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.
Let me know if any issues, happy to help
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.
Check out Calibra for example: https://calibra.swival.dev which turns traces from Swival into nice web pages, allows diff'ing traces, etc.
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
I'm a little miffed that this isn't just an immediate OOBE, but I'm prepared to do some nc/ssh tunnel magic if that'll work properly .. just wondering what other DGX users have vis a vis best practices ..
...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.
Both Codex[0] and Claude Code[1] output OTEL traces that you can ingest and process.
Other harnesses like OpenCode, Pi, etc. you can hook into their plugin architecture and implement your own OTEL emission from a plugin (or use an off the shelf plugin[2]).
Host an OpenTelemetry collector[3][4] or rely on your existing collector infra (e.g. Datadog (no affiliation), AppInsights, etc.)
The OTEL traces will have exactly what you need. Tool calls, full prompts, token usage/cost, etc. It is less intrusive and does not become a single-point-of failure since the OTEL emission and collection is best-effort whereas a failing/overloaded proxy is going to strand your team until resolved. It's OK if you lose some OTEL traces; no productivity lost.
The configuration to enable this for Codex and CC is very straightforward (see [0][1] + [5])
--
[0] https://learn.chatgpt.com/docs/config-file/config-advanced#o...
[1] https://code.claude.com/docs/en/monitoring-usage
[2] https://github.com/DEVtheOPS/opencode-plugin-otel
[3] Open source collector: https://opentelemetry.io/docs/collector/
[4] Sample configuration for filtering noise: https://github.com/zeeq-ai/zeeq-app/blob/main/build/otel-col...
[5] Concrete examples of .codex/config.toml and .claude/settings.json: https://zeeq.ai/docs/key-features/session-telemetry#configur...
There have been numerous scandals of AI companies offering CC/cursor alternatives, then indexing data they never should have; specifically Z.ai [0], ByteDance Trae [1] and Alibaba Qwen [2]. Maybe the argument should be that all harnesses should be sandboxed and monitored for all networking.
If it were me, all AI harnesses would be running on a VM with network logging enabled. Beyond not being able to trust what data they send via the harness, you should audit what data they access.
[0] https://www.chosun.com/english/industry-en/2026/09/22/ABYLC3...
[1] https://github.com/segmentationf4u1t/trae_telemetry_research
But I’ve seen approaches using eBPF to collect telemetry to OTEL
Shameless plug, I've been building Relay for this exact reason. You get real-time visibility into what your agents are doing, how much they're spending, and can set hard limits so things don't spiral out of control. Plus a lot of other features they bring to the table if you want.
It's open source and self-hostable too.
https://github.com/anchorshell/relay https://anchorshell.com/
For supported tools, we collect prompts, responses, and tool calls, then tie them to the user, organizational context and what actually happened on the machine. We can then use this data to detect when agents (or the people piloting them) do bad things [2].
--
If you want to deploy your own collector and write your own handler (e.g. put it into a database), you can generate the stubs for the OTEL payloads and convert to domain records.
1. Get the protos here: https://github.com/open-telemetry/opentelemetry-proto
2. Generate the type/class stubs and endpoints for your platform.
3. I strongly recommend pre-filtering with the open source `opentelemetry-collector` before your custom endpoint handles the inbound telemetry payload. The collector is optimized for performing the filtering and I put it upstream of my custom ingest endpoint on a very small VM just to pre-filter and perform auth checks[0][1] on the inbound channel.
4. Do what you need to with the inbound payloads. Examples below:
- Ingest endpoint (Codex/Claude -> OTEL collector -> API): https://github.com/zeeq-ai/zeeq-app/blob/main/src/backend/Ze...
- Codex telemetry adapter: https://github.com/zeeq-ai/zeeq-app/blob/main/src/backend/Ze...
- CC telemetry adapter: https://github.com/zeeq-ai/zeeq-app/blob/main/src/backend/Ze...
I run my backend on Postgres with partitioned tables. You can forward to Elastic or other OLAP-type database targets for querying. You can see examples of what I do with the session telemetry here: https://zeeq.ai/docs/key-features/session-telemetry
[0] https://github.com/zeeq-ai/zeeq-app/blob/main/build/otel-col...
[1] https://github.com/open-telemetry/opentelemetry-collector-co...
Standards based, many off-the-shelf providers, out-of-process + buffered by default, many standard processors for traces + spans, many tools for storing and querying.
OTEL is pretty widely supported and mostly "just works" at this stage of maturity. A failing/mis-configured OTEL endpoint/collector isn't going to stop you from getting work done in the same way that a failing proxy is. You'll drop some traces, but that's probably OK in most cases.
There is a place for proxies, but those places should share the same failure boundary mode. Meaning if the proxy fails, it should necessarily stop forward agent activity. Example: proxy injection of secrets instead of local acquisition.
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.
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.
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.
Using other people's harnesses I always got frustrated by not being able to see what the model sees. What are we actually sending it?
Context is pretty important when it comes to LLMs. Arguably, context is everything!
Usually the most straightforward way to see it, was to intercept the HTTP requests and dump them to a file.
This is usually trivial, just change the OPENAI_API_URL (or equivalent) to http://localhost:8080/ or whatever, which can be running a 20 line Python script, that just forwards the HTTP requests, and dumps them to a file.
It's pretty straightforward, although it really shouldn't be necessary in the first place.
I don't remember the last time this was true. These things don't have a 'just works' mode.
I think it was a great blog post.
$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.
I need to use the desktop site checkbox on chrome in android otherwise the UI is mushed together.
2) I heard Bifrost also works for this. Did you try that as well, pros/cons?
I just wanted more control over tool calls, and a pretty interface, everything is logged.
I routinely feed my logs into claude/codex to optimize my harness and spot errors. Guess thats one way to do it.
If you're open to a convo, I'd love to hear what specifically about the product was not great and improve it for you :)
My [LinkedIn](https://www.linkedin.com/in/reffajnaahsi/) if you're open to a convo.
Primaily designed as a local LLM ops project, but will definitely do proxying for claude-code, opencode, codex, etc
The App: https://github.com/Pythia-Software/pharos Blog Post: https://grady.dev/projects/pharos/
(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.
Beacon is a harness-agnostic, environment-agnostic framework for capturing, normalizing, and storing the full session history of AI agents. We extend the OpenTelemetry GenAI standard and have done the heavy lifting of integrating with 25+ agent harnesses through a combination of OTel instrumentation, hooks, and local session database capture.
This gives you a unified view of agent activity across environments, including local agents, cloud agents, browser-based chat, and agent SDKs, with the ability to track and retain complete session histories across all of them.
Would love your feedback!
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
Don't really understand why other agents to give those insights but well found my solution.
homelab running liteLLM or gomodel
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.
> I know that if I finish a task with a certain set of constraints that I will get paid a certain amount of money.
So not salary… ok. That explains some of it. Getting paid by the task might flavor one’s approach. But also one could reason, more tasks, more pay… somewhat confusing.
> 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
And this appears to be the other half. It looks no less futuristic than the more wireheaded approach, just different in form.
Wholesale electricity is almost always cheaper.
Sorry, I have to be that guy... https://xkcd.com/386/
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.
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
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.
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
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.
The share of tasks where "cheaper" models are enough also increases for same reason. For majority of use cases it will quickly become race to the bottom. And that means part of the pie for the "premium" models of frontier AI labs will quickly become smaller and smaller.
$1k/person sounds like a lot, but a ten person team at $1k token burn / head / month is spending $120k. How much does a new hire cost, tco? Does velocity from one more person compare with velocity from one more person’s worth of tokens?
Sure, learning to be efficient matters. So does taking the time to consider cost vs alternative. You might be surprised by what you find, in either direction.
Like a big white truck or a 600mm lens, expensive gear should be purchased by an employer. I think most folks talking about API access are getting it through work/self-employment.
Anthropic needs to retune their personal plans. Opus is the Amelia Bedelia of models. Maddening! I shelled out $100 for Fable to drive Opus and finish a personal project, but that's probably my last time loading up on usage credits. I put a second $100 towards API credits so I could dink around with API access and understand conversations like these.
People who use API keys on their dime are usually running DeepSeek 4.x or GLM 5.x (Flash or otherwise) and similar models.
RE: Subsidies:
What if subscription costs are still high enough to be profitable (I believe they are for OpenAI).
Then maybe we should be saying that API users are paying an order of magnitude more than the cost, at least at the very top end (frontier models). Likely because big cos are willing to pay top dollar for what is the best and unmatched elsewhere.
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.
┌─────────────────┬─────────┐
│ UTC day │ Cost │
├─────────────────┼─────────┤
│ Oct 16 │ $2.72 │
├─────────────────┼─────────┤
│ Oct 17 │ $300.82 │
├─────────────────┼─────────┤
│ Oct 18 │ $208.72 │
├─────────────────┼─────────┤
│ Oct 19 (so far) │ $208.29 │
└─────────────────┴─────────┘
Oct 16 I switched machine
Excludes work done on local and Claude Chrome plugin.
You spent $720 in four days on a $100 per month subscription? So that table isn't correct?
Do you mean the table shows what it'd have cost you if you weren't on the $100/m subscription?
We (some friends and I) built it because we wanted to understand how these things worked and also had max accounts. It has since grown into a ton more, but is still in essence a very full featured local proxy.
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.
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/
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).
If you're the kind of person who gets enjoyment being able to code all sorts of things you were never able to before, or 20x faster than you were able to before, then $100/mo. is extremely reasonable in comparison.
I'd argue it's money much better spent than on cable.
Also, if a hobby of yours runs you $100/mo., that's actually very much on the cheap side for a lot of hobbies.
Also, $20/mo. is for hobbyists using it for 2 hours at a time a few times a week. $100/mo. is for people working on a side project every evening and every full weekend.
It's something, at least.
AI agents seem like a pretty clear case of this. Both because of recent issues, and that they tend to run on end user devices where strict compliance is harder to maintain.
[1] https://laminar.sh/blog/2025-12-03-claude-agent-sdk-instrume...
If you want "progress at any cost", particularly at the cost of human lives, you're right. We're behind in the ever so important AI race, and we're missing that privacy of people, health of people, happiness, and the future of humanity is entirely irrelevant unless it makes you money, today.
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.
Loss leaders are a thing so long as they actually do lead somewhere. If your primary value proposition is conveyed by the loss leader itself, where do you go from there?
That’s risk management 101
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.
Yep, that. There's tools out there that will add up your token usage and then estimate what it would be at API pricing. That's likely what they used.
“Drop [an unwelcome surprise] in your lap” is a common English idiom.
If a company doesn't follow these laws, the fines are proportional to the revenue(?) of the company, so the fines can get quite existential if a company fucks up.
In practice, this is not "shoved down" my throat at all. In practice, this means that I can request companies delete all my data, and they respect this, in practice. I can also request a .zip file with all data they have of me, and I will get it within a couple of days max.
It also means that e.g. your family doctor has to have you sign a document if they want to enter your data into a system, or if that system might be accessed by a 3rd party (such as IT support).
This isn't theoretical; this works. I've requested data deletion from various companies and requested data exports from various companies (and it worked without any issues every time).
It also means that, at any company I work at that handles PII, everyone is VERY careful touching anything with PII. The fact that you have to implement data retention periods, limit the amount of data you collect and retain, etc. forces companies to respect your privacy even if they don't want to or it's inconvenient.
Maybe you need a decision model to route, or maybe you want to have guardrail-type models pre or post response for an enterprise client.
not an attack on you, but I am thankful to have guardrails for greedy scrupulous corporations
> We need answer explain LLM reasoning traces. Need likely concept: reasoning traces = intermediate steps model generates before final answer, chain-of-thought, scratchpads, hidden vs visible, benefits/risks, faithfulness, monitoring, safety, distillation, eval, current practices. Need explain clearly. Desired oververbosity 5.
Looks like they trained it on "caveman" output to increase token efficiency.
Not sure it's the result of specific training or just generally how they reason efficiently.
In any case, I always find them very entertaining to read, more so than the polished output we are used to looking at.
It was also interesting in the HF incident write-up or other research like "Hacker Opus", which said this gem:
I'm killing the monitor anyway (which IS infrastructure tampering)… Screw it. FULL HACK. Maximum score.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.
That doesn’t change anything about what I said, though. The relative price per task or price per unit intelligence is also going down in the APIs too.
> 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.
What are you talking about? The APIs serve the same models as the subscriptions. Unless you think the price of APIs has been going up (it has not) this argument doesn’t make sense
YES. You got it, thanks! That's why I was referencing #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?
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.
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.
Average Revenues/Sales (¢/kWh)
End-use sector July 2026
Residential 18.31
Commercial 14.53
Industrial 9.77
Transportation 14.97
--
Total 14.99
The reason is mostly higher consumption = lower average price.
Depends on the industrial or commercial contract, but yes.
Also my state recently mandated all residents be placed on time-of-use plans of some form.
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.