If you are in charge of that tooling, how do you ensure the correctness of the work? Or is it that at this point the responsibility goes one level higher now where implementation details are not important or relevant at all and all it matters is it behaves as described?
> I have zero knowledge of k8s, helm or configmaps.
Obviously this is not anything resembling engineering, or anything a respectful programmer would do. An elevator that is cut lose when you press 0 also works very well until you press 0. The claims of AI writing significant chunks of code come from these sort of people with little experience in programming or engineering in general, SPA vibe coders and what not. You should tremble at the thought of using any of the resulting systems in production, and certainly not try to replicate that workflow yourself. Which gives you a sense of how overblown these claims are.
> The claims of AI writing significant chunks of code come from these sort of people with little experience in programming or engineering in general, SPA vibe coders and what not.
I'm sorry man but I've been doing this for 25 years and I've worked and studied with some extremely bright and productive engineers. I vouch for the code that I write or that I delegate to an LLM, and believe it or not it doesn't take a magician to write a k8s spec file, just patience to write 10 levels of nested YAMLs to describe the most boring, normal and predictable code to tell your cluster what volume mounts and env variables to load.
> I have zero knowledge of k8s, helm or configmaps
…
> I vouch for the code that I write or that I delegate to an LLM, and believe it or not it doesn't take a magician to write a k8s spec file…
I have been writing code since 1995.
That has zero relevance to my skill at rolling out deployments in a technology I know nothing about.
One of the two things you’ve said is false:
Either a) you do know what you’re talking about, or b) you are not confident in the results.
It can’t be both.
It sounds to me like you’re subscribed heavily into a hype train; that’s fine, but your position, as described, leaves a lot to desired, if you’re trying to describe some wide trend.
Here my anecdote: major cloudflare outages.
Hard things are hard. AI doesn’t solve that. Scaffolding is easy; ai can solve that.
Scaffolding is a reliable thing to rely on with ai.
Doing it for K8s configuration, if you don’t know k8s is stupid. I know what I’m talking about when I say that. Having it help you if you do know what you’re doing is perfectly legit.
Claiming it did help when claiming you have, and I quote, “zero knowledge” (but you actually do) is hype. Leave it on LinkedIn dude. :(
> Either a) you do know what you’re talking about, or b) you are not confident in the results. It can’t be both.
You've been coding for a lifetime yet you don't seem to get that certainty in software is a spectrum? I have sufficient confidence in the output of LLMs to sign my name under the code it writes when putting up a PR for a specialist to read. That's good enough for 90% of the work that we do day-to-day. You think that's not hype-worthy?
> Doing it for K8s configuration, if you don’t know k8s is stupid. I know what I’m talking about when I say that. Having it help you if you do know what you’re doing is perfectly legit.
"Knowing" k8s is an oxymoron. K8s is a profoundly complicated piece of tech that can don insanely complicated things while also serving as a replacement for docker-compose or basic services that could have been hosted on ECR. The concepts behind basic k8s functionality are not difficult, but I saved myself two weeks of reading how to write helm spec files, a piece of knowledge I have no interest in learning because it doesn't add any appreciable value to the software I produce, and was instead able to focus on getting what I needed out of my cluster automation scripts.
This really isn't that complicated to understand. I don't care for being a k8s expert and I don't care for syntactical minutiae behind it. It isn't hype that I now I only need to understand the essential conceptual basics behind the software to get it working for what I need instead of doing a deep dive like I had to do years ago in when reading similar docs for similar IaC producs to get lesser functionality going.
Because after 25 years of coding and a dozen infrastructure description languages I know that you test your code and you get someone expert in the field to look at your PRs.
LLMs are _really_ good at writing infra code if you know how infra works, believe it or not. And the ultimate responsibility still lies in human beings for code ownership.
Betteridge's law proven correct once again. The answer to the headline is: no. Perhaps it will be true in the future, nobody knows.
I'm skeptical the extent to which people publishing articles like this use AI to build non-trivial software, and by non-trivial I mean _imperfect_ codebases that have existed for a few years, battle tested, with scars from hotfixes to deal with fires and compromises to handle weird edge cases/workarounds and especially a codebase where many developers have contributed to it over time.
Just this morning I was using Gemini 3 Pro working on some trivial feature, I asked it about how to go about solving an issue and it completely hallucinated a solution suggesting to use a non-existing function that was supposedly exposed by a library. This situation has been the norm in my experience for years now and, while this has improved over time, it's still very, very common occurrence. If it can't get these use cases down to an acceptable successful degree, I just don't see how much I can trust it to take the reins and do it all with an agentic approach.
And this is just a pure usability perspective. If we consider the economics aspect, none of the AI services are profitable, they are all heavily subsidized by investor cash. Is it sustainable long term? Today it seems as if there is an infinite amount of cash but my bet is that this will give in before the cost of building software drops by 90%.
>I asked it about how to go about solving an issue and it completely hallucinated a solution suggesting to use a non-existing function that was supposedly exposed by a library.
Yeah, that's a huge pain point in LLMs. Personally, I'm way less impacted by them because my codebase is only minimally dependent on library stuff (by surface area) so if something doesn't exist or whatever, I can just tell the LLM to also implement the thing it hallucinated :P
These hallucinations are usually a good sign of "this logically should exist but it doesn't exist yet" as opposed to pure bs.
I likely did something wrong but according to my hastily put calculations, Stripe has to improve favorable dispute result chance by 40% for this option to begin making sense. Or it could be lower but the value proposition of producing the evidence to dispute must cover for the gap.
That’s not accurate. At least in the majority of the city. You can buy a brand new 5 gallon garrafón for $65mxn ~ $3.25. You can fill one up from empty for ~$35mxn.
I read all entries about Rebecca last night after reading this one. It is such a visceral and devastating chronicle expressed in a beautiful way, it left me deeply moved.
I wonder how he felt after writing those words. I wonder if that beautiful ability to write what he feels so that many can feel a tiny glimpse of what he felt, helps to keep moving forward, even if a little bit.
Maybe a big assumption, but perhaps one of the founders is a fan of Malazan Book of the Fallen. Karsa Orlong is a character in the book series. A solid character, not sure if I would name a company after him though, so maybe the name is from somewhere else.
I'm from a Spanish speaking country. In the 90s one of the ubiquitous pencil brands had on their pencils the phrase "Sin plomo" or "No contiene plomo", can't remember which one, these phrases translate to "Without lead" and "Does not contain lead" respectively.
I never understood where it came from but it probably came from some English label translation perhaps? Where the distinction and labeling where the disambiguation of the word "Lead" made more sense and the label was simply translated at face value on a Spanish speaking market.
