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> have the LLM focus and summarize a slice of the system when they need to know about it or ask for it. But.... That's not knowledge? That's just search a la google? And thus seems to be subject to the same problems where the quality of your search dictates the quality of your knowledge that you surface at any given time?

This is the crux. Take pause, because hidden here is a sea-change in our fundamental trust model of software...

There is no longer anyone to turn to if this system breaks by, eg, having a critical bug that no one can figure out. No causal model in anyone's head that can be appealed to, to slowly and methodically debug. By design, the system is too large for that, and everything hinges on Claude itself being able to find and understand the right slice of the system in any situation. As long as that very new invariant holds, everything will be all right. If it fails catastrophically, there is no recovery. You are the owner of a recovered alien spacecraft with tech you have no hope of understanding.

The new trust model is: We trust Claude to always understand the system enough to debug anything or make any reasonable change we could want. The risk might be worth the reward. But it's worth explicitly laying out the deal we're making.

Tbf, it's worth pointing that many large legacy systems already work like that (sort of), with "Claude" replaced by "whoever happens to be maintaining it this year".

> wherein the machines are treating them like pets

I know some people will groan hearing the phrase again, but: "Reverse centaur." A centaur is a synergistic combination of two things, but now those things are in the wrong position: The human is the computer's tool.

Naturally, how "wrong" it is tends to depend on whether you ask the people who do all the work or the people who own all the computer-capital.

I think it's just a different focus on what matters.

There's clearly enormous (human) work that goes in to building and tuning their models.

The software they develop around their model is, relatively, trivial. It's not clear that enormous amounts of (human) energy need to go in to that code.

It seems largely a function of applying human energy towards the things that are marginally most important to generating you money and putting you in front of competitors.

> I really don't get the tendency here from Anthropic to describe what's most likely churn? 1000 "PRs" a day on a TUI to wrap a while loop?

From the article, the 30,000 changes a month are in the monorepo, and Claude Code is in a separate repo. So it’s not the TUI that has 1,000 PRs a day.

I could easily see 1,000 PRs a day on the backend. Big tech was doing more than that pre-AI.

My favourite quote at the moment: "May not man himself become a sort of parasite upon the machines? An affectionate machine-tickling aphid?" Samuel Butler, Erewhon, 1872

100%, although if people are getting 90% of their interaction from a robot, one may start to pick up some vocal tics and colloquialisms from machine world. a kind of robo-pidgin.

this definitely seemed like something claude generated, i know because i frequently do all my research in chat and then ask it to generate a doc based on what we talked about and when i read what it generates the verbosity, the style it writes in makes me delete the whole thing. I would never subject readers to that.

Pangram reports 80% of the text is AI-generated: https://www.pangram.com/history/72309aad-6e3f-4002-bdc5-c062...

I'm thinking about high volume mass manufacturing as an example here. I like those "How it is made" type YouTube videos. You see a production line that has some kind of QA process where cameras + automated systems do spot checks at high speeds and these crazy actuators are punching out bad examples. These processes often also involve spot checks where some statistical sample is selected and viewed carefully.

I don't think we've gotten to that level of reliable review with code, but I don't see any reason we can't continue moving in that direction.

It's conducting/steering/oversight/supervision, not reviewing.

I dont believe it, its FOMO marketing to me.

Anthropic has been profitable for the past two quarters.

Yes it used to be said, the code is not the asset, the people who know what the code does and how to change it are the asset.

Now we’re just going to outsource our capacity to design and review because it’s faster that way, as if the thing that was wrong with the software industry was that releases weren’t being pushed out often enough.

i am tired of listening about other ppls agent setups. Everyone thinks they've discovered something cool and unique but They are all the same.

Its like telling other ppl about your dreams. Not interesting.

My advice is to start a totally vibe coded side project. You will never gain confidence until you experiment, find the failure cases, learn to deal with them, etc.

Choose something you want to do but don't really care that much about. Be more ambitious than you think you could be, have a high bar on the outcome but purposefully choose to completely ignore the actual code. Make it write tests, dashboards, monitoring - whatever you need other than code to feel confident.

Now is the cheapest time it will ever be to experiment.

This is why I like GitHub Copilot's autocompletion, I'm right there guiding and policing the code as it appears.

You're unable to stop being responsible? Tragic!

No one cares about good code. It’s a means to an end. Your code doesn’t need to look pretty or be well documented or any of that stuff anymore because people are not looking at it. The only thing people care about is performant and error free code.

From my perspective as a power user, the product has improved substantially over the past six months. It has gained new features that are actually useful, lots of UI/UX/perf improvements, and bug fixes as well.

New features have actually been remarkable. For me they are almost always in one of two categories: things I've always wanted (but never actually bothered communicating to the devs), and things I didn't know I needed but did. The product team is clearly very tuned in.

All in all, I'd say their approach is working.

We've had great success with a custom gh action on a self hosted runner. It sets up codex and all the same stuff a dev has on their machine:

So dbs, seed files, etc, and then just a review prompt and some skills and a few scripts.

It triggers on a new published PR or if tagged @bot-name. It's way better than the other services we've tried (which was admittedly ages ago) because you can get it to work exactly how you want it and it's dead simple.

With Codex, for the time being at least, you can use a subscription, so it's basically free if you're already paying for one. But on API pricing it's still not too bad as it doesn't produce that much output.

I set this all up in about half a day. Codex does 99% of the heavy lifting.

Using a different lab's model to review the code to the one that wrote it. Claude model plans/codes, OpenAI model reviews, or vice versa, or DeepSeek or GLM or whatever.

> the claude code review product originally mentioned it cost "$15-25 per review" (which is absurd)

If an engineer paid $150,000 a year reviews some code manually for about 30 minutes, the cost of their time is about $36.

The UI has improved substantially over the past six months. New capabilities are prominently featured and less-used ones are de-emphasized or removed. Every product goes through this type of evolution. The difference with Claude Code is that at the speed they iterate, it happens a lot faster and is therefore more noticeable.

I just learned that manually invoked skills MUST be the _first_ thing in the prompt, e.g. you can't have `disable-model-invocation: true` and say "Hi, /grill-me on X".

Worse, everything after the /grill-me is injected a second time into the prompt as a <command-args> so your prompt is literally added to the context TWICE. (first time in the original user prompt.)

I swear Anthropic is intentionally bloating your context so you burn tokens on useless bullshit like this.

I was running into something similar where I had it working on a single Python file. Maybe part of the issue is that I had memory turned off, and the conversation might have spilled into two conversations. I wasn't using version control either, but since it was a single file with about 1000 lines of code, it didn't seem too hard to eventually get all of my features back.

I snorted laughing at this. "We are experiencing tremendous growth" and it's just a codebase with 1,000 agents endlessly adding markdown documentation for every 1 line change.

There was a post some months back called "Lines of Code Got a Better Publicist" or something along those lines. This is just more of that. I am not impressed by 30 thousand "changes" per day in the slightest without significant added context. When I logged in and prompted Claude today, do I feel like I got +600,000 change value from when I logged in a month ago?

lol right? So youre telling me they shipping 150,000 features this week? Or, maybe, they whack-a-moled 149,995 perf or bug regressions and shipping 5 new things. :shrug:

I, too, can write and merge 30000 changes per day. Even 300000 if I've up to.

Of course, just like "line of code" is a worthless metric, "change merge per day" is;

  for i in {1..10000000}
  do
    echo "I am working !" >> README.md
    git add README.md
    git commit -s -m "feat: working with AI"
  done

The premise is clear, is one agent can do what developer can, but quicker, why not speed up the whole workflow to match it?

That's the trick: they don't

1000/day in what sounds like a single repo is a low number?