Yes, my CC usage is regularly $50-$100 per day, so their Max plan is absolutely great value that I don’t expect to last.
The reason they are talking about building new nuclear power plants in the US isn't just for a few training runs, its for inference. At scale the AI tools are going to be extremely expensive.
Also note China produces twice as much electricity as the United States. Software development and agent demand is going to be competitive across industries. You may think, oh I can just use a few hours of this a day and I got a week of work done (happens to me some days), but you are going to end up needing to match what your competitors are doing - not what you got comfortable with. This is the recurring trap of new technology (no capitalism required.)
There is a danger to independent developers becoming reliant on models. $100-$200 is a customer acquisition cost giveaway. The state of the art models probably will end up costing hourly what a human developer costs. There is also the speed and batching part. How willing is the developer to, for example, get 50% off but maybe wait twice as long for the output. Hopefully the good dev models end up only costing $1000-$2000 a month in a year. At least that will be more accessible.
Somewhere in the future these good models will run on device and just cost the price of your hardware. Will it be the AGI models? We will find out.
I wonder how this comment will age, will look back at it in 5 or 10 years.
Probably because I am an old man, but I don’t personally vibe with full time AI assistant use, rather I will use the best models available for brief periods on specific problems.
Ironically, when I do use the best models available to me it is almost always to work on making weaker and smaller models running on Ollama more effective for my interests.
BTW, I have used neural network tech in production since 1985, and I am thrilled by the rate of progress, but worry about such externalities as energy use, environmental factors, and hurting the job market for many young people.
There are a lot of parts in the near term to dislike here, especially the consequences for privacy, adtech, energy use. I do have concerns that the greatest pitfalls in the short terms are being ignored while other uncertainties are being exaggerated. (I've been warning on deep learning model use for recommendation engines for years, and only a sliver of people seem to have picked up on that one, for example.)
On the other hand, if good enough models can run locally, humans can end up with a lot more autonomy and choice with their software and operating systems than they have today. The most powerful models might run on supercomputers and just be solving the really big science problems. There is a lot of fantastic software out there that does not improve by throwing infinite resources at it.
Another consideration is while the big tech firms are spending (what will likely approach) hundreds of billions of dollars in a race to "AGI", what matters to those same companies even more than winning is making sure that the winner isn't a winner takes all. In that case, hopefully the outcome looks more like open source.
I don’t see how that can be true, but if it is…
Either you, or I are definitely use Claude Code incorrectly.
Nobody's asking for $200 in single-line diffs in less than a day - right?
People are recreating this with local toolchains now.
You mean… it’s almost exactly like working with interns and jr developers? ;)
I would love to understand better just how Perplexity is able to integrate up-to-date sources like other theads (and presumably recent web searches, but I haven't verified this, they could be just from the latest model) into it's query responses. It feels seamless.
It rears its head regardless of what sociopolitical environment you place us in.
You’re either competing to offer better products or services to customers…or you’re competing for your position in the breadline or politburo via black markets.
And, since there is no global super-state, the world economy is a market economy, so even if every state were a state-owned planned economy, North Korea style, still there would exist this type of competition between states.
So yeah it basically comes down to your definition of "worker-owned". What fraction of worker ownership is necessary? Do C-level execs count as workers? Can it be "worker-owned" if the "workers" are people working elsewhere?
Beyond the "worker-owned" terminology, why is this distinction supposed to matter exactly? Supposing there was an SV startup that was relatively generous with equity compensation, so over 50% of equity is owned by non-C-level employees. What would you expect to change, if anything, if that threshold was passed?
If the workers are majority owners, then they can, for example, fire a CEO that is leading the company in the wrong direction, or trying to cut their salaries, or anything like that.
Why wouldn't the board fire said CEO?
The most common reason to cut salaries is if the company is in dire financial straits regardless. Co-ops are more likely to cut salary and less likely to do layoffs.
Also, lots of companies reduce salaries or headcount if they feel they can get away with it. They don't need to be in dire financial straights, it's enough to have a few quarters of no or low growth and to want to show a positive change.
What changes is democracy in the work place.
You are confusing owning minority equity with what actual control gives you —- actual ownership of capital/MoP/assets/profits
Remember, if employees own 49%, if they can persuade just 2% of the other shareholders that a change will be positive for the business, they can make that change. So minority vs majority is not as significant as it may seem.
Estimating productivity gains is a flame war I don’t want to start, but as a signal: if the CC Max plan goes up 10x in price, I’m still keeping my subscription.
I maintain top-tier subscription to every frontier service (~$1k/mo) and throughout the week spend multiple hours with each of Cursor, Amp, Augment, Windsurf, Codex CLI, Gemini CLI, but keep on defaulting to Claude Code.
It’s so stupid fast to get running that you aren’t out anything if you don’t like it.
There was no way I was going to switch to a different IDE.
Ultimately, my not using the best tools for my personal research projects has zero effect on the world but I am still very curious what elite developers with the best tools can accomplish, and what capability I am ‘leaving on the table.’
Are you doing front end backend full stack or model development itself?
Are you destilling models for training your own?
I have never heard someone using so much subscription?
Is this for your full time job or startup?
Why not use qwen or deep seek and host it yourself?
I am impressed with what you are doing.
As to “why”: I’ve been coding for 25 years, and LLMs is the first technology that has a non-linear impact on my output. It’s simultaneously moronic and jaw-dropping. I’m good at what I do (eg, merged fixes into Node) and Claude/o3 regularly finds material edge cases in my code that I was confident in. Then they add a test case (as per our style), write a fix, and update docs/examples within two minutes.
I love coding and the art&craft of software development. I’ve written millions of lines of revenue generating code, and made millions doing it. If someone forced me to stop using LLMs in my production process, I’d quit on the spot.
Why not self host: open source models are a generation behind SOTA. R1 is just not in the same league as the pro commercial models.
Yup 100% agree. I’d rather try to convince them of the benefits than go back to what feels like an unnecessarily inefficient process of writing all code by hand again.
And I’ve got 25+ years of solid coding experience. Never going back.
Which frameworks & libraries have you found work well in this (agentic) context? I feel much of the js lib. landscape does not do enough to enforce an easily-understood project structure that would "constrain" the architecture and force modularity. (I might have this bias from my many years of work with Rails that is highly opinionated in this regard).
I think Fiction LiveBench captures some of those differences via a standardized benchmark that spreads interconnected facts through an increasingly large context to see how models can continue connecting the dots (similar to how in codebases you often have related ideas spread across many files)
https://fiction.live/stories/Fiction-liveBench-May-22-2025/o...
> I’ve written millions of lines of revenue generating code
Approx 250 working days in a year. 25 years coding. Just one million lines would be phenom output, at 160 lines per day forever. Now you are claiming multiple millions? Come on.
1. Before wife&kids, every weekend I would learn a library or a concept by recreating it from scratch. Re-implementing jQuery, fetch API via XHR, Promises, barebones React, a basic web router, express + common middlewares, etc. Usually, at least 1,000 lines of code every weekend. That's 1M+ over 25 years.
2. My last product is currently 400k LOCs, 95% built by me over three years. I didn't one-shot it, so assuming 2-3x ongoing refactors, that's more than 1M LOCs written.
3. In my current product repo, GitHub says for the last 6 months I'm +120k,-80k. I code less than I used to, but even at this rate, it's safely 100k-250k per year (times 20 years).
4. Even in open source, there are examples like esbuild, which is a side project from one person (cofounder and architect of Figma). esbuild is currently at ~150k LOCs, and GitHub says his contributions were +600k,-400k.
5. LOCs are not the same. 10k lines of algorithms can take a month, but 10K of React widgets is like a week of work (on a greenfield project where you know exactly what you're building). These days, when a frontend developer says their most extensive UI codebase was 100k LOCs in an interview, I assume they haven't built a big UI thing.
So yes, if the reference point is "how many sprint tickets is that", it seems impossible. If the reference point is "a creative outlet that aligns with startup-level rewards", I think my statement of "millions of lines" is conservative.
Granted, not all of it was revenue-generating - much was experimental, exploratory, or just for fun. My overarching point was that I build software products for (great) living, as opposed to a marketer who stumbled into Claude Code and now evangelizes it as some huge unlock.
10 years would make 500k and you just cross a million at 20.
So that would have to be 20 years straight of that style of working and you’re still not into plural millions until 40 years.
If someone actually produced multiple millions of lines in 25 years, it would have to be a side effect of some extremely verbose language where trivial changes take up many lines (maybe Java).
i've tried agent-style workflows in copilot and windsurf (on claude 3.5 and 4), and honestly, they often just get stuck or build themselves into a corner. they don’t seem to reason across structure or long-term architecture in any meaningful way. it might look helpful at first, but what comes out tends to be fragile and usually something i’d refactor immediately.
sure, the model writes fast – but that speed doesn't translate into actual productivity for me unless it’s something dead simple. and if i’m spending a lot of time generating boilerplate, i usually take that as a design smell, not a task i want to automate harder.
so i’m honestly wondering: is cc max really that much better? are those productivity claims based on something fundamentally different? or is it more about tool enthusiasm + selective wins?
Honestly reading some of the comments here makes me want to do some sort of course on using them properly. I feel like I'm using them incorrectly.
My app builds and runs fine on Termux, so my CLAUDE.md says to always run unit tests after making changes. So I punch in a request, close my phone for a bit, then check back later and review the diff. Usually takes one or two follow-up asks to get right, but since it always builds and passes tests, I never get complete garbage back.
There are some tasks that I never give it. Most of that is just intuition. Anything I need to understand deeply or care about the implementation of I do myself. And the app was originally hand-built by me, which I think is important - I would not trust CC to design the entire thing from scratch. It's much easier to review changes when you understand the overall architecture deeply.
i found opus is significantly more capable in coding than sonnet, especcially for the task that is poorly defined, thinking mode can fulfill alot of missing detail and you just need to edit a little before let it code.
"Agentic" workflows burn through tokens like there's no tomorrow, and the new Opus model is so expensive per-token that the Max plan pays itself back in one or two days of moderate usage. When people reports their Claude Code sessions costing $100+ per day, I read that as the API price equivalent - it makes no sense to actually "pay as you go" with Claude right now.
This is arguably the cheapest option available on the market right now in terms of results per dollar, but only if you can afford the subscription itself. There's also time/value component here: on Max x5, it's quite easy to hit the usage limits of Opus (fortunately the limit is per 5 hours or so); Max x20 is only twice the price of Max x5 but gives you 4x more Opus; better model = less time spent fighting with and cleaning up after the AI. It's expensive to be poor, unfortunately.
I've yet to use anything but copilot in vscode, which is 1/2 the time helpful, and 1/2 wasting my time. For me it's almost break-even, if I don't count the frustration it causes.
I've been reading all these AI-related comment sections and none of it is convincing me there is really anything better out there. AI seems like break-even at best, but usually it's just "fighting with and cleaning up after the AI", and I'm really not interested in doing any of that. I was a lot happier when I wasn't constantly being shown bad code that I need to read and decide about, when I'm perfectly capable of writing the code myself without the hasle of AI getting in my way.
AI burnout is probably already a thing, and I'm close to that point already. I do not have hope that it will get much better than it is, as the core of the tech is essentially just a guessing game.
So I vibe coded it. I was extremely specific about how the back end should operate and pretty vague about the UI, and basically everything worked.
But there were a few things about this one: first, it was just a prototype. I wanted to kick around some ideas quickly, and I didn't care at all about code quality. Second, I already knew exactly how to do the hard parts in the back end, so part of the prompt input was the architecture and mechanism that I wanted.
But it spat out that html app way way faster than I could have.
It is also BYOA or you can buy a subscription from Zed themselves and help them out. I currently use it with my free Copilot+ subscription (GitHub hands it out to pretty much any free/open source dev).