There is no description of what the thing is, no indication of what value it provides its users. The closest it gets is "the product has been used by hundreds of users internally, including daily internal power users".

But the fact that the thing has a million lines of code is repeated twice in the first few hundred words.

[1] https://openai.com/index/harness-engineering/

[2] https://smackernews.com/item/48416264 HN

I do think that over the past few months, it feels like the hype around producing unmaintainable amounts of LoC has started dying down. More pragmatic and realistic takes are seemingly shared more openly, and are maybe even getting through to top leadership at some tech companies. Maybe not all is lost yet.

When a company says “AI made everyone more productive, so we need fewer people”, I want to see the evidence - and I don’t believe it exists today.

Because they're bullshitting and using AI as an excuse to correct from their covid era over-hiring while simultaneously making themselves look good to investors by showing they're embracing the hip new technologies to become a more streamlined and cost-efficient operation than ever.

When a company says “AI made everyone more productive, so we need fewer people”,

They are implicitly saying that as a company, they don't want to be more productive. They want the same productivity by paying fewer more productive people.

Why is there an imbalance between what an employer gets paid for a unit of production and what an employee gets paid for a unit of production?

The reasons we rejected LoC and other measurements have not changed (broadly: code output isn't important, quality output is). AI has all the same problems people do. But for whatever reason we are throwing what we've learnt away. It's kind of embarrassing.

> If you got a free headcount increase essentially overnight, why wouldn’t you use it to deliver more value to your customers, faster?

That shows that it's really just short-sighted profit-taking. Boss wants another lambo in the garage, and doesn't really plan to be around, when it's time to pay the piper.

The difference this time is pace: you could delay adopting “the cloud” for a couple of years and survive. With AI you might get a few months.

It is weird that the author seems to understand that the pro-AI claims made by AI companies about the product’s necessity are not falsifiable, but then backtracks with “woah woah woah but don’t think I’m anti-AI.”

How is the assertion above any more rigorous than the productivity claims the author is criticizing throughout the rest of the article? That you won’t “survive” if you don’t adopt AI within a few months?

It is not true when the AI CEO says it, and it is not true when the person calling BS on the AI CEO… for some reason also says it…

It's not the first article I've read recently that is an ad for AI after a short context pretending to criticize it, with nothing connecting them.

Measuring programming progress by lines of code is like measuring aircraft building progress by weight.

https://www.goodreads.com/quotes/536587-measuring-programmin...

Non-Functional requirements is a vestigial term from ‘function point analysis’ which is from the late 70s, and which also ended up being a proxy for LoC.

The entire industry is so focused on measuring now, and incentives are so skewed to short term that lagging indicators like maintainability are a non starter in many organizations that it will be challenging to fix this time.

The difference this time is pace: you could delay adopting “the cloud” for a couple of years and survive. With AI you might get a few months.

I don't think so. Take a good company A (with a good product and a good pace of good features) of today. Take the extreme case they decide not to use AI at all. Well, they will still be shipping good features at their current pace.

No amount of AI will make a bad company ship a better product than A's. If any, bad/mediocre companies will be pushing crap faster than they did before, but that's it.

AI can make good companies better, but cannot make bad companies good. Why does company A need to worry about shitty companies using AI? Sure, other good competitors could be using AI, but all in all, shipping "faster" is not the "mark" of good quality

A) a newly-receptive audience - engineers who have discovered that they very much enjoy and appreciate the tradeoff of proximity to the code for amplified velocity and impact, now that it's possible to achieve without being a manager of messy human teams.

B) an ecosystem in which it's grown nearly impossible to connect a functional description of something to how much bespoke construction and effort was involved, partially because of marketing and partially because of how much software already exists to be built on top of. It's impossible to tell from a few paragraphs of functional description whether something was built in a weekend or took a team 4 years to ship, so volume of code is the natural fallback for describing complexity.

Ugh. Just imagine the following on a normal curve:

Pre-AI: The goal is to make more money.

With-AI: The goal is to ship more code.

Post-AI: The goal is to make more money.

Can't wait to see how we get there...

When a company says “AI made everyone more productive, so we need fewer people”, I want to see the evidence - and I don’t believe it exists today. Show me that x% of your workforce is genuinely idle (or even just underutilised) because the work can now be done by fewer people. Even then: I’ve never seen a product/SaaS company that didn’t have an endless roadmap. If you got a free headcount increase essentially overnight, why wouldn’t you use it to deliver more value to your customers, faster? That should show up as MAU, conversion, revenue.

I see some people calling for calm instead of AI panic by invoking Jevons Paradox. But at least within these companies there's no good evidence of Jevons in action, is there? The roadmap is endless, but when employees are perceived to be idle they get fired instead of being assigned more (or more ambitious) tasks.

To be fair, one could claim Jevons applies to "the market" at large, but at least we can say the evidence from tech companies is not encouraging. So maybe it is, indeed, time to panic a bit?

Choosing the layoff instead tells me the productivity claim is doing PR work for a decision that was already made for other reasons (over-hiring, investor pressure, take your pick).

Yup, I think we all suspect this. Though it's probably a mix of the two factors.

But! Hold my beer… in February 2026 METR effectively walked it back : their follow-up estimates flipped to a speedup (with error bars wide enough to ride a Moto Guzzi, with panniers, through!), and they abandoned the study design entirely - because developers now refuse to work without AI, and can’t reliably self-report time on agentic work. Their latest position: AI probably speeds developers up in 2026, and we can no longer cleanly measure by how much.

This may be true, but they followed in May with this [0]:

Importantly, survey results are not necessarily grounded in reality. There are reasons to be skeptical of people’s responses to counterfactual questions such as about AI’s effect on productivity — for instance, our study in early 2025 found that people overestimated AI’s effect on their time spent on tasks by 40 percentage points on average.

[0] https://metr.org/blog/2026-05-11-ai-usage-survey/#productivi...

Since this is an area where failure can lead not to Instagram accounts getting hacked, but planes falling out of the sky and nuclear reactors spewing radioactive elements, it’s worth a close look. Some of the most visible companies in this sector include: QNX, Wind River, SYSGO, Lynx, Green Hills, Siemens Embedded, etc. None of them seem to have much if any adoption of LLMs for source code generation based on public statements.

Research in this area agrees with this view:

“In this paper, I have conducted a comparative analysis of the C++ code generated by popular LLMs including: OpenAI ChatGPT, Google Gemini, DeepSeek, Meta AI, and Microsoft Copilot for compliance with MISRA C++. The study revealed that none of the evaluated LLMs generated MISRA-compliant code despite clear prompts, with DeepSeek showing the fewest violations and Meta AI the most.”

https://arxiv.org/abs/2506.23535

Deciding what to build. Reviewing Code. And testing code. Are the new bottleneck.

So of course we don't see massive productivity gains. Because these parts of the SCLC were always bottlenecked but their capacity matched the throughout. We fired all the dedicated QAs years ago. Sr+ engineers that do all the code review are limited.

Teams have not re-organized to match the new code-input velocity.

Engineers don't want to do QA because it's "beneath them".. and most engineers don't like performing or are not Sr enough to do extensive or high quality code review.

"Augment surveyed 219 engineering leaders and asked them to define “AI-native engineering” . They got 219 different answers."

I mean, if you give 219 people a free text box and ask them to explain anything, you're extremely unlikely to get the exact same answer twice...

I think every engineer should be using AI daily.

Why?

That is why I have created one (Open Honest Slop Audit).

Funny how AI is continuing the same story of non/semi technical busy bodies with their dumb bullshit.

https://imgur.com/a/UW15xVE