research, and not just a foundation of hope, hype, copium and groupthink.

I have seen this before, just not at this level. Even when I worked at a startup with massive tech debt caused by poor design decisions, they had the intellectual honesty to recognize they would've done differently if it wasn't for "it is startup, more feature, no backlog".

People push 2000+ massive PRs not just without reading — without even *running* the code. Someone hallucinated a config envvar; it did *not* exist in the lib's documentation.

The system does not work, but my leader sells it to internal sponsors as if everything is fine, and every week we have design idea presentations/discussions for the next steps. Sponsors are understandably skeptical, but receive non-answer answers; "yes or no" questions are not responded with yes nor no. Then the team massively misinterprets their feedback to preserve the illusion.

People started citing sources in response to me asking hard questions to stress-test their ideas. Then, when I go ahead and read the material, it sometimes even directly contradicts them.

"I feel like" is a sentence that's been exhausting to me. If this came from a senior with vast experience in the topic, okay, but I'd still like to know the reasoning so I can learn it too. But here it's more of "I have never done anything like this before and read barely anything about this subject anywhere, but I feel like we should do X".

AI is being used as a substitute for thinking. I watched a *senior* DevOps telling the AI to write a shell script to remove all SSH permissions from the VPC's security group instead of spending 20 seconds to do this manually on his already opened AWS console. He did this because these permissions were unnecessary, but he was the one that wrote the script that put them there in the first place. My lead used AI to compress a 50+ paged academic whitepaper into a 1 page summary of why our project makes sense — but reading the actual whitepaper left me really confused on how he reached some of the conclusions.

Again, what is going on, and is there anything I can do about it?

Sorry for ranting, I'm not usually this salty.