AI demands more engineering discipline. Not less • Hacker News Board

Re: AI demands more engineering discipline. Not less

#21

Post by romaniv » Wed, Jun 17, 2026, 3:48 PM UTC

>"It’s easy to forget, but for most of 2025, the idea that AI-generated code was slop and might always be slop was not only a reasonable position to hold, it was the default, mainstream position.

That question was answered decisively last November."

It's easy to forget that people said this exact thing about every model after GPT 3.5. This is a standard trick the industry uses to invalidate negative experience with LLMs. 'You are prompting it wrong' becomes 'you are using Gemini, but you should use Clade' which then becomes 'well, all of your criticism is now irrelevant, because everything is fixed in this new version'.

This "discussion" about capabilities is set up to be asymmetrical and basically non-falsifiable.

Re: AI demands more engineering discipline. Not less

#22

Post by molsongolden » Wed, Jun 17, 2026, 3:49 PM UTC

msteffen wrote: post #15

I liked this article, and I see a lot of other commenters didn't, so I'll give my take: When starting on a new codebase, how do you make yourself into a helpful contributor as quickly as possible? I go straight for the humans and their human docs. What problem was the system originally built to solve? What was the original design, and what were its biggest problems? Who is currently using it? If you know these, readi…

I wonder if the reception is so variable due to differing exposure to 1) infra as code and 2) engineering teams that don't produce any artifacts outside of their code.

> When starting on a new codebase, how do you make yourself into a helpful contributor as quickly as possible? I go straight for the humans and their human docs. What problem was the system originally built to solve? What was the original design, and what were its biggest problems? Who is currently using it? If you know these, reading the code is much easier because you can guess why things were done the way they are.

This is the way but plenty of engineering teams don't have any human docs at all. Decisions are made in one engineer's head or in a chat that isn't saved. The spec was just a few notes in a ticket that was deleted during cleanup or lost when the team changed trackers. There's no map of the codebase or features, no ADRs, minimal observability. All you have is the code. You read the code to try and figure out what is going on then ping an engineer who made a recent commit to a specific area to ask if they remember why something was done the way it was. Someone makes a change and it breaks something on the other side of the codebase that they thought was totally unrelated, etc.

Re: AI demands more engineering discipline. Not less

#23

Post by wbl » Wed, Jun 17, 2026, 3:50 PM UTC

romaniv wrote: post #21

>"It’s easy to forget, but for most of 2025, the idea that AI-generated code was slop and might always be slop was not only a reasonable position to hold, it was the default, mainstream position. That question was answered decisively last November." It's easy to forget that people said this exact thing about every model after GPT 3.5. This is a standard trick the industry uses to invalidate negative experience with L…

The old model couldn't do math, the new one solved a big open problem.

Re: AI demands more engineering discipline. Not less

#24

Post by ryandvm » Wed, Jun 17, 2026, 3:51 PM UTC

It is now significantly harder to figure out who understands the systems and is using AI effectively and who doesn't know shit and is just slinging LLM copypasta around. Before 2025, the underperformers/coasters were at least relatively identifiable by the paucity of their contributions. Now all of the sudden every single engineer is filing PRs, code reviews, technical design documents, and every other artifact under the sun with perfect formatting and at least superficial plausibility. This is mostly due to incredible pressure from the C-level for every engineer to be using as much AI as possible, but it's also just a game theory respopnse because it's in every engineer's best interest to be as prolific as possible.

We are absolutely drowning in documentation and code that seems legit and the only recourse is to lean on AI to help process the sheer quantity of it. I have a feeling that the fallout from this phase of the industry is going to be an exotic form of technical debt that is remarkable mostly in its enormity.

Re: AI demands more engineering discipline. Not less

#25

Post by sdicker » Wed, Jun 17, 2026, 3:53 PM UTC

Thanks, great to have the perspective of thoughtful engineers who have been in the trenches for a long time

Re: AI demands more engineering discipline. Not less

#26

Post by blensor » Wed, Jun 17, 2026, 3:53 PM UTC

ryandvm wrote: post #24

It is now significantly harder to figure out who understands the systems and is using AI effectively and who doesn't know shit and is just slinging LLM copypasta around. Before 2025, the underperformers/coasters were at least relatively identifiable by the paucity of their contributions. Now all of the sudden every single engineer is filing PRs, code reviews, technical design documents, and every other artifact under…

Maybe the solution is to look out for the most silent engineers. Those that output less despite having the ability to create near infinite output.

Re: AI demands more engineering discipline. Not less

#27

Post by trjordan » Wed, Jun 17, 2026, 3:55 PM UTC

> Those are not code problems. They are evaluation problems.

> Code becomes precious when it is the only place knowledge lives.

Reading AI code all day is _agonizing_. Just, a horrible way to live, and it melts people's brains at the moment you need them to be the most capable.

Manual programming has this really productive and gratifying feedback loop, where you read the code, write the code, and fix it until it compiles/runs/does what you want. AI code not only does half that for you, but it makes the "click" at the end uninspiring because you're never sure if it's cheated a bit to get to that moment.

Trying to operate with AI-generated code as the only durable artifact of programming is a dead end for the industry. Charity points to (and correct discards) architecture diagrams/specs as an interesting space to work in. My suspicion is that it's closer to the thing that's hand-written: prompts, markdown plans, and other nudges. Focus on the thing that you, as a human, produce, and that's the basis for both the core loop of "did the AI follow my instructions" and it's higher-leverage when you go to code review.

By the time you get to the PR, you've probably typed enough to Claude that you can regenerate the code, but the current industry default is to just throw away all those sessions and ship the code. That's backwards!

Re: AI demands more engineering discipline. Not less

#28

Post by hashmap » Wed, Jun 17, 2026, 3:55 PM UTC

romaniv wrote: post #21

>"It’s easy to forget, but for most of 2025, the idea that AI-generated code was slop and might always be slop was not only a reasonable position to hold, it was the default, mainstream position. That question was answered decisively last November." It's easy to forget that people said this exact thing about every model after GPT 3.5. This is a standard trick the industry uses to invalidate negative experience with L…

i mean i am very much still waiting for it to not be slop, but fable actually i think made a bit of headway in this direction, the code it writes what little of it i saw, makes me want to fall over dead slightly less than other models.

Re: AI demands more engineering discipline. Not less

#29

Post by lstodd » Wed, Jun 17, 2026, 3:56 PM UTC

AndrewKemendo wrote: post #6

Broadly concur with this and in fact it’s all of this is going to make doing real engineering easier in my opinion The author makes the wrong assumption though that the majority of people who are doing engineering want to do even more engineering. It’s my experience that most technology workers just want a high paycheck and have some kind of association with being in tech and doing cool things

> a high paycheck and have some kind of association with being in tech and doing cool things

yeh, I can see how that is now mistaken for a definition of 'engineer' or 'hacker'.

I am sorry you never knew what engineering truly means.

Re: AI demands more engineering discipline. Not less

#30

Post by mooreds » Wed, Jun 17, 2026, 3:57 PM UTC

trjordan wrote: post #27

> Those are not code problems. They are evaluation problems. > Code becomes precious when it is the only place knowledge lives. Reading AI code all day is _agonizing_. Just, a horrible way to live, and it melts people's brains at the moment you need them to be the most capable. Manual programming has this really productive and gratifying feedback loop, where you read the code, write the code, and fix it until it comp…

Are there any products out there that are capturing the prompts/sessions? I imagine you could do it in an adhoc way, asking Claude to write up a summary of the session as part of the commit message. But is there anything else that's more structured/higher level?