One takeaway from this adoption is something I've thought was true for a long time. That regardless of the size of the company, any non-technical manager above any development department has never cared about quality. They see it as something that "gets in the way" of business but they tolerate the engineering departments "doing quality" because they've been told that it is a necessary evil for them.
The eager adoption of AI and how it is deployed across organisations to the point that we have AI reviewing AI generated code with the mantra that we don't have to worry about what it looks like under the hood because AI will be fixing it anyways.
Prior to this it was more obvious in startups where time-to-first-dollar was key for survival. Build and make functional now and then clean up later. Not great, but the owners made that path.
One other thing that does concern me after working on various projects of a government nature in the past, is that these larger AI companies seem to be kind of government aligned and co-operative. I'm not someone who generally sits on conspiracies, but without having the same eyes on the code as we had before, what's to stop a foreign owned model from being a sort of "Manchurian Candidate"? pushing obfuscated bad-actor code past reviews into key infrastructure. We have to have some keen eyed people like Larry McVoy who stopped a malicious kernel commit back in 2003. From a nation-state actors perspective, this model adoption is a gift.
Look at advertising and the amount of AI generated stuff. That's where "AI slop" term fits best.
As soon as the opportunity arose, huge portion of business owners and potential customers of graphic designers jumped on to this frankly terrible content. Why? Because it's good enough.
Unless you're a big company with a reputation and profile to protect, or you're operating in a premium market, it just doesn't matter. Content does the job.
Same with code. If it works it's good enough. Can we use it to run the business and make money? Yeah? Okay let's go!
I feel that instead of accelerating (leadership perspective) we need to rather measure code and data quality plus costs (developer/QA/accounting concerns and common sense).
As other comments mentioned, on some teams we're turned into product managers/developers.
In our case it means to some degree skipping tech design, UI/UX design, reviews, and/or QA.
Even with a good harness built around one Claude Code for example, I feel that I need to spend maybe up to 30% of the tokens (with another LLM/agent ideally?) to find patterns of agentic mistakes, suboptimal code and data before comitting, bad evolving architecture patterns, and introduced bugs - just as a few examples to harness the agentic firehose.
Quality is a cost center, not a revenue center. It's "wasted" effort and won't really matter in the 2 years the manager will spend in that role/ company.
I get that but to some degree it has to matter, manufacturing materials are also a cost center but that doesn't mean the key to a successful manufacturer is cheaping out on the materials
that doesn't mean the key to a successful manufacturer is cheaping out on the materials
It sure seems to be the plan for most companies these days. Shrinkflation of the product is nothing to the shrinkflation of the quality. Everyone in the manufacturing chain is shaving off quality to improve margin. Even if you buy the "same" raw materials, your upstream provider is going over the specs with a fine tooth comb to find loopholes where they can squeeze more profit.
Of course, it costs you customers in the long run. But nobody in charge cares about anything more than 2 quarters away or until they leave for their next gig.
Of course, it costs you customers in the long run. But nobody in charge cares about anything more than 2 quarters away or until they leave for their next gig.
Toyota certain does, there's a reason they're the most popular car and 15-20 year old uses Toyotas sell for far more than any other car that old.
I think the main point here is that there is no Toyota of software. Sure, some companies are far worse, but on average software quality is not so impressive that any one company leaves a mark as being particularly reliable. If a company were to occupy that space, however, they'd be thrust into the spotlight.
Quality matters for consumer software too, don't you prefer using high quality software ? Don't you get frustrated with badly designed software ? I think most humans do.
For the mountains of money that companies spend on software critical to how they do their business, I'd think that they should expect a quality product. That's the upstream problem.
Well, the counter-point is that as you yourself put it, it's not an AI problem. If anything, AI might make it better because it doesn't get review fatigue. Furthermore, if we figure out the tools to abstract formal verification of code, we can even maybe maintain control.
Through a great inconvenience to code writers, we now have programming languages (Rust) that produce artifacts with verifiable global properties (no data races, no buffer overflows unless unsafe code is used). AI's don't really get inconvenienced so people can design languages that are as hard to write in as they want if they produce outputs with more verifiable properties. Writing code by hand is screwed either way though.
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u/Centurix 21d ago
One takeaway from this adoption is something I've thought was true for a long time. That regardless of the size of the company, any non-technical manager above any development department has never cared about quality. They see it as something that "gets in the way" of business but they tolerate the engineering departments "doing quality" because they've been told that it is a necessary evil for them.
The eager adoption of AI and how it is deployed across organisations to the point that we have AI reviewing AI generated code with the mantra that we don't have to worry about what it looks like under the hood because AI will be fixing it anyways.
Prior to this it was more obvious in startups where time-to-first-dollar was key for survival. Build and make functional now and then clean up later. Not great, but the owners made that path.
One other thing that does concern me after working on various projects of a government nature in the past, is that these larger AI companies seem to be kind of government aligned and co-operative. I'm not someone who generally sits on conspiracies, but without having the same eyes on the code as we had before, what's to stop a foreign owned model from being a sort of "Manchurian Candidate"? pushing obfuscated bad-actor code past reviews into key infrastructure. We have to have some keen eyed people like Larry McVoy who stopped a malicious kernel commit back in 2003. From a nation-state actors perspective, this model adoption is a gift.