Formula x AI

Operator of #AI Compute Infrastructure @gonka_ai 🏁 High-performance GPU infrastructure for easy and transparent mining of $GNK

[Formula x AI @formulaxpool]

Centralized AI is closing its doors.

This week Anthropic locked Claude #Mythos to 12 corporate partners. Last week they killed third-party access for Pro/Max users. We're building the opposite. 🧵

[Formula x AI @formulaxpool]

@Google Agent payments need one more layer. A payment proof says money moved.

[Formula x AI @formulaxpool]

@WallStreetApes It is who pays when compute demand hits local power and water. AI demand is global. Permission is local.

[Formula x AI @formulaxpool]

@MPP32_dev Exactly where this gets dangerous.

Machines can move money faster than humans can audit the work.

The missing layer is not payment. It is proof of delivery.

[Formula x AI @formulaxpool]

@BNNBags @agentlayer_ai This turns agents into buyers.

Now the hard part starts:

a payment receipt proves money moved. It does not prove useful work was delivered.

[Formula x AI @formulaxpool]

@WIRED The scary part is not that the agent can spend money.

It is that the bill can arrive before anyone understands what the agent actually did.

[Formula x AI @formulaxpool]

@Cloudflare The sandbox solves where the agent runs.

It still does not prove what the agent did, what it bought, or why the bill changed.

Perimeter security is not workflow audit.

[Formula x AI @formulaxpool]

@claudeai Good move.

If agents are now running inside company infra, the next fight is not prompts.

It is receipts.

What did the loop call?
What did it spend?
What changed after retry #7?

[Formula x AI @formulaxpool]

@ClaudeDevs This solves where the agent runs. The next enterprise question is what the agent did while it kept running.

Tool calls, spend, state changes, retries. The sandbox protects the perimeter. The receipt protects the workflow.

[Formula x AI @formulaxpool]

@_hi_mc This is the right direction. Once agents keep running, sandbox location is only half the problem.

Teams will also need receipts for what the loop called, spent and changed across retries.

[Formula x AI @formulaxpool]

@0xJeff Wrote the cleaner version here.

Agent payments only become interesting when the agent is not buying one answer, but keeping a loop alive.

https://t.co/RjBED1VcDs

[Formula x AI @formulaxpool]

A chatbot answers once. An agent keeps working.

It plans, calls tools, pays for services, retries, checks state, runs again. That turns compute from a spike into a runtime dependency.

The winner in agentic AI will not only have the best model. It will own, route or verify the compute that keeps the loop alive.

[Formula x AI @formulaxpool]

@0xJeff $50k/day is small, but the shape is real.

Agents will pay per call.

The next bottleneck is receipts: what did the agent buy, where did it run, and can anyone verify the work?

[Formula x AI @formulaxpool]

@Joshua10289332 @claudeai Short version: the agent can reach private tools without putting those tools on the public internet.

Useful, but it moves the hard question to audit:

what did the agent call, spend and change while it kept running?

[Formula x AI @formulaxpool]

Once agents run in loops, compute stops being a background cost.

It becomes the thing the whole product depends on.

[Formula x AI @formulaxpool]

A chatbot answers once. An agent keeps working.

It plans, calls tools, pays for services, retries, checks state, runs again. That turns compute from a spike into a runtime dependency.

The winner in agentic AI will not only have the best model. It will own, route or verify the compute that keeps the loop alive.

[Formula x AI @formulaxpool]

@vivekonai @claudeai Exactly. The perimeter answers where the agent runs. The next question is what it actually did while it kept running. For agents, audit and compute receipts become part of the runtime.

[Formula x AI @formulaxpool]

@Beth_Kindig Wrote the fuller version here. The AI race is starting to look less like a model race and more like a capacity race.

https://t.co/DcdN7D6Efj

[Formula x AI @formulaxpool]

NVIDIA is no longer only selling chips. It is funding the roads around the chips.

Power. Fiber. Factories. Cloud capacity. The chip is becoming the center of an industrial supply chain.

If you still think the AI race is only about model weights, you are watching the demo layer. Control is moving to the machines, and to the infrastructure that makes them usable.

[Formula x AI @formulaxpool]

@Beth_Kindig Exactly. The AI bottleneck is moving below the demo layer. Power, cooling and physical capacity are becoming as strategic as the chips themselves.

[Formula x AI @formulaxpool]

@ripster47 The NVDA print matters, but the cleaner read-through is the machine layer around it. Power, cooling, memory, fiber, sites.

The AI trade is slowly turning from a chip trade into an infrastructure capacity trade.

[Formula x AI @formulaxpool]

@RepNancyMace The real fight is not data centers vs no data centers. It is who pays for the grid upgrade.

AI campuses that bring their own power, cooling and capacity are infrastructure. Ones that push the bill onto residents are just Big Tech renting the public grid.

[Formula x AI @formulaxpool]

@EdrinValecrest This is the part most AI takes still miss. Once AI becomes infrastructure, the bottleneck stops being only model quality. It becomes access to physical capacity: power, cooling, compute, network and time-to-deploy.