Even your straw man 20th century cut off is hilarious where you just kind of forget about 1873? Or maybe that decade is your shining example of the benefits of deflation. So much joy and global prosperity the peasants just forgot how to eat. Its cool, Bismarks destruction of the bimetallic system really helped usher in that age of stabikity from the international gold standards.

It did work like this! And it was! My recollection is that the first S3 was out of SEA and had no user concept of region. Then “VDC” was added in virginia. That provided API endpoints in what became us-east-1. A bucket could be accessed from either location, and the original intent was for object store to replicate between them. By the time dub/eu-west-1 came along that was obviously not tenable; itd take 10s of gbs to replicate.

So S3 became regional. But the original sea/vdc deployments still had shared APIs and data in both regions. Your object would be stored in the region of the API you geolocated to via DNS, but read from either. _eventually_ all the data migrated to IAD, but those API endpoints were transparently proxying across the continent until 2013 or so.

And of course glacier had much more interesting takes on this with cross dc/az/region erasure encoding. But i dont think any of the wacky multi dimensional cross region stuff ever materialised in practice.

PS: hi!

Welcome to the concept of fair market value. Less snarkily you're conflating the concepts of price and cost; theyre not the same thing and theyre not the same for you or the seller.

That said, even 3ms TPM signatures are going to be for special cases or novelty. Plain old CPU tls will do about 1ms cpu time per request which will scale by cpu core count. One or two orders of magnitude more throughput per host.

  - Write ~1 paragraph of developer instructions (AGENTS.md): Use subagents for tasks that can be decomposed, worked on in parallel, or delegated. Describe common examples. I put a reference to a "how to use subagents" skill for more details. The "skill" isnt' always read (as subagents arent always useful) which saves some tokens. But you pay the once-per-session read-skill cost when its relevant.
  - Describe how to use subagents in ~1 page or less (SKILLS.md): use them for sub tasks. select model size/quality based on task ambiguity, scope, unbounded work, or conflicting requirements. Use reasoning effort for complexity, interdependence, or ambiguous success criteria. How to evaluate complexity & common subtask examples across the spectrum. give tasks a relevant name like "model-family_version_reasoning-effort_task-description" so you can actually understand what theyre doing by name.
  - in dev instructions (SKILLS.md) provide a table of agent names (low complexity summarizer, bounded implementation, complex implementation), model+effort (gpt-5.6-luna medium, gpt-5.6-luna high, gpt-5.6-sol medium), and short description of 2-3 task "types" for each.
  - Explain they can use "default" or specify their own custom model settings if needed.
  - Define your list of subagent profiles in ~/.codex/agents/ which matches names (low_complexity_summarizer.toml) from previous. In each you'll need to set model, reasoning, and `developer_instructions` that describe *how* to do a task, *not what* to do.

  - IMO subgent profiles are "task centric" because `developer_instructions` are required. You can't just specify model & reasoning, you also have to give valid developer_instructions that will be merged in to every session/prompt. I address this by defining a few different agents for tasks that are commonly encounted like summarization, synthesis, planning, implementation, etc. The different agent profiles (~2-5 per category) will "scale" the model + reasoning based on the complexity and ambiguity. This work pretty well in practice. And you don't need to over due it, the harness/agent can still launch a "custom" profile that uses the parent sessions developer instructions.
  - You need to use agent profiles with codex because "v2" models (terra & sol) can't launch "v1" models (luna). There are a couple of code paths to avoid this, the agent profile is the simplest. 

Then the effective cost of scaling CPU > RAM > storage > network due to power & space limitations. Spending extra processing time on 50% of your content would be wasted effort as its never read again.

And yes, increasing effective storage might increase cache width/lifetime, but its not by that much to dramatically inprove access rates. Especially when most content by unique bytes is compressed audio/video in the first place.

I did see one prototype someone built using private ios APIs a few months back. They were able to run a reasonable SLM about an order of magnitude slower than GPU but with a tiny power draw.

PS: you might get tripped up on 0x00, 0x2F, or similar control characters? As i recall any valid octet can be included in a label. We definitely saw literal ‘*’ and ‘.’ inside labels. And I wouldnt be surprised to find a bell in there either.

Around 2010-11 there was a shift towards RESTish structures and json for serialization. A lot of methods and payloads still feel SOAPy, but look like json. I think it was DynamoDB which had the most unfortunate API with a literal xml-json transform live in the API service.

And then somewhere around 2015 you started seeing more well defined RESTish APIs with better tooling and adoption for smithy (and some openapi, iirc).

One of the interesting things I noticed here is that manufacturers are providing exchangers and head units that can reuse existing pipes. Makes sense for retrofit/upgrades where running pipes through utility spaces and bulkheads is a significant labor cost.

Installed prices in the US are pretty silly. Theres a bourgeoning set of DIY units that come precharged. But even those are pricey compared to the rest of the world.

Why and how would it be in the public or shareholder interest?

Im unaware if any public market where similar reductions in reporting led to significant, positive, outcomes. FTSE is the common example. They had a similar “reform” circa ‘14 and FTSE companies continue to generally under perform while the LSE continues to lose listings.

so zero exposure to any popular index? Even “ex-US” is tsmc and sk-hynix in a trenchcoat. I think it was BHP exclaiming that theyre an AI play because they cover 85% of the raw materials in DC build outs.

In the current mania “no financial stake in AI-related” is a very bold claim.