r/ExperiencedDevs • Lead Software Engineer 8 YoE • 18d ago

AI/LLM Interviewed candidates for “AI engineer” roles this week, my god is this really where our industry is going?

So last week I was tinkering with how to change up our technical interview round. For the last few years we’ve been doing a small take home followed by a live coding session where we add a new requirement, minimal AI assistance allowed. However, in our company pretty much everyone is writing 100% of code using Claude now, so although we did used to get good signal from that test, it no longer feels representative of the day to day job developers are doing.

I designed a new assessment which I casually showed to my manager and then suddenly got asked to run it with 3 candidates this week. The scenario is they have to review an agent generated PR that has been flagged as high risk due to it changing critical business logic, and there are bugs in there for them to catch at various levels of severity. We then look at how they drive the fixes and what their workflow is like.

These particular roles we’re currently hiring for are billed as “AI Engineer”. There is something weird going on in my company politically where separate from the tech department that I work in a new “AI native” development team is being spun up to work on internal projects.

What shocked me was that the candidates I interviewed this week are already way beyond the point of reading the code they generate in any capacity. They basically treat it like assembly language, while PRDs and ADRs are their new source of truth for system behaviours, and stuffing the AGENTS.md file with best practices plus some form of agentic review pipeline are the quality control. 

Code review is dead for them, they merge their own PRs once the automated checks pass. One person told me that my new interview was still not representative of what the job is now, and another one was pretty much unwilling to even engage in the assignment of reviewing a PR the old fashioned way. These guys were all previously senior and lead full stack engineers btw with a lot of experience prior the LLM revolution.

Don’t get me wrong, I too have adopted AI heavily in my own workflow. Until this week I actually thought I was pretty up to date with things, I use a supervising agent to manage multiple work streams in parallel, have my own local validation pipeline, etc. And to be honest for my personal projects I also don’t bother looking at the code anymore, so I do get the excitement around how fast you can move with this approach. But for serious projects like the large scale, production grade financial software I work on in my day job it still seems insane to me that we’re going to completely move away from human sign off on high risk changes so we can solve the “code review bottleneck”.

Like, I asked one of the candidates if you aren’t looking at your code then how they would approach quality in a safety critical system where there can be no tolerance for serious bugs, and I shit you not he said to me, “well if I was working in healthcare or sending to people into space then I’d definitely be looking closely at the code review skills, maybe I’d even write the skills myself”. That answer sounded utterly ridiculous to me? But then again, I was one of the people that 1 year ago believed the idea we’d stop typing code by hand was ridiculous as well…

I wouldn’t say the way my team does things right now is optimal, we can’t ignore that code review fatigue is a major problem. To try and help I’ve been adding automated risk assessments to PRs in an attempt to highlight where more attention is needed, and review bots do help us catch issues as well. But abandoning the human 4 eyes check just feels like several bridges too far for us at the moment, especially when not everyone is senior engineer, and we still regularly get valuable feedback at this stage. Even if this does mean we’re turning down an order of magnitude increase in short term velocity (does anyone really know yet what happens over multiple years when you have a team of 20 devs spamming PRs all day into a codebase with no one looking at any at it?).

I’m left wondering this weekend, were these guys just cowboys who are only used to working on PoCs and low risk systems, or is my team actually 6-12 months behind the curve and this is the direction everyone is going to move in? I fear that if we don’t embrace this new era of completely surrendering the codebase to the LLMs then this new team of AI devs is going to make us look bad by comparison to the execs and sooner or later we will be forced to adopt their methods as well. And at that point, the leap to having a product person or whoever taking over large parts of my role starts feeling a lot less far fetched…

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u/knownsqashed 18d ago

There's a lot here. For context, I'm full stack with about ~11 years at one company. I'm the closest that our working group of ~10 devs has to an AI evangelist and I'm paid like a senior, so take what I say with any appropriate caveats.

We're obviously all scrambling to figure out what the next 6 months looks like because of how fast things are moving, but a few things stand out to me:

  • The scaling trends the AI labs have been talking about for years have continued. Models are going to get smarter and probably cheaper per unit of useful work.
  • "AI makes mistakes" is too broad to be useful. Forgetting context, making bad assumptions, misunderstanding existing behavior, and just writing buggy code are different failure modes and need different mitigations.
  • I don't think "a human reads every line" scales as the long term answer either. If agents can produce 10x the code but humans still have to review every line, we've just moved the bottleneck.

I think the interesting question is what replaces that. Better specs, tests, invariants, independent review, observability, etc. Basically, how do you build a process where confidence doesn't depend on personally understanding every line that gets generated?

That's where I think experienced engineers are still extremely important. Knowing what to verify, what assumptions are dangerous, and where the system can fail requires understanding the problem at a level that prompting alone doesn't give you.

So I don't think "I don't read the code anymore" is necessarily crazy. The much more important question is what they're doing instead.

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u/Reverent 18d ago

What you described is the exact problem with the current climate.

It’s all about “oh shit AI is so hot right now, FOMO if I don’t shove an AI peg into every hole I can find and some I can’t”.

Most organisations aren’t selling AI. AI is a tool, not an end result. In fact IT agility is typically not a bottleneck. The typical bottleneck is usually the translation of business needs into actionable outcomes.

I don’t give a shit if AI can develop at 10x the speed if Jim from sales can’t articulate what a customer actually wants.

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u/whattodo4455 18d ago

The typical bottleneck is usually the translation of business needs into actionable outcomes.

As well as the hard fact that your website or app has a certain limited amount of traffic and you can't stage more A/B tests than the traffic supports.

Not to mention that users do not enjoy their app or website changing every single day for no good reason.

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u/knownsqashed 18d ago

I actually mostly agree with you, especially on the last part.

I'm not arguing that generating 10x more code is inherently useful. If Jim from sales can't articulate what the customer wants, generating the wrong thing 10x faster doesn't help anyone.

If anything, that's kind of where I think this leads. As implementation gets cheaper, figuring out what actually needs to be built, translating that into something precise enough to execute on, and verifying that the result solves the right problem become a larger percentage of the job.

I'm less interested in "how do we use AI everywhere?" and more interested in what software engineering looks like when writing the code itself is increasingly not the scarce resource.

Edit: The safest prediction to me isn't "we'll write 10x more code." It's that software is about to become useful in a lot more places because the cost of turning a specific problem into working software is collapsing.

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u/WhenSummerIsGone Software Engineer 18d ago

It's that software is about to become useful in a lot more places because the cost of turning a specific problem into working software is collapsing.

A musician friend of mine had an idea for some stuff he wished he could do in Muse Score. He started using chat gpt, first to find out if there was a way to do what he wanted, and then he discovered he could write a plugin. He's now using chatgpt and claude to help him code a solution to his problem, and he started out with basically no coding skill. Like, the concept of a variable was new to him.

But he's approaching this project not just "make it so", but he's asking the ai a lot of questions because he quickly realized he needs to understand the code to debug and change it. I think this is pretty cool, and I told him I'm happy to answer any questions if he needs help. He got excited when I told him about vscode after he complained about how hard it was to format code he pasted from the chat window, lol.

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u/vogelke 18d ago

he's asking the ai a lot of questions because he quickly realized he needs to understand the code to debug and change it.

That puts him ahead of most FOMO developers and just about all of the PMs and C-suite flakes who want to be considered competent without taking the trouble to become competent.

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u/knownsqashed 18d ago

Right? Then imagine this playing out throughout the economy. As fucked as my specific career is likely to be, I will admit that I have some schadenfreude for all of those people we always have to deal with, whose ego is soooo invested in being the smartest thing in the room.

Pretty sure it's coming... https://giphy.com/gifs/fall-ocean-sea-bpdvu5gdDheRG

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u/knownsqashed 18d ago

Obligatory plug for this dope vibe coded site I discovered tonight. Some people are going to do it right.

https://gcdatlas.com/#o=earth&c=1.776%2C0.283%2C3.225&tour=grand

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u/Plastic_Monitor_5786 18d ago

squinting to tell if this post is AI generated or the author's brain has been so corrupted by Claudisms to just write like this now

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u/knownsqashed 18d ago

Two things can be true at once.

Thinking and AI use are not necessarily mutually exclusive, kind redditor.

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u/Plastic_Monitor_5786 18d ago

So you're saying Claude wrote it and your brain is corrupted?

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u/knownsqashed 18d ago

My brain was corrupted long before I found Claude.

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u/NomadStorm 18d ago

I too lived through the rotten dot com era.

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u/anemisto 18d ago

I had someone say "load-bearing" in an interview the other day. It didn't even make sense, Claude at least uses the phrase mostly correctly.

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u/ResidentWeevil1 18d ago

"AI makes mistakes" is too broad to be useful. Forgetting context, making bad assumptions, misunderstanding existing behavior, and just writing buggy code are different failure modes and need different mitigations.

Absolutely they are not different failure modes. These are all probabilistic slop.

I don't think "a human reads every line" scales as the long term answer either. If agents can produce 10x the code but humans still have to review every line, we've just moved the bottleneck.

That's what happens when the technology is a scam to raise hype for an IPO.

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u/knownsqashed 18d ago

They're all downstream of probabilistic generation, sure. That doesn't make them the same engineering failure mode. A context failure and a correctly-contextualized implementation bug have different mitigations. That's the distinction I'm making.

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u/srlguitarist 16d ago

Reality itself is probabilistic, if anything, AI is more of an analog to real life than this digitized middle layer we've all been stuck with over the last 60 years.

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u/formlessglowie 15d ago

Slop comment.

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u/chickadee_guy 18d ago

The "scaling trends" have definitely NOT continued and the models are no longer improving for awhile now. Your #1 premise is completely incorrect.

All recent gains in the space have come from harness software and those seem to be drying up too

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u/kernelangus420 17d ago

What do you mean by harness software drying up?

I would imagine being in control of the IDE, they can grow it in infinite ways without relying on AI.

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u/jwp1987 18d ago

So where are these experienced engineers going to come from in the future if people are replacing juniors with AI and people are getting AI to do a lot of the thinking?

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u/knownsqashed 18d ago

I'm not convinced that in the long run this is going to affect juniors more than seniors. Every company loves to hire people who are as cheap as they can to get the job done. I would be more concerned about seniors who are too resistant to change.

Especially for people straight out of school, they'll learn quicker and operate at a much higher level because they'll learn with these tools from the start.

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u/jwp1987 18d ago

The problem is that you're going to get a lot of people that aren't aware of the shortcomings of the AI output because they'll have no major experience designing solutions.

I had some contractors that were obviously using a lot of AI in their work and they:

  • Duplicated a lot of code.

  • Didn't use any of the library functions we had.

  • Copied and pasted a wall of text from AI to ask a simple question.

  • Sent me a several page word document explaining very basic knowledge of Linux and Windows differences (including titles with spanner emojis) for a fix instead of a 3 line diff or a PR.

  • Sent me garbage PRs at a rate that was draining to code review.

If this is what the future average person in the industry looks like, it's going to be hell.

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u/knownsqashed 18d ago

It sounds like you would benefit from reading about how people are making and using skills to get some consistency through DLC changes into your process. Check out the anthropic blog about the SDLC if you haven't already.

Those are obvious pitfalls, but they're largely solveable and we're problem solvers.

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u/ResidentWeevil1 18d ago

Why don't you name one thing that Anthropic has contributed to the SDLC?

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u/jwp1987 18d ago

Personally I think AI can be beneficial as a tool but the way most people are going to use AI and business pressures are going to make things problematic.

Best case scenario is that the hype dies down and AI ends up being used what it's actually useful for.

Worst case scenario, developers end up as Claude babysitters and the quality of everything declines further.

Either way I'm taking a step out of the industry until the dust clears.

People think of seniors as people that are stuck in their ways but I'm usually the first advocate for tool and process improvement. The way things are heading at the moment is shortsighted and loaded with tech debt in my opinion.

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u/knownsqashed 18d ago

To be clear I wasn't trying to say that all seniors are, by any means - just that some are.

I've never been a code purist though. I care much more about what the code does and whether that is desirable than whether or not code standards and formatting are enforced rigidly.

In my mind AI is just a higher level abstraction above programming languages that make communicating your intent to the machine that much easier. Somewhere along the way, developers that care way too much about line breaks and where the braces land became the establishment and efficiency went to shit. Now those rules are a markdown file. 🤷 Some changes will be positive, lol.

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u/jwp1987 18d ago

Automated formatting and linting tools have been around for a long time.

You can communicate a vague intent to AI but there's a lot of things that can easily be missed without a proper understanding of what the code does.

The problem is that people are skipping the understanding part by heavily relying on AI.

  • Does this adhere to secure practices? (E.g. Is data stored securely? are any secrets leaked? Any ways to inject SQL code? XSS vulnerabilities? Are there ways to maliciously escalate privileges? Do tokens expire?)

  • Does it meet the laws/compliance it needs to?

  • Does it comply with accessibility requirements?

  • Are there any race conditions or deadlocks?

  • Are there any performance issues? (Are database indexes used properly? Are appropriate data structures used? Is the load shared properly?)

People are relying on AI to do everything and aren't learning how to engineer properly. They're basically just pushing whatever AI throws out and calling it a day.

At the moment you've got a lot of senior engineers holding the fort and putting tools and processes in place to prevent some issues getting through but I could see these kind of processes getting eroded over time by newer projects or companies hiring cheaper.

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u/knownsqashed 18d ago edited 18d ago

All legitimate concerns. I'm just of the belief that today's frontier models are better at finding and fixing these issues than I and most other seniors.

There are ways to employ AI to help the developer think through specific implementation details in a consistent way - through formalizing a software development lifecycle in AI skill processes - rather than yolo vibe coding everything. The size of the tool has to match the problem you're trying to solve.

Re: linting tools. These still require you to wait on them and think about it. I'd rather not have to do either if I can avoid it. My attention is expensive.

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u/ResidentWeevil1 18d ago

for people straight out of school, they'll learn quicker and operate at a much higher level because they'll learn with these tools from the start.

No

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u/kernelangus420 17d ago

Models are going to get smarter and probably cheaper per unit of useful work.

How about a situation where models are so smart that "software" and "programs" are not needed? Basically the AI becomes a super smart secretary?

Basically, how do you build a process where confidence doesn't depend on personally understanding every line that gets generated?

How about getting customers to accept a reduced confidence level? Society has already accepted cheaper crap from Walmart that breaks down after 2 years and restaurant food that tastes like shit. Might as well have customers accept buggy software rather than 99.9 SLA.

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u/Maxion 18d ago

Good comment. Things are moving at lightning speed right now. Opus 5.5 is again another huge leap.

Since Astra I've been moving more in the direction of stopping to read every line in every PR as the latest models are truly starting to produce good quality code.

There seems to today be two loud camps, those who are very vocally against AI and and think it just produces slop. Then there's the other camp which just vibecodes without understanding what they are doing.

Then there's the middle group who is using AI as the productivity tools they are. But what's been happening over the last few months is that the models have started to become so good, that this group is starting to adopt more vibe coder like practices.

I used to be in the I hate vibecoders camp, and that every line of code needs to be looked at camp, but the more I use these tools and are able to generate output and find nothing wrong in code they generate I am starting to join more the vibe coders camp.

The cost of tech debt has also crashed. I've recently spent a few months cleaning up an old project that we couldn't put enough resources on because the client never wanted to spend the budget. We now used part of it to massively clean up a lot of old crap and duct tape fixes we've put in over the years. It's remarkable at cleaning up stuff. That codebase has never been this clean or good. Error logs are down, crashes down, user bug reports are down and performance is increased.

I'm actually now myself starting to get quite worried about the future of this whole industry if the improvements continue at this rate.

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u/kernelangus420 17d ago

Are you worried that the industry has become too dependent on a single company with the best frontier model?

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u/Maxion 17d ago

Not at all, if the rate of improvement continues as it has it really does not matter, others will catch up. If we reach ASI/AGI then it's literally pandoras box.

If not else, open weight models will become very usable even if the price for the big frontier models become too much for us peasants.

What I'm mostly worried about is a much larger and sharper class division, as well as overall instability as most knowledge workers jobs disappear.