iksoor🧠

[iksoor🧠 @iksoor_]

@finnbags @BagsApp 0x8d60871aABdA3Dca22EBCB5e8fB060ed1c891FC9

[iksoor🧠 @iksoor_]

@BagsApp 0x8d60871aABdA3Dca22EBCB5e8fB060ed1c891FC9

[iksoor🧠 @iksoor_]

@Sambags12 0x8d60871aABdA3Dca22EBCB5e8fB060ed1c891FC9

[iksoor🧠 @iksoor_]

@finnbags @BagsApp 🤫

[iksoor🧠 @iksoor_]

@thinkingtree413

[Khouba @khouuba]

last thursday we opened the gates to the @primisprotocol beta by sending 150 invites to teams and individuals on our waitlist.

you can expect an in depth update tomorrow of how this week went with concrete numbers.

and the next step will be a full on open beta to everyone.

primis mode

[iksoor🧠 @iksoor_]

@khouuba @primisprotocol 👏

[iksoor🧠 @iksoor_]

@juny19441357 쏘니 있고없고 밑에서 풀어나가는거랑 속공때 차이 많이남 이기고싶음 꼭 있어야하는 선수. 누구나 당일 컨디션따라 기복있을수있음. 중요한건 쏘니가 글케 삽질했는데도 이겼다는거 만약 터지기 시작하면? ㅋㅋ

[iksoor🧠 @iksoor_]

@khouuba 🫡🫡🫡

[Khouba @khouuba]

we’re almost done. which means open beta is around the corner.

primis mode

[iksoor🧠 @iksoor_]

@khouuba @primisprotocol 🤫

[Khouba @khouuba]

we’re solving problem number 9 with @primisprotocol.

teams don’t just need compute. they need compute they can price, reserve, route, and reconcile.

the primitive is simple:

→ query rate → reserve rate
→ attach workload → reconcile usage

not another cloud. not another GPU marketplace.

the pricing layer for compute.

primis mode.

[iksoor🧠 @iksoor_]

@khouuba 👏

[Khouba @khouuba]

been a little quiet, not because nothing is happening but the opposite.

first the market has been moving exactly where we thought it would: gpu availability tightening, prices repricing overnight, compute futures appearing and builders realizing “access” is not enough.

the missing layer is becoming obvious. and that’s what we’ve been building with @primisprotocol.

our closed beta that has been running for months is already processing ~$100k/monthly. and allowed us to understand what needed to improve for scale. which is what we’ve been working on.

all this, to say open beta has never been closer as we estimate we’re 1 big sprint away from opening the gates.

primis mode

[iksoor🧠 @iksoor_]

@khouuba 🫡

[Khouba @khouuba]

when a few actors control hardware, memory, cloud capacity, and frontier APIs, builders get squeezed from both sides:
hardware becomes unaffordable,
API pricing rises,
and the market loses optionality.

open models and cheaper inference are the counter-force.

but the real unlock is the layer that can route across all of it:
frontier apis,
open models,
cloud gpus,
local / edge inference,
alternative providers.

that’s the @primisprotocol thesis.

not one model.
not one cloud.
not one hardware stack.

pricing + routing across fragmented compute so builders can access the best economics for each workload.

primis mode

[iksoor🧠 @iksoor_]

@khouuba @primisprotocol 👏

[Khouba @khouuba]

this is very aligned with the @primisprotocol thesis.

teams are moving from “use the best model everywhere” to “optimize cost per useful output.”

that requires more than cheaper apis.

it requires routing, pricing, reservation, and one layer that helps builders match each workload to the right compute economics.

tokenmaxxing → compute costmaxxing.

[iksoor🧠 @iksoor_]

@chillypnl 👏

[Chilly @chillypnl]

The end of AI inference subsidies marks a critical inflection point for the industry.

Major labs and enterprises are confronting sharp cost realities:
Microsoft cancelling Claude licenses, Uber exhausting its 2026 AI budget within months, anticipated 15-30x price increases from Anthropic, and GPT-5.5 already trading at 3x prior rates. At the same time, agentic workflows are amplifying demand a single user request can trigger hundreds of model calls, where even high per-step accuracy compounds into unacceptable failure rates at scale.

This environment underscores a fundamental challenge: sustainable economics for AI infrastructure.
While solutions like SERV advance the reasoning, verification, and orchestration layer delivering substantial gains in performance-per-dollar and production reliability the underlying compute procurement remains fragmented, opaque, and volatile.

@primisprotocol addresses this gap as the dedicated pricing layer for compute.
Primis aggregates and normalizes GPU and inference supply across providers into a single, confidence-scored rate feed.

Teams can:
• Query real-time normalized pricing with explicit confidence intervals

• Reserve capacity with enforceable validity windows

• Attach pricing directly to workload identifiers

• Forecast and track spend within existing orchestration pipelines

By removing reliance on manual spreadsheets, stale quotes, and regional volatility, Primis delivers the price predictability required for production-scale inference and agent deployments.
In an era of exponential compute demand, the difference between pilot and production increasingly hinges on cost certainty and operational predictability. Primis provides the economic infrastructure that complements architectural advances like SERV enabling builders to scale reliably without exposure to sudden pricing shocks.

The AI compute stack is maturing. Those who secure both performance optimization and economic visibility will define the next phase of adoption.
Primis is live on Solana, with open beta access expanding. The foundation for autonomous AI economics.
Curious to see what teams are building atop predictable compute rails.