I'd love to do something like this, or use API keys, but I still don't understand how people justify the cost of using API keys vs. subscription.
I tested it once, I'm in on the 20x claude max ($200/month) and I either max my weekly limit every week or come really close. But it only took 2-3 days to hit $200 spend with api keys.
I had a subscription for a few months. I found that at the end of every week I would succumb to the sunk cost fallacy and try to squeeze all the usage out of my subscription. I'd rather pay a little extra in LLM cost to not have that issue.
People using API keys heavily, are either making enough money from whatever they're doing to afford Anthropic's high prices, or are using a mix of locally hosted and cloud-based models. E.g. using a cloud model as a planner/orchestrator, with a local model as a subagent that follows the orchestrator's designs/instructions.
I think in many cases the token bloat comes from using a fleet of autonomous agents that "collaborate" over a problem. Using one coherent agent loop with a human involved might not feel as futuristic but it's more effective and efficient (right now).
We have two wildly different cohorts of people. Those who see these tools as a technological curiosity and those who see them as a means to a specific end. I know that if I finish a task with a certain set of constraints that I will get paid a certain amount of money. I'd much rather be HITL on one very good agent loop if there is real money on the table. If you are mostly having fun, being curious, or exploring (which is fine!) then the cost of subscriptions might feel safer. Running an IRL version of factorio can get very expensive.
I also think the API tokens perform better but I have zero evidence other than observing the quality of my work product relative to that of my peers. I have almost a religious fervor about using prepaid tokens now. I am still using GPT5.5 in my copilot with custom model configuration for most heavy lifting in visual studio. It is more than sufficient. My average monthly token cost is <$100. Paying for a subscription would be more expensive because I have a predictable and controllable amount of demand.
This is analogous to variable vs fixed rate electricity. Paying the real time wholesale price is a massive economic advantage if you can figure out how to control the demand side of the house.
I often read opinions where people say their particular method of more hands-on working with AI is the most efficient and reasonable way.
From 500 hours working on my mobile app project outside of work, I can confidently say that using anywhere between 2 to 10 conversations to parallelize work is much more effective in my project.
The models being served in the API are the same as via the subscription, there are no shenanigans here, particularly not concerning quality.
And GPT 5.5 was great at the time, I made heavy use of it for my project, but it's long outdated and already being retired.
You also mentioned using it in copilot, which is a third-rate harness that is frustratingly buggy and inefficient.
There's no comparison to Opus 5.5 in Claude Code.
Use whatever works for you, but frankly, I think you should try something new.
> This is analogous to variable vs fixed rate electricity. Paying the real time wholesale price is a massive economic advantage if you can figure out how to control the demand side of the house.
rrr_oh_man is claiming that wholesale fixed rate electricity is generally cheaper than varible rate domestic electricity. Or that the wholesale-bit is higher order than the variable rate-bit. Not that it's a big issue, bob1029's point doesn't actually care about one situation being wholesale. It's just a somewhat narrow, (in this case) inconsequential, but also valid, nitpick.
The current crop of flash models are more comparable to sonnet than opus but they are very affordable.
The reality is that the subscriptions are heavily subsidized. Pretty much every sub that's not run by one of the money-burning frontier labs has had to drop it or dramatically increase prices and lower limits in the last few months. Cheap tokens are an acquisition tool, not a real product. It sounds dramatic but it really is the drug dealer sales funnel.
At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less. Better to get a handle on it now.
> At some point they're going to drop the real prices in your lab
The real price for tokens at a specific level of intelligence is dropping rapidly. Between models improving and new hardware getting faster, I think prices will be going down, not up.
> Better to get a handle on it now.
I experiment with a lot of providers and models. I strongly disagree that anyone needs to start migrating now in preparation for prices maybe going up in the future.
It doesn’t make sense. Deal with a price increase when it happens, if it does.
Switching models and providers isn’t some huge lift. I can jump to a new model or even hardness and get a feel for it in a day or two. It’s not some huge undertaking that requires preparation and planning.
If prices go up, try something at that point in time. Don’t worry about it until then.
When Claude Code subscriptions really started to catch on, there was a popular idea on HN that Anthropic's end game was that basically every dev adjacent role would need to pay for a $200/mo coding plan.
Then, both Anthropic and OpenAI in lockstep developed a enterprise pricing structure that openly coerced large businesses to pay API prices where it was feasible to spend $200/day rather than the comparatively cheap $200/mo.
Even if token pricing relative to intelligence does trend down over time, that doesn't mean the pricing structure will actually translate to lower costs, particularly in the cash cow B2B market.
From experience, if you work somewhere with very disconnected higher ups a sales person shows what your token usage is vs spend on the monthly subs for whatever set of users you have and then show an API price with a sample bill for even “more users” at that same number of tokens that is 30% lower. The crux of course being that your existing user base is not going to use fewer toke a just because you signed more people up and have a discount for the status quo.
Then when you consolidate all users to a single provider you find out you have a 2x to 3x larger bill because you… logically have more users at the same average token spend than the quote.
At my previous job, all while managing a full team, I did a lot of porting of legacy apps to modern standards to maintain various obligations. It was AI gen work in between meetings and paperwork. It was seen as such a success that I was asked to move to an IC role to focus on it within the “Elite new products team” that was supposed to be all AI and the latest tech. I showed up to find that they were pushing out low quality manually written code in 12 hour days six days per week to appear like LLMs were in use to save face because they lacked a token budget or the skills to properly manage one under the APIs. They had dismissed someone who had spent multiple thousands per month on Agent swarms. It was the perfect situation to make their 3x budget issue a 10-30x budget spend issue.
For many many reasons I left that job and got a new one but that was the cherry on top.
Companies still believe they have IP to protect. Even when all they do are basic CRUD systems or on the verge of collapsing if they don’t renew some contracts.
It's not obvious the subsidization will end. Loss leaders are a thing. Most enterprise at this point are paying API pricing
To better predict what they'll do with it we'd need to know the proportion of token usage via API vs subscription. Keeping an affordable, slightly unprofitable subscription to get people in isn't a bad idea. They also get marketing benefits from the word of mouth
In the optimistic case you describe, what smart customers want to watch out for is being lured into vibing your projects into such byzantine slop-complexity that subscription plans and trailing models are no longer sufficient to make progress on them.
Vibe-coders talk about surrendering understanding to the models, trusting that there will always be a model able to overcome and work through any technical debt they happen to accumulate, but the danger that still lurks there (at least for the naive) is that you'll need increasingly large contexts, increasingly sophisticated models, and increasingly large token spends just to keep that ball rolling.
Between profitable enterprise accounts being ineligible for subscription, eager but busy people paying for underutilized subscriptions, and naive vibe-coders falling into their pit trap, you can indeed imagine subsidized subscription accounts being available for a long time and remaining an effective value hack for people careful enough not to fall into the pit trap. But only insofar as they are that careful.
Also they can always find another way to make money. Make subscription users product and sell some analytics like "show most trending project being built this week".
Also, some subset of developers on subscriptions are going to develop products that use the API, and some of those products are going to be successful.
You cannot predict the future, but you can identify risks and attribute a likelihood. A risk is that the subsidized inference will either end or be reduced significantly in the next 1-2y. If you think the likelihood is high enough it makes sense to ensure your systems are prepared for it.
>At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less. Better to get a handle on it now.
So just wait until that happens? What's the point of scrimping and saving now? Not to mention you're paying for a premium in the meantime.
> At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less.
This only applies under the assumption that everyone tokenmaxxes their subscription.
I have visibility across a few different Claude team subscriptions. I'd say roughly 10% of people max their subscriptions.
I think I've only seen one organization where the under-used subs don't more than pay for the tokenmaxxed ones.
And that is ignoring the 90% margin that API inference runs at.
(meta commentary)
really gnarly word choice: "drop" in "they're going to drop the real prices in your lab"?
I took your meaning as "they're gonna drop [a bad surprise on you by raising] the real prices"... so at least it's not quite as tortured as the ambiguous "support for version N dropped today" (where you often can't even infer the direction from context).
this isn't just a tangent, I'm having trouble understanding the point you're trying to make, which hinges entirely on deciding if you meant "drop" literally
The term "drop" becoming a synonym for "release", "put out" or "put into effect" for things outside of music/albums is one of the most confusing linguistic innovations of the last decade.
They meant "they're going to drop a bad surprise by charging you API prices", so yes, a better wording would be "they're going to give you a bad surprise in the form of forced API pricing".
For a lot of large scale day to day work, deepseek / zai models (the latter comes with a subscription) can be very cost effective and very competitive actually.
Another thing of note is that when coding at 'scale' to my surprise over time with memory aggregation across users/sessions these models can be better than the evals would have you believe because they seem to be differently/less (?) RL'ed (aka actually listen to instructions), which results in them being more fastidious about writing memories and benefiting from them, especially over time. These are of course mostly subjective opinions but they were surprising, and not what we were expecting.
Relevant: the proxy we wrote and use:
https://yapp.latchlabs.dev is partially open sourced: still working on releasing more of our memories stuff.
I'm with you there. I'm on expensive plans with everyone because I run out of tokens and rotate/use the models that are best in their niche...
CLI Model Pct Remaining Reset Date
claude all models 15% 3d
claude Fable 50% 3d
grok all models 0% 4d
agy Gemini 36% 5d
agy Claude and GPT models 0% 5d
codex codex 0% 6d
And I also just used two of my three get-another-week-free tokens for codex.
If you've got an agentic swarm, or are working on multiple big projects at once, or have agents parsing data... you burn through tokens fast. The last four days in API would have cost me well over $3k.
Personally at home I use the free github copilot and then openrouter when that runs out. Last month I used $0.90 of openrouter. Zero so far this month. When my bill starts hitting double digits I'll consider options.
Different matter at work but even there we are paying for API costs and have a monthly allowance (starts at $200/month but increases fairly easy to get)
The drug dealer gives you a free hit because it is profitable for him in the long term for you to be addicted to his product, not because he is your friend.
If you're genuinely curious, I'd recommend searching around about the history of this persistent urban legend. It's really interesting.
But the short version is that there are lots of people who want to buy any given drug and drug dealers sell them. I don't know exactly what you mean by "WAIT for people to demand the more profitable drugs", but there typically isn't a whole lot of waiting. There's a lot of demand out there. Giving away a bunch of free fentanyl to random people in the hopes that one of them instantly gets addicted would be a pretty wasteful and high risk sales tactic, especially given the number of people that want to buy it already.
...yes? It doesn't literally kill you if use more tokens than usual?
And we're talking about subscription plans from OpenAI/Anthropic here. Switching to a different model and/or harness if the price changes isn't a "the world has run out of opioids and I'm going to need a detox center" level crisis.
The original question was "are you sure an OpenAI subscription isn't heroin?" Different impacts of overuse (death vs slop code) feels like a valid point of difference.
This is a weirdly melodramatic analogy.
If you want to flatten everything to "all things habit forming are definitionally equivalent", you'll get some pretty funky results.
You're equivocating, they were talking about addiction, you're talking about overuse/overdose which is where the analogy breaks down for pretty obvious reasons.
What? (1) Yes.. it's never that [stupid economics, they don't want their purchasers to die.. might as well sell fentanyl], (2) it's always that [hardly any way to propose alternatives.. within the scope of not killing the customer]
I'm not sure exactly what you're implying but if you're curious, there's a lot of writing about the persistence of this particular urban legend. A lot of it starts with 1920s newspapers painting pictures of dastardly drug peddlers luring in children with free drugs to get them hooked.
Turns out that drug dealers by and large prefer the straightforward approach of selling drugs to the huge market of people who want to take them.
I think businesses are footing the majority of that bill right now due to regulatory requirements, but for individuals that price increase is def coming. Maybe I'm too pessimistic, but enjoy it while it lasts :')
You might not have a choice. For example, if you want to get a guarantee from Anthropic that they don't train bases on your prompts, you will need an enterprise deal, which is pay-by-token.
For subscriptions, it is easier to collect the JSONL files from ~/.claude/projects/ and similar directories. They are better organized (e.g., subagents) than what the proxy sees.
However, the best value comes from collecting agent sessions across the whole organization. You'll need to scrub credentials and handle security.
Isn't any personal data a PII? You just need a couple of personal o enable t identify individual. And if this is in an org then amount of individuals is quite small, so sometimes it needs just one personal detail.
If you have dyslexia and I know it, that brings it down to 20% of people. Combined with some other data, this is a pretty good factor to narrow it down to "who you are", right?
GDPR doesn't cover unrecorded human memory, so you're fine to overhear whatever in a day-to-day setting. If you then do anything that looks like digital processing or cataloguing that information though, then you're making it a GDPR issue.
Unless you are a robot, you'll be fine. GDPR is about digitally recorded information. If you are a robot, it's probably best to delete that information.
Technically you can still run Claude-Code through proxies though, even with the subscription.
Right now I run my Claude-Code sessions through a very simple mitmproxy, logging everything that goes in & out. It's very low level, sure, but it works.
What’s the best way to pull (ie archive) and search these across a few harnesses? I remember seeing a project or two trying to standardize them, but can’t find anything that seems to be a good sensible solution
Mlflow does it pretty nice including session gathering and optional data enrichment (eg what files were touched, what model was used, git remote).
We use these session IDs for commenting on issues and stories touched by AI for context tracing.
I just wrapped around the Mlflow setup to make this simple CLI helper to set it up. Ofcourse the name suggests only Claude but it’s Codex, CC, GHCP and Agy. https://pypi.org/project/claudetracing/
Ask claude to do it end to end, then write a solution that fits your needs from it's experience with you driving it.
I did exactly this - probably the single most valuable piece of software I've "written". It's the backbone of every piece of code coming out of any agent under my control (via MCP toolset).
Tailscale makes Aperture available for free, and while it's not something you own, it is in your tailnet, so at least you have a certain amount of control over how things access it.
It gives a nice view of what agents are doing, with lots of configurability and extensions, and the team behind it has been updating pretty steadily.
I happen to be working on an extension to Aperture, so I have my own reason to promote it. But I do think it's a nice easy solution, and I promoted it to people before I was extending it.
I'm building a "bring your own data" layer for agentic work of all sorts, using the webhook method for now.
In the context of Aperture, I watch for agents looking for certain types/sources of data, and instead provide them with an in-tailnet API for accessing that data.
In a personal context, think email, calendar events, music playlists, fitness app records, transactions. I've also found it useful in a professional context, but I think I need to explore that a fair bit more.
It keeps credentials out of agents hands, and provides some relatively standard ways for controlling what agents can see and change.
I need a fair bit of hardening work before I try to get random folk to use it, but I might post something more here in the next week. :)
I’m not sure what people are doing with these subscriptions to feel the need to monitor what’s going on this closely. A $100 OpenAI subscription feels effectively infinite for my usage at home
In similar spirit, the biggest motivation for me to set up DeepSeek Flash over Opus 5.5 would be seeing the reasoning traces, which is a mere curiosity.
I let them install the free ISP router a year back when they installed fiber in the neighborhood. I assumed I would swap it out the next day, but I haven't had any issues like back in the day. I love shopping for a nice router as much as the next tech nerd, but decent drop-in home networking seems to be pretty commodity now days.
I've never touched my ISP-provided router. But maybe it's just how it works in my country (Malaysia), we pretty much only have 1 ISP with monopoly, so maybe that helps.
Cache TTL will get you anyway. For Claude subscriptions, subagents still have a 5m TTL and before I discovered that, their constant waits for ~10 min tests or similar tasks would destroy my 5h usage. And for my API subscription at work, Claude has a 5m TTL for all stuff, and that's nowhere near long enough. You have to be monitoring this unless you want to absolutely torch your company's budget.
what proxy is he using? i support not trying to support a specific product in a post but not even mentioning what you use after writing this seems pretty odd.
1) What kind of guardrails are you using? Do you do models like prompt injection checkers? Or what guardrails are useful that do not know the environment the agent lives in?
2) I heard Bifrost also works for this. Did you try that as well, pros/cons?
I'm not the person you asked but yes pretty much. I've found the prompt injection protection models pretty limited, but get good results from gpt-oss-safeguard with a policy describing various prompt injection techniques. More expensive but more flexible and reliable and I only run it on web fetch and web search results. Costs me like 5-20 cents a day depending on what I'm working on.
Just one info for many: if you’re a big company and have enterprise needs, subscriptions aren’t a solution. OpenAI, Anthropic, Google (ain’t sure about them tbh), GitHub Copilot aren’t offering subsidized subscription prices in their enterprise plans; discounts are calculated differently and these services are much more expensive.
For example, Github Copilot has these AI credits that are insane in terms of costs with the usual token-based pricing.
Enterprise plans are almost never subsidized. You are paying a premium to get what others are missing. Guarantee of data residency, SLA agreements, fast support etc.
How do you ditch Claude Code without paying for API tokens? (Assuming from the way you phrased it that you still use Claude, only you didn't want the system prompts that came with Claude Code.)
Last I looked into it, using other harnesses with a subscription was a TOS violation that Anthropic seemed to take quite seriously (with automatic rate limiting etc.)
Mostly using GLM/zai and pi agent these days. GLM also allows hermes on their subscription which is very useful.
If I do need Opus/whatever to look at a specific issue I just use openrouter API.
Can't say I particularly care for the US providers walled garden ToS restricted handholding suprise fallback nonsense even if their models are the strongest. Most of my tasks work just fine with lagging behind absolute SOTA so don't feel the need to tolerate it.
Yeah you should run an LLM proxy, but imagine a world where LiteLLM and all the other LLM shovels weren't buggy vibecoded messes. And with the velocity of updates I feel there has to be vulnerabilities there. Or am I just holding it wrong? Anyone got a good alternative?
This general phenomenon is not new, but it has been so obvious during 2026. Everyone want to consume everyone else hard work, to create their own slop. Just pure egoism.
OpenRouter does all this for you. It's pretty nice. Although for apps I use another server to lock down the requests even more and prevent the client from seeing my API key.
I agree its so important to proxy and capture all the data. I've been very happy with bifrost as a proxy. It's a quality piece of software, unlike LiteLLM. You also get this one interface to access all your models, across all services, including self-hosted, STT models, everything. There are ways to use subscriptions with proxies too, but they are discouraged because of grey-hat uses..
prob a noob question; but what kind of data are people looking to get to help with what kind of decisions with these tools?
i can see some IT/infra team using these tools to manage their LLM costs, but this blog post seems to hint at some kind of product decision making? what am i missing here?
It is a not proxy. It can clearly show whats going on across all agents. The proxy's are generally inconvenient and yet another point of failure. I think the author got to the resort option quickly
I don't do this but I do have a system that imports all my conversations with AI (claude code, chatgpt, claude app, etc.) to a storage system I call Chatacombs: a unified storage of most conversations I've had with AI, as detailed as I can easily get.
there's the kind of people who care and the kind who doesn't ...
your local politicians and landlords do all kinds of normal, non-funky stuff you don't know about ... as do your local ISP-techies and hobbyists with access to supply chains and sub-distributing units ...
or your local school teachers and some parents and their widdle vintage schemes and circumambient tales they tell some kids but not others ... Lord, some guy even caught teachers and parents running schemes on teens to prep them for gay homo fag stuff, despair, frustration ... running for years ...
and you wonder how peeps don't what is going on xD?<
even those hackies and hackers and programmers and brogrammers and AI superusers who think they know and care and wield some power really really don't
Well that was one of the reasons why i build my own agent/harness - to have actual full observability of what it is doing and why it is doing what it is doing.
Don't really understand why other agents to give those insights but well found my solution.
Because the details we care about right now already travelling over the network and the industry is adopting OTEL, where you can export and collate kernel things if you need to
All that posturing for the purpose to be manually monitoring cache hits and misses. This can't be serious. Buy a larger plan or reduce some instructions and you don't have to deal with this waste of time.
With just a 12gb VRAM GPU + 64gb of CPU RAM, and you can actually own your own infrastructure. I can't wait for hardware prices to fall so that becomes even more accessible.
I am boggled how the first step of an llm after you make an orchestrator isn't some kind of proxy that records your personal internet surfing to be used by your personal AI later. Every college should be running in house AI with their own in house search engines and in house any service. Don't go to any college that wants you to use chatgpt or other corporate nonsense. If they can't make local LLMs work, they are not a real college.
I use GoModel and its amazing. My favorite features are virtual model, the support for arbitrary request labels, and the nice dashboads / ui. Creator has more sophisticated report generation on the near term roadmap. He's super responsive to feedback and ships fast. (except for his recent trip to the US west coast to meet founders and investors, he's EU based)
You can use and control all.your subscriptions or aoikeys through a gateway like this, so you don't get pwned like what just happened with OpenCode (or an OpenRouter like vendor). GoModel has some ambitions like this, but is open source so you can run it on you own infra, with plans for self hosted enterprise as well (there are a few features already like SSO). We are rolling out the free version at work right now.
I run GoModel at home and have hyper detailed history of every agent interaction, across models running on my sparks and OpenCode sub. You can call me a committed superfan of this project.
I tested it once, I'm in on the 20x claude max ($200/month) and I either max my weekly limit every week or come really close. But it only took 2-3 days to hit $200 spend with api keys.
Oct 16 I switched machine
Excludes work done on local and Claude Chrome plugin.
We have two wildly different cohorts of people. Those who see these tools as a technological curiosity and those who see them as a means to a specific end. I know that if I finish a task with a certain set of constraints that I will get paid a certain amount of money. I'd much rather be HITL on one very good agent loop if there is real money on the table. If you are mostly having fun, being curious, or exploring (which is fine!) then the cost of subscriptions might feel safer. Running an IRL version of factorio can get very expensive.
I also think the API tokens perform better but I have zero evidence other than observing the quality of my work product relative to that of my peers. I have almost a religious fervor about using prepaid tokens now. I am still using GPT5.5 in my copilot with custom model configuration for most heavy lifting in visual studio. It is more than sufficient. My average monthly token cost is <$100. Paying for a subscription would be more expensive because I have a predictable and controllable amount of demand.
This is analogous to variable vs fixed rate electricity. Paying the real time wholesale price is a massive economic advantage if you can figure out how to control the demand side of the house.
From 500 hours working on my mobile app project outside of work, I can confidently say that using anywhere between 2 to 10 conversations to parallelize work is much more effective in my project.
The models being served in the API are the same as via the subscription, there are no shenanigans here, particularly not concerning quality.
And GPT 5.5 was great at the time, I made heavy use of it for my project, but it's long outdated and already being retired.
You also mentioned using it in copilot, which is a third-rate harness that is frustratingly buggy and inefficient.
There's no comparison to Opus 5.5 in Claude Code.
Use whatever works for you, but frankly, I think you should try something new.
Wholesale electricity is almost always cheaper.
Sorry, I have to be that guy... https://xkcd.com/386/
The analogy is false.
Domestic electricity is priced per kWh, wholesale electricity is priced per kWh, the latter is, as a rule, cheaper. It is not fixed vs variable rate.
> wholesale electricity is priced per kWh
> the latter is, as a rule, cheaper.
I think you’re missing some detail. Why do two things that are “priced per kilowatt hour” have to have different prices?
The reason is mostly higher consumption = lower average price.
The reality is that the subscriptions are heavily subsidized. Pretty much every sub that's not run by one of the money-burning frontier labs has had to drop it or dramatically increase prices and lower limits in the last few months. Cheap tokens are an acquisition tool, not a real product. It sounds dramatic but it really is the drug dealer sales funnel.
At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less. Better to get a handle on it now.
The real price for tokens at a specific level of intelligence is dropping rapidly. Between models improving and new hardware getting faster, I think prices will be going down, not up.
> Better to get a handle on it now.
I experiment with a lot of providers and models. I strongly disagree that anyone needs to start migrating now in preparation for prices maybe going up in the future.
It doesn’t make sense. Deal with a price increase when it happens, if it does.
Switching models and providers isn’t some huge lift. I can jump to a new model or even hardness and get a feel for it in a day or two. It’s not some huge undertaking that requires preparation and planning.
If prices go up, try something at that point in time. Don’t worry about it until then.
Then, both Anthropic and OpenAI in lockstep developed a enterprise pricing structure that openly coerced large businesses to pay API prices where it was feasible to spend $200/day rather than the comparatively cheap $200/mo.
Even if token pricing relative to intelligence does trend down over time, that doesn't mean the pricing structure will actually translate to lower costs, particularly in the cash cow B2B market.
Then when you consolidate all users to a single provider you find out you have a 2x to 3x larger bill because you… logically have more users at the same average token spend than the quote.
At my previous job, all while managing a full team, I did a lot of porting of legacy apps to modern standards to maintain various obligations. It was AI gen work in between meetings and paperwork. It was seen as such a success that I was asked to move to an IC role to focus on it within the “Elite new products team” that was supposed to be all AI and the latest tech. I showed up to find that they were pushing out low quality manually written code in 12 hour days six days per week to appear like LLMs were in use to save face because they lacked a token budget or the skills to properly manage one under the APIs. They had dismissed someone who had spent multiple thousands per month on Agent swarms. It was the perfect situation to make their 3x budget issue a 10-30x budget spend issue.
For many many reasons I left that job and got a new one but that was the cherry on top.
To better predict what they'll do with it we'd need to know the proportion of token usage via API vs subscription. Keeping an affordable, slightly unprofitable subscription to get people in isn't a bad idea. They also get marketing benefits from the word of mouth
Vibe-coders talk about surrendering understanding to the models, trusting that there will always be a model able to overcome and work through any technical debt they happen to accumulate, but the danger that still lurks there (at least for the naive) is that you'll need increasingly large contexts, increasingly sophisticated models, and increasingly large token spends just to keep that ball rolling.
Between profitable enterprise accounts being ineligible for subscription, eager but busy people paying for underutilized subscriptions, and naive vibe-coders falling into their pit trap, you can indeed imagine subsidized subscription accounts being available for a long time and remaining an effective value hack for people careful enough not to fall into the pit trap. But only insofar as they are that careful.
That’s risk management 101
So just wait until that happens? What's the point of scrimping and saving now? Not to mention you're paying for a premium in the meantime.
It does make me sharper I think. If you only ever use claude or whatever you don’t even really know exactly how tied to it you are.
Funny enough the drug dealer thing still holds. A deal’s a deal if you’re going to buy it anyway.
This only applies under the assumption that everyone tokenmaxxes their subscription.
I have visibility across a few different Claude team subscriptions. I'd say roughly 10% of people max their subscriptions.
I think I've only seen one organization where the under-used subs don't more than pay for the tokenmaxxed ones.
And that is ignoring the 90% margin that API inference runs at.
I took your meaning as "they're gonna drop [a bad surprise on you by raising] the real prices"... so at least it's not quite as tortured as the ambiguous "support for version N dropped today" (where you often can't even infer the direction from context).
this isn't just a tangent, I'm having trouble understanding the point you're trying to make, which hinges entirely on deciding if you meant "drop" literally
Another thing of note is that when coding at 'scale' to my surprise over time with memory aggregation across users/sessions these models can be better than the evals would have you believe because they seem to be differently/less (?) RL'ed (aka actually listen to instructions), which results in them being more fastidious about writing memories and benefiting from them, especially over time. These are of course mostly subjective opinions but they were surprising, and not what we were expecting.
Relevant: the proxy we wrote and use: https://yapp.latchlabs.dev is partially open sourced: still working on releasing more of our memories stuff.
CLI Model Pct Remaining Reset Date claude all models 15% 3d claude Fable 50% 3d grok all models 0% 4d agy Gemini 36% 5d agy Claude and GPT models 0% 5d codex codex 0% 6d
And I also just used two of my three get-another-week-free tokens for codex.
If you've got an agentic swarm, or are working on multiple big projects at once, or have agents parsing data... you burn through tokens fast. The last four days in API would have cost me well over $3k.
Someone who pays $20 a month may only use 10% of their max budget.
Different matter at work but even there we are paying for API costs and have a monthly allowance (starts at $200/month but increases fairly easy to get)
1. In most cases, like this one, the product isn't heroin.
2. Drug dealers don't actually do that.
I'm not sure about that. Someone using AI for productivity every day will experience massive issues if you suddenly take it away.
It's even the whole business model of MS Copilot: They don't work with companies to have their data structured in the past or going forward.
They don't help you to structure your business "life", they offer a tool you consume to make sense of it while you use it.
The moment you stop using it, you'll struggle to even make sense of your own past actions.
> "2. Drug dealers don't actually do that."
It would be a weird business if they only WAIT for people to demand the more profitable drugs...
But the short version is that there are lots of people who want to buy any given drug and drug dealers sell them. I don't know exactly what you mean by "WAIT for people to demand the more profitable drugs", but there typically isn't a whole lot of waiting. There's a lot of demand out there. Giving away a bunch of free fentanyl to random people in the hopes that one of them instantly gets addicted would be a pretty wasteful and high risk sales tactic, especially given the number of people that want to buy it already.
And we're talking about subscription plans from OpenAI/Anthropic here. Switching to a different model and/or harness if the price changes isn't a "the world has run out of opioids and I'm going to need a detox center" level crisis.
This is a weirdly melodramatic analogy.
If you want to flatten everything to "all things habit forming are definitionally equivalent", you'll get some pretty funky results.
Turns out that drug dealers by and large prefer the straightforward approach of selling drugs to the huge market of people who want to take them.
For subscriptions, it is easier to collect the JSONL files from ~/.claude/projects/ and similar directories. They are better organized (e.g., subagents) than what the proxy sees.
However, the best value comes from collecting agent sessions across the whole organization. You'll need to scrub credentials and handle security.
So id be very careful with chats and treat them like chats, not like code.
Is my brain now subject to GDPR regulations?
Not an attack on you, but my word am I thankful I don’t participate in the European regulatory regime.
not an attack on you, but I am thankful to have guardrails for greedy scrupulous corporations
Right now I run my Claude-Code sessions through a very simple mitmproxy, logging everything that goes in & out. It's very low level, sure, but it works.
I just wrapped around the Mlflow setup to make this simple CLI helper to set it up. Ofcourse the name suggests only Claude but it’s Codex, CC, GHCP and Agy. https://pypi.org/project/claudetracing/
https://github.com/CauchyIO/claudetracing
I did exactly this - probably the single most valuable piece of software I've "written". It's the backbone of every piece of code coming out of any agent under my control (via MCP toolset).
I happen to be working on an extension to Aperture, so I have my own reason to promote it. But I do think it's a nice easy solution, and I promoted it to people before I was extending it.
I'm building a "bring your own data" layer for agentic work of all sorts, using the webhook method for now.
In the context of Aperture, I watch for agents looking for certain types/sources of data, and instead provide them with an in-tailnet API for accessing that data.
In a personal context, think email, calendar events, music playlists, fitness app records, transactions. I've also found it useful in a professional context, but I think I need to explore that a fair bit more.
It keeps credentials out of agents hands, and provides some relatively standard ways for controlling what agents can see and change.
I need a fair bit of hardening work before I try to get random folk to use it, but I might post something more here in the next week. :)
For clarity, I do like blog posts like these.
I don't remember the last time this was true. These things don't have a 'just works' mode.
$100 a month on an LLM subscription for hobby usage is an absurd amount of money IMO.
I can't orchestrate agents in sandboxes without it.
1. It can issue virtual keys, so provider API keys never go near the sandbox
2. I can see everything
3. Guardrails
And much more
Looking forward to it.
2) I heard Bifrost also works for this. Did you try that as well, pros/cons?
For example, Github Copilot has these AI credits that are insane in terms of costs with the usual token-based pricing.
Feel free to prove me wrong, I really wish I was.
(Aside from ditching CC & it's bloated sys prompts that is)
Last I looked into it, using other harnesses with a subscription was a TOS violation that Anthropic seemed to take quite seriously (with automatic rate limiting etc.)
If I do need Opus/whatever to look at a specific issue I just use openrouter API.
Can't say I particularly care for the US providers walled garden ToS restricted handholding suprise fallback nonsense even if their models are the strongest. Most of my tasks work just fine with lagging behind absolute SOTA so don't feel the need to tolerate it.
Primaily designed as a local LLM ops project, but will definitely do proxying for claude-code, opencode, codex, etc
https://llama-dash.dev
i can see some IT/infra team using these tools to manage their LLM costs, but this blog post seems to hint at some kind of product decision making? what am i missing here?
my own ai gateway/proxy
It is a not proxy. It can clearly show whats going on across all agents. The proxy's are generally inconvenient and yet another point of failure. I think the author got to the resort option quickly
there's the kind of people who care and the kind who doesn't ...
your local politicians and landlords do all kinds of normal, non-funky stuff you don't know about ... as do your local ISP-techies and hobbyists with access to supply chains and sub-distributing units ...
or your local school teachers and some parents and their widdle vintage schemes and circumambient tales they tell some kids but not others ... Lord, some guy even caught teachers and parents running schemes on teens to prep them for gay homo fag stuff, despair, frustration ... running for years ...
and you wonder how peeps don't what is going on xD?<
even those hackies and hackers and programmers and brogrammers and AI superusers who think they know and care and wield some power really really don't
but there you go, AI augmented diluted delusions
Don't really understand why other agents to give those insights but well found my solution.
homelab running liteLLM or gomodel
...proceeds to use codex.
With just a 12gb VRAM GPU + 64gb of CPU RAM, and you can actually own your own infrastructure. I can't wait for hardware prices to fall so that becomes even more accessible.
You can use and control all.your subscriptions or aoikeys through a gateway like this, so you don't get pwned like what just happened with OpenCode (or an OpenRouter like vendor). GoModel has some ambitions like this, but is open source so you can run it on you own infra, with plans for self hosted enterprise as well (there are a few features already like SSO). We are rolling out the free version at work right now.
I run GoModel at home and have hyper detailed history of every agent interaction, across models running on my sparks and OpenCode sub. You can call me a committed superfan of this project.
https://github.com/ENTERPILOT/GOModel