I'll agree but from the other direction. AI continues to absorb my job as a senior systems software engineer (c/c++) and after a couple months I've only spent a few hundred dollars using gpt-5.5/5.6 and codex. I have no idea what people are doing to burn so many tokens but for me this is laughably cheap and every day I discover new capabilities. I don't care if costs go up or down, it's so cheap for what I get that I don't care.
GLM 5.2 and the coming AI margin collapse
151–160 of 495 posts
Re: GLM 5.2 and the coming AI margin collapse
#152I'm not convinced raw costs matter: 1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins. 2. Many open source office suites exist yet none compete with the ubiquity of gsuite or office. GitHub, Slack are similar examples. 3. Both Windows and macOS dominate the home desktop space despite free alternatives existing for a long time. 4. Many formerly open source infrastructure…
There's a huge case of survivorship bias when trying to recall historical analogues, because in every instance where margins collapsed and competition made the industry a commodity business, the big proprietary names are no longer with us. Here's a selection of examples, though: 1. Memory chip margins collapsed so much in the 80s that Intel exited the memory chip business entirely. At the time, they were known much m…
There's a really noticeable difference in time frame covered in your examples (80s and 90s) and the one in the comment you're replying to (2010s and 2020s).
Is that just two people with different go-to examples? Or is there something going on here?
(I don't mean this as a leading question to some conclusion in my back pocket, I genuinely have no clue.)
Re: GLM 5.2 and the coming AI margin collapse
#153I'm not convinced raw costs matter: 1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins. 2. Many open source office suites exist yet none compete with the ubiquity of gsuite or office. GitHub, Slack are similar examples. 3. Both Windows and macOS dominate the home desktop space despite free alternatives existing for a long time. 4. Many formerly open source infrastructure…
All the more reason to focus on those service guarantees, integration, and lawyers while making the underlying model easily swappable to whoever’s winning the frontier model involution battle at the moment
Re: GLM 5.2 and the coming AI margin collapse
#154Earlier quoted context omitted.
If you're developing on top of LLM APIs directly, this is definitely not true. There are differences in how context caching works, in what's available through native harnesses, the types of tools you're fine-tuned on (GPT uses apply_patch while Claude uses edit, with different formats), the API surface (Agents SDK, Responses API, Managed Agents), cost structures, and best-practice guidance all around. Not to mention…
Exactly, as in, really, will they? Where and at what price, especially across an actual enterprise that needs to deploy them to lots of devs? There's much more than just the actual model. Of course my numbers are a sample of one and I am not spending a lot of money or time on it. Just lazily trying things on my "happen to have this" hardware. But basically trying out the Claude Code I'm used to from work but locally…
Open weights != local models.
Re: GLM 5.2 and the coming AI margin collapse
#155Earlier quoted context omitted.
Switching an agent harness is more difficult, especially on the enterprise/teams level. Once your team gets settled with Claude teams, cowork, and the various plugins, it’s going to be a pain in the butt to switch.
The irony is that Claude will help you migrate away from itself AI is possibly the first product in history that will eagerly help you replace it with one of its competitors.
Wait till they will pop a warning: “using Claude to migrate away will suspend your account. “
Or even better just silently sabotage the migration so you can’t do it. Something we can definitively expect from Claude given past behavior
Re: GLM 5.2 and the coming AI margin collapse
#156Earlier quoted context omitted.
I don’t exactly see orgs lining up to switch (and train) their employees between claude desktop and codex and whatever copilot is doing. There’s probably some inertia to those harnesses/integrations on top of the llms themselves.
The inertia is legal and financial. People are paying Anthropic through AWS accounts because the simple reason of not dealing making new contract and legal agreements is enough of reason of the inertia. But, eventually, I’m quite sure that AWS will also provide open models with those contracts without any inertia. Copilot is already offering Kimi. My company has a deal with Devin and they provide new models all the t…
Also they pay for legal liability of code produced
Re: GLM 5.2 and the coming AI margin collapse
#157Earlier quoted context omitted.
There's a huge case of survivorship bias when trying to recall historical analogues, because in every instance where margins collapsed and competition made the industry a commodity business, the big proprietary names are no longer with us. Here's a selection of examples, though: 1. Memory chip margins collapsed so much in the 80s that Intel exited the memory chip business entirely. At the time, they were known much m…
There's a really noticeable difference in time frame covered in your examples (80s and 90s) and the one in the comment you're replying to (2010s and 2020s). Is that just two people with different go-to examples? Or is there something going on here? (I don't mean this as a leading question to some conclusion in my back pocket, I genuinely have no clue.)
Somewhere else in the comments here, someone else remarked "Individuals perhaps [move to the new models], but not organizations."
That's illustrative. The mechanism by which organizations are forced to update their technology, move to more competitive suppliers, and cut costs is a recession. In one, every business that doesn't do so goes bankrupt, and what's left are the more efficient businesses that have adopted technology effectively.
We haven't had a real recession since 2009. (2020 was an odd case, because it was effectively brought on by government edict and so it actually killed a number of efficient but unlucky sectors while doing nothing to clean out the dead wood in major corporations). The next one is likely to be a doozy, because the economy is filled with bullshit jobs, bullshit corporations, and bullshit products.
Re: GLM 5.2 and the coming AI margin collapse
#158I'm not convinced raw costs matter: 1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins. 2. Many open source office suites exist yet none compete with the ubiquity of gsuite or office. GitHub, Slack are similar examples. 3. Both Windows and macOS dominate the home desktop space despite free alternatives existing for a long time. 4. Many formerly open source infrastructure…
There's a huge case of survivorship bias when trying to recall historical analogues, because in every instance where margins collapsed and competition made the industry a commodity business, the big proprietary names are no longer with us. Here's a selection of examples, though: 1. Memory chip margins collapsed so much in the 80s that Intel exited the memory chip business entirely. At the time, they were known much m…
Also cases where both happened, eg, Xerox wasn’t wiped out but copiers now have multiple vendors at the high end and have commodity via other brands at the low end.
Re: GLM 5.2 and the coming AI margin collapse
#159I think the fixation on numbers of tokens and dollars per token is missing the point a bit. LLMs are quite useless without good tools. The article calls out search as one of them. And it's important. If you are coding, the tools are relatively easy: they are mostly open source and don't have a lot of authorization logic around them. Anyone with access to python and some access to a half decent AI model can pull together a decent agentic coding tool. There are many examples out there.
But if you look at the overall market, there's a rapid shift happening to non-coding tools and non programmer users starting to become very active. This kicked off beginning of the year with Claude Cowork. OpenAIs Codex and ChatGPT (they both have the same plugin infrastructure) is doing a lot of the same things. I've talked to a lot of non technical business users in recent months. There's a growing amount of people who definitely have zero interest in programming starting to use these tools and getting value out of them. This is going to rapidly scale to essentially most white collar users. Programming tools are becoming a side show to this market.
The difference here is that these people need connections to all their favorite protected data SAAS silos: MS office, Sales Force, Outlook, Gmail & GSuite, Calendar, SAP, Oracle, etc. The moat here is very different: it's mediated access to these silos in a compliant way. Anthropic announced a solution in the form of some MCP features. Those features boil down to getting access to all your favorite silos, if you sign in with the right identity provider. What's the right identity provider? The one that's whitelisted by the data silos you are locked into. Okta seems to have weaseled themselves into a position of power here. And it's all the other usual suspects. We'll see who is going to "win" that race but I bet it's going to be a pretty exclusive club with zero outsiders from China on that list. You can hack your way around some of those limitations. But doing so in a compliant way is going to be tricky.
And that's before you consider who's going to pay for this and what they are going to insist on. Corporate IT departments & data security policy compliance basically. What's the moat here? Secure & compliant access to all your favorite silos. Here in the EU that also includes data residency. The difference between sending all your data to Silicon Valley or Beijing is that of getting stabbed or getting shot. If it leaves the EU, you have a huge compliance issue. Most of the juicy corporate LLM usage is going to have to be fully compliant. I.e. hosted and controlled in the EU. This will be the same across the world. The least important choice right now is which model you use. The most important ones are about where those models run and what tools the models running there have access to and how that is governed.
On paper, OpenAI, Anthropic, MS, and Google are pretty well positioned here. Not necessarily in that order. Most others are still figuring it out. But they'll have a moat of data center ownership in the right regions + mediated tool access that works out of the box.
Re: GLM 5.2 and the coming AI margin collapse
#160I'm not convinced raw costs matter: 1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins. 2. Many open source office suites exist yet none compete with the ubiquity of gsuite or office. GitHub, Slack are similar examples. 3. Both Windows and macOS dominate the home desktop space despite free alternatives existing for a long time. 4. Many formerly open source infrastructure…
> I understand the arguments for a margin collapse, but I don't see any historical analogues.
How is this the top comment? It lists all the outliers and ignores thousands of instances where fat margins caused a collapse.
I mean, just what Linux did to the dozen or so fat-margin unix server companies is already a longer list of collapsed companies than provided in this comment.