There is a sense in which it doesn’t matter at all; many of the limitations of agents in large codebases are just the context management challenges. So proving that you can cohere and progress at O(1m) is a useful scale observation. “Can I use agents in my 1m line codebase?” There is of course another sense in which the output quality is the only thing that matters. “Can I use agents to build a 1m line codebase that I want to maintain going forward.” I take this as being exclusively a tech demo of the former. Quality (feature velocity, bugs, scalability) is not demonstrated.

I stand corrected, but the LOC being advertised still make me doubt the efficacy of their process.

This is a lot tamer than what Claude Code's team claims tbf.

It is likely better because AI agents make access to domain knowledge easier. However, I would wager that the problem is people don’t remember the code well. The problems are going to be long-term as the pace of change increases. If you think about it, successful products rely on designing well-thought-out experiences, customer discovery (see all the Forward-Deployed Enginneer job listings at OpenAI) so the code velocity somewhat becomes irrelevant. If you’re solving the right problem and you’ve got a good team then competitive advantage comes from somewhere OUTSIDE of code velocity. The more important question I think is does faster code yield more value long-term? At the moment, it’s like yeah we do 3.5 pull requests per day. I’m thinking, great, good for you. You could also combine three pull requests into one and then you’re doing 1 per day. This is quantitative data that doesn’t really mean anything tangible.

I'm not an AI skeptic but I'm skeptical of the intent of this article. It makes great claims about agent-first engineering and tries to make a real case based on a real product, with real users, and a real team that's been growing — all without even saying what was built or showing it, just like every other AI hype article.

I wish these breathless blog posts would actually try to be more didactic. For example, actually doing a walkthrough of how to set up these allegedly super powered workflows and concrete demonstrations. I’m not an AI skeptic. Rather I’d don’t want to miss out on any actual super powers.

A lot to these blogposts are trying to catch on the next buzzword "harness". It's almost close to the productivity porn mindset that we witnessed 10-15 years ago where creating the complicated system is more exciting than using the system for daily tasks.

> Lines of code has always been a terrible metric. But all else being equal it is a measure. A terrible metric is _worse_ than no metric. A terrible metric can _only_ lead you in the wrong direction. "No metric" means saying we don't know, and that leads us to stop and reconsider. But we've taken "move fast and break things" as a mantra, and we'd rather run towards any direction than stay still. Using LoC as a metric for quality of LLMs will promote LLMs that write more code. It's better to say we have no way to compare different LLMs than it is to say "let's use the LLMs that produced more LoC because at least we can measure that". We, as an industry, should be focusing on developing better metrics for quality, not on improving LLMs based on known-bad metrics. We should be turning to the computer scientists, not to the venture capitalists. When a pundit talks about how many lines of code an LLM has created, we should lose all respect for them. It's as if someone talking about physics measured the phlogiston, or as if a doctor started measuring our skulls. We know these theories don't work, and anyone using them should be mocked.

> It's surprising to me that people who know about reward hacking choose a simple objective like lines of code generated as a signal for quality. The simple answer is that promoting locs as a relevant metric is also reward hacking. Is it easier to promote big loc counts as a key metric, or is it easier to prove agentic engineering against harder metrics? On a more general note, software practice marketers have been pushing in that direction for quite a while. "You need cloud", "Here's how to do agile at scale", "microservice everything", etc.

I don’t think the flex here is the amount of code alone. Their goal is to show that AI can improve productivity, the number of lines is just the proxy to that. This article is a marketing piece after all. Now someone can argue that lines of code are not a good proxy of engineering productivity, but I wouldn’t be surprised if the audience they target with this content is not the HN commenters of this thread.

Isn't this essentially normal AI usage and what everyone has been doing for 6 months?

I understand that the’ve written zero lines of code for this application, but would it kill them to write a few lines of the blog post by hand? Forcing readers to wade through an unceasing string of LLM clichés demonstrates the opposite of the point you’re trying to make—that the consumers of your work are worse off because you exercised no human judgment in creating it.

But this is almost what we have been doing for the last 3/5 months, isn’t?

I guess orders of magnitude ain’t what they used to be.

The world is now agent-first already?

Individual voices aren't strong enough to drown the marketing machine. Artists and writers are unionized, why they have a more powerful collective voice. Second, there are enough peole for which their jobs are very well paid and too cozy to dare to rock the boat. The economy and job market isn't so hot either at the moment for people to quickly be able to jump ship. Can you even be sure that you find a tech company that isn't jumping head first onto the AI hype train? Even politicians can't have enough of AI in their mouth.

I for one am not protesting because I know that this is bullshit marketing nonsense. Look at reliability metrics of OpenAI, they’re terrible. Everyone knew a long way ahead that it’s a scam, now they’re cranking up pricing and trying to rug pull. There will be a lot of developers who will come out very well once the stock tanks. That’s my two cents

> in an agent-first world casual gaslighting

> Over the past five months, our team has been running an experiment: building and shipping an internal beta of a software product with 0 lines of manually-written code. This is such a common thing among software engineers nowadays that I was very surprised that OpenAI would open with that line as if it were mind blowing. But then I saw it was published in February and OP is just reposting it to farm karma.