> […]
> Put another way, LLM companies are trying to climb the ladder to be a platform, I have zero interest in that, I was a "dumb pipe", I want a commodity, I want a provider, not a platform.
That is my sentiment precisely, and a big reason why I’ve started moving away from Claude Code in the past few weeks when I realised how much of my workflow was becoming tied to their specific tools.
Claude Code’s "Memory" feature was the tipping point for me, with the model committing feedbacks and learnings to some local, provider-specific path, that won’t persist in the git repo itself.
That’s fine for user preferences, not for workflows, rules, etc.
And the latest ToS changes about not being allowed to even use another CLI made up my mind. At work we were experimenting with an autonomous debug agent using the Claude Code cli programmatically in ephemeral VMs. Now it just returns an error saying we can’t use subscriptions with third-party software… when there is no third-party software involved?
Anyway, so long Claude.
I also clearly see the lock-in/moat strategy playing out here, and I don't like it. It's classic SV tactics. I've been burned too many times to let it happen again if I can help it.
Woz has been saying this for decades, we went from buying a computer and owning it to being trapped inside someone else's platform. MCP being open was a good sign but I'm watching how tightly Routines gets coupled to their stack.
To the contrary, they've proven again and again and again they'll absolutely do that the first chance they get.
For example, this demo (https://github.com/barnum-circus/barnum/tree/master/demos/co...) converts a folder of files from JS to TS. It's something an LLM could (probably) do a decent job of, but 1. not necessarily reliably, and 2. you can write a much more complicated workflow (e.g. retry logic, timeout logic, adding additional checks like "don't use as casts", etc), 3. you can be much more token efficient, and 4. you can be LLM agnostic.
So, IMO, in the presence of tools like that, you shouldn't bother using /loop, code routines, etc.
I see people making similar conclusions about various LLM providers. I suspect in the end it’ll shake out about the same way, the providers will become practically inoperable with each other either due to inconvenience, cost, or whatever. So I’ve not wasted much of my time thinking about it.
What grinds my gears is how Anthropic is actively avoiding standards. Like being the only harness that doesn't read AGENTS.md. I work on AI infra and use different models all the time, Opus is really good, but the competition is very close. There's just enough friction to testing those out though, and that's the point.
My point was, I don't think it mattered much, and it feels like an ok comparison - cloud offerings are mostly the exact same things, at least at their core, but the ecosystem around them is the moat, and how expensive it is to migrate off of them. I would not be surprised at all if frontier AI model providers go much the same way. I'm pretty much there already with how much I prefer claude code CLI, even if half the time I'm using it as a harness for OpenAI calls.
Claude Code routines sounds useful, but at the same time, under AI-codepocalypse, my guess is it would take an afternoon to have codex reimplement it using some existing freemium SaaS Cron platform, assuming I didn't want to roll my own (because of the maintenance overhead vs paying someone else to deal with that).
It's just portability v convenience. But unlike ~15 years ago with cloud compute, it _feels_ like more people are skeptical of convenience, which is interesting.
I guess I'm one of the people who disagree, specifically about AWS. I think a lot of companies just watch their bill go up because they don't have the appetite to unwind their previous decision to go all-in on AWS.
Ignoring egress fees, migrating storage and compute isn't hard, it's all the auxiliary stuff that's locked in, the IAM, Cognito, CloudFormation, EventBridge, etc... Good luck digging out of that hole. That's not to say that AWS doesn't work well, but unless you have a light footprint and avoided most of their extra services, the lock-in feels pretty real.
That's what it feels like Anthropic is doing here. You could have a cron job under your control, or you could outsource that to a Claude Routine. At some point the outsourced provider has so many hooks into your operations that it's too painful to extract yourself, so you just keep the status quo, even if there's pain.
your experience just hasn’t been my experience I guess. The more managed the service you use, the more costs you are going to pay - for a very long time I’ve got by with paying for compute, network, and storage on the barebones services. If you want to pay for convenience you will pay for it.
One area that was a little shitty that has changed a lot is egress costs, but we mostly have shifted to engineering around it. I’ve never minded all that much, and AWS support is so good at enterprise tiers that they’ll literally help you do it.
> I’ve got by with paying for compute, network, and storage on the barebones services.
Yes, as I mentioned, that type of migration isn't difficult, which is akin to migrating to a different model provider, but that's not what we're discussing. You can't hand wave the issue away if you're not even talking about the the topic at hand.
That said, I agree with your suspicions of how it'll shake out in the end, because most businesses behave the same way, and always try and lock-in their customers.
not the op, but I suspect they were meaning it's a huge pain migrating to a different cloud provider when all those features mentioned are in use. not that managing them is a mess in AWS.
However if I only expect to have a handful of (lucrative) users, it's not the worst idea. The other reason to use Cognito is that AWS handles all the user login issues, and costs very few lines of code to use on my end. The fatal security issue is getting hacked, either the platform as a whole, eg S3 bucket with bad perms or user login getting leaked and reused. While obviously no system is unhackable, the gamble is if a homegrown system is more impervious than Cognito (or someone else's eg Supabase). With a large development team where the login system and overall system security isn't going to be an afterthought, I wouldn't think about using Cognito, but where both of those things are an afterthought, I'd at least consider Cognito, or some other managed system.
The ultimate problem with Cognito though is the vendor lock in. (Last I checked, which was years ago) in order to migrate users out, they have to reset their password which would cause users to bounce off your service instead of renewing their subscription.
Yes, I expect that is very much the point here. A bunch of product guys got on a whiteboard and said, okay the thing is in wide use but the main moat is that our competitors are even more distrusted in the market than we are; other than that it's completely undifferentiated and can be swapped out in a heartbeat for multiple other offerings. How do we do we persuade our investors we have a locked in customer base that won't just up-stakes in favour of other options or just running open source models themselves?
Too bad we've now managed to turn programming into the same annoying guesswork.
We can quibble as to how much that is or is not "programming", but on a post about Claude code, what's relevant is that's how things are today. How much code review is done after the AI agent stops churning is relevant to the question of code quality out the other end, but to the question at hand, "has programming changed", either has, or what I'm doing is no longer programming. The semantics are less interesting to me, the point is, when I sit down at my computer to make code happen so I can deliver software to customers, the very nature of what I do has changed.
I actually trust that they will.
1) that AI will be more advanced in the future
2) that the AI I am using will be worse in the future
# Note: This is inefficient, but deterministic and predictable. Previous
attempts at improvements led to hard-to-predict bugs and were
scrapped. TODO improve this function when AI gets better
* make sure the model maxes out all benchmarks
* release it
* after some time, nerf it
* repeat the same with the next model
However, the net sum is positive: in general, models from 2026 are better than those from 2024.
Not just that, but there’s really no way to come to an objective consensus of how well the model is performing in the first place. See: literally every thread discussing a Claude outage or change of some kind. “Opus is absolutely incredible, it’s one shotting work that would take me months” immediately followed by “no it’s totally nerfed now, it can’t even implement bubble sort for me.”
Funny: I’m literally, at this very moment, working on a way to monitor that across users. Wasn’t the initial goal, but it should do that nicely as well ^^
Suuuuuuure it was.
That said, I had way better experiences with old (but contemporary) Apple hardware than any other kind of old hardware.
Sometimes you have to keep starting new session until it works. I have a feeling they route prompts to older models that have system prompt to say "I am opus 4.6", but really it's something older and more basic. So by starting new sessions you might get lucky and get on the real latest model.
I never asked for a 1M context window, then I got it and it was nice, now it's as if it was gone again .. no biggie but if they had advertised it as a free-trial (which it feels like) I wouldn't have opted in.
Anyways, seems I'm just ranting, I still like Claude, yes but nonetheless it still feels like the game you described above.
https://x.com/lydiahallie/status/2039800718371307603
--- start quote ---
Digging into reports, most of the fastest burn came down to a few token-heavy patterns. Some tips:
• Sonnet 4.6 is the better default on Pro. Opus burns roughly twice as fast. Switch at session start.
• Lower the effort level or turn off extended thinking when you don't need deep reasoning. Switch at session start.
• Start fresh instead of resuming large sessions that have been idle ~1h
• Cap your context window, long sessions cost more CLAUDE_CODE_AUTO_COMPACT_WINDOW=200000
--- end quote ---
https://x.com/bcherny/status/2043163965648515234
--- start quote ---
We defaulted to medium [reasoning] as a result of user feedback about Claude using too many tokens. When we made the change, we (1) included it in the changelog and (2) showed a dialog when you opened Claude Code so you could choose to opt out. Literally nothing sneaky about it — this was us addressing user feedback in an obvious and explicit way.
--- end quote ---
but you can replicate these yourself! i'm happy that ant/oai are experimenting to find pmf for "llm for dev-tools". After they figure out the proper stickyness, (or if they go away or nerf or raise prices, etc) you can always take the off-ramp and implement your own llm/agent using the existing open-source models. The cost of building dev-tools is near zero. it is not like codegen where you need the frontier performance.
Chinese models (GLM, MiniMax) are better.
It changes a number of things. Not all tasks require very high intelligence, but a lot of data may be sensitive enough to avoid sharing it with a third party.
Anthropic wants a moat, but that ship has sailed. Now all I keep reading about is: token burn, downtime and... Wait for it, another new product!
Anthropic thinks they are pulling one over on the enterprise, and maybe they are with annual lock-in akin to Microsoft. But I really hope enterprise buyers are not this gullible, after all these years. At least with Microsoft the product used to be tangible. Now it's... Well, non-deterministic and it's clear providers will gimp models at will.
I had a Pro Max account only for a short period of time and during that short stint Anthropic changed their tune on how I could use that product, I hit limits on a Max account within hours with one CC agent, and experienced multiple outages! But don't worry, Anthropic gave me $200 in credits for OpenClaw. Give me a break.
The current state of LLM providers is the cloud amplified 100x over and in all the worst ways. I had hopes for Anthropic to be the least shitty but it's very clear they've embraced enshittification through and through.
Now I'm spending time looking at how to minimize agent and LLM use with deterministic automation being the foundation with LLM use only where need be and implemented in simple and cost controllable ways.
I can’t use Claude Code at all anymore, not even for simple tasks. The output genuinely disgusts me. Like a friend who constantly stabs you in the back.
My favorite AI feature at the moment is the JetBrains predict next edit. It‘s so fast that I don’t lose attention and I’m still fully under control.
I'm currently hosting, on very reasonable consumer grade hardware, an LLM that is on par performance wise what every anyone was paying for about a year ago. Including all the layers in between the model and the user.
Llama.cpp serves up Gemma-4-26B-A4B, Open WebUI handles the client details: system prompt, web search, image gen, file uploading etc. With Conduit and Tailscale providing the last layer so I can have a mobile experience as robust as anything I get from Anthropic, plus I know how all the pieces works and can upgrade, enhance, etc to my hearts delight. All this runs from a pretty standard MBP at > 70 tokens/sec.
If you want to better understand the agent side of things, look into Hermes agent and you can start understanding the internals of how all this stuff is done. You can run a very competitive coding agent using modest hardware and open models. In a similar note, image/video gen on local hardware has come a long way.
Just like Linux, you're going to exchanging time for this level of control, but it's something anyone who takes LLMs seriously and has the same concerns can easily get started with.
Yet I still see comments like this that seem to complete ignore the incredible work in the open model community that has been perpetually improving and is starting to really be competitive. If you relax the "local" requirement and just want more performance from an LLM backend you can replace the llama.cpp part with a call to Kimi 2.5 or Minimax 2.7 (which you could feasibly run at home, not kimi though). You can still control all the additional part of the experience but run models that are very competitive with current proprietary SoTA offering, 100% under your control still and a fraction of the price.
Nothing insurmontable or even complex; just laborious. Friction. That’s all it takes to lock users in.
This isn’t an LLM. It’s a product powered by an LLM. You don’t get access to the model you get access to the product.
An LLM can’t do a web search, an LLM can’t convert Excel files into something and then into PDF. Products do that.
I think it’s a mistake to say I don’t trust this engine to get me here, rather than it is to say I don’t trust this car. Because for the most part, the engine, despite giving you a different performance all the time is roughly doing the same thing over and over.
The product is the curious entity you have no control over.
The funniest thing Ive heard is that now we have LLMs, Humanoid robots are on the horizon. Like wtf? People who jump to these conclusions were never deep thinkers in the first place. And thats OK, its good to signal that. So we know who to avoid.
Increasingly, we're also seeing the moat shrink somewhat. Frontier models are converging in performance (and I bet even Mythos will get matched) and harnesses are improving too across the board (OpenCode and Codex for example).
I get why they're trying to do that (a perception of a moat bloats the IPO price) but I have little faith there's any real moat at all (especially as competitors are still flush with cash).
So yeah, doesn't bode well for being a pure play model producer.