Apple will deploy the same security/ privacy / ease of use /packaging strategy they have done for every other product.
Same reason developers continue to use Apple payments even when they have to shell out 30% of the revenue.
I can see Apple, setting App store rules around declaring AI usage, or could start labeling apps not using their models with strong language designed to amplify the increasing user concerns around AI and so on.
The product strategy has to be better the product itself does not have to be objectively better for the developer for them to have to choose it.
Backrooms was a quite successful web series on YT which in turn originated in 4chan boards.
Only the medium being sourced from is changing from successful Broadway shows, popular novels or comic books in the years past. The calculus remains the same - properties with name recognition even from other formats tend to be green-light.
The web series and the film also defaulted to a very SCPified generic horror formula with conspiracy, "containment" and monster jumpscares.
But the original element that set backrooms/liminal spaces apart wasn't what was in them, but what wasn't. Sure it's creepy to be all alone, you may be afraid to get jumped, but you aren't. Some of the backrooms-inspired video games stay true to this concept.
So point is, the "Backrooms" film author may be an outsider, but he sticks to a very well-tried formula - one mainstream authors probably avoid for being too cliche more than anything.
Trust of a project long term always was and continues to be of concern when choosing a critical dependency .
The concern basically boils down to how large and serious is the team and what if they abandon the project in few weeks or months .
These were always the risks, many here have been burned by betting years of their career building against promising but what turned out to be weak projects
OP is alluding to the fact that today commit frequency, lines of code or how active the contributors in the issue trackers are no longer good signals to use as proxy.
When the underlying project to yours is few million lines of code written by machines only it is not going to be feasible fork and maintain or in-house it if the maintainers abandon it
To be clear users of a library or a tool aren’t owed anything when it available gratis and fully open source .
However not everyone has access to unlimited tokens to disregard the quality (in terms of history and usage ) or size of the underlying project completely
I think the primary value of a project like this is the demonstration that this is possible and a proof that it does not incur some unknown tradeoff you'll discover after spending resources doing it.
IMO the maintenance story is more or less solved if you can keep AI agents refactoring and improving it in a loop.
> However not everyone has access to unlimited tokens
Apologies. I did not consider this when writing my comment, being spoilt by unlimited 'free' AI.
Free in quotes because, presumably, training agents on AI usage from developers is worth more than the cost of providing free AI.
> IMO the maintenance story is more or less solved if you can keep AI agents refactoring and improving it in a loop.
That’s a weak argument, though, if the future of AI is totally unreliable when it comes to cost and quality. Right now I definitely wouldn’t want to depend on being able to infinitely access AI tools for such an important part of the toolchain.
Aside from that it’s just not attractive to trust a project made by one person.
> rather than the optimizations involved in rendering the text.
Any views they have on this topic is going to come across as quite opinionated given their choices for text rendering for this post and general aesthetics of website.
Naw, the truth is I'm not really smart or intelligent enough to build a semantic diff system. For that you'll need to wait on a post from one of our smarter devs, this was a post about rendering diffs in a browser.
Using the keyword “Workflow”like “Ultrathink” is problematic?
Ultrathink is uncommon enough that it is unlikely to be used in code or prompt outside its intended purpose.
Workflow is generic keyword and used in so many contexts both inside the codebase and orchestration tooling like say temporal.io or others that name their constructs “workflows”.
Everyone has critical risk on multiple parts of the supply chain. GPUs and Memory are just things OAI mitigated for.
Power - Bigger bottleneck than GPU or RAM perhaps, New Grid connected capacity is typically 10+ year timescale with lot of regulatory friction. Captive capacity is also quite constrained - now Gas turbines have 7+ year wait time.
There are plenty of hard constraints that OAI cannot easily solve either.
Comparing $/MTokfor models makes as much sense as comparing $/ghz for CPUs. Models have different tokenizers and take varying number of "thinking" to get to a solution. A far better proxy is how much it takes to do a run, which takes all of that into account. Such metrics are much harder to gather, but once source claims $3357 for gpt-5.5 vs $4686 for opus, the opposite of your conclusion.
There is no conclusion , I only stated the only objective fact to compare with that will not change for you to me.
Everything else is subjective to your setup, use case, configuration tuning and so forth.
More importantly bean-counters and decision makers at even 150+ seat orgs are looking at pricing sheets and enterprise contracts not how it performs for some team in a specific harness today to make million dollar annual contracts. It is not common for procurement teams to do commission the level of detailed analysis or large scale pilots that will actually hold for the duration of contract.
That doesn't mean that GPT-5.5 is selling less than Claude at all, just that cost is not the primary driver if list price is not cheaper, there is reason these are published in the same format by every vendor, because the common metric is how finance likes to compare with.
Most variants of GPT-5.5 are less chatty and token-intensive than Opus 4.8/4.7, so despite the output token price being higher, it generates fewer tokens, so the net cost is lower.
Per-token pricing is totally sensible from the provider-perspective on mapping COGS to revenue, but for a consumer, different models will produce more or less tokens, meaning the cost calculation is multi-dimensional.
You can configure model to be terse/concise with output style ? There are plenty of popular projects like https://github.com/JuliusBrussee/caveman which do it for you even.
Input/Cache/Output ratios are use case and configuration dependent . Any benefits in one model can usually be roughly to another with configuration tuning, and discussions devolve into subjective experience.
Pricing sheet is the objective way to compare cost.
>Airbus reported a commercial aircraft backlog of 9,031
> 10.4 years of production coverage
Kinda true, airlines and manufacturers like to do big order announcements/deals for their future needs of few years all upfront. If Airbus suddenly delivered all 9k aircraft most airlines simply cannot afford it, or take possession and use them even.
For example Indigo is Airbus only operator with a fleet of 450 today and has around 920 more Airbus aircraft (10% of the book) on order. Neither Indigo or Indian aviation sector( of which Indigo is 60%) can triple the capacity today . India need serious upgrades (Terminals, Runways, Gates, new airports) coming online and also demand maturing, i.e. more people can afford to fly for that kind of volume to make sense which even the best scenario will happen over the next decade.
For more mature/slow growing airlines it is function of existing fleet age and the optimal point each aircraft is retired/sold , doing it too early will make them unprofitable .
It is a less a backlog and more their next 10 years of committed sales.
P.S. There is whole other industry aspect around Buy-Sell-and-leaseback financial engineering that can drive order volumes a bit. The backlog/order book also have commodity futures aspects.
Same reason developers continue to use Apple payments even when they have to shell out 30% of the revenue.
I can see Apple, setting App store rules around declaring AI usage, or could start labeling apps not using their models with strong language designed to amplify the increasing user concerns around AI and so on.
The product strategy has to be better the product itself does not have to be objectively better for the developer for them to have to choose it.
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