ciji

[ciji @cijicooks]

@chillypnl @khouuba @primisprotocol Primis looks good here

[Chilly @chillypnl]

When sentiment is sour and most people are waiting for the next narrative, the best builders are already 18–24+ months deep into solving real problems.

@khouuba and the @primisprotocol team have been quietly building the pricing layer for compute for over two years creating the infrastructure that will power the next wave of AI agents and decentralized compute.

No hype cycles. Just consistent execution on one of the hardest problems at the intersection of Solana, DePIN, and AI.

This is exactly what Ansem is talking about.

The work happens in the dark. The recognition comes later.

Proud to watch it unfold.

[ciji @cijicooks]

@chillypnl I’m bullish in primis

[Chilly @chillypnl]

As frontier models advance, real capability is increasingly driven by test-time compute tokens, dollars, and inference budgets not just pre-training.

This shift makes transparent, reliable, and normalized compute pricing more essential than ever for labs, builders, and safety teams running long-horizon agents and high-stakes evals.

That’s precisely why i am excited about @primisprotocol: the pricing layer for AI compute. Primis abstracts fragmented GPU supply into confidence-scored, reserved rates that teams can integrate directly into workflows turning volatile inference costs into something predictable, efficient, and scalable.

In a world where performance curves matter more than single-number benchmarks, infrastructure like Primis becomes foundational.

Strong validation for the inference-era stack.

[ciji @cijicooks]

@chillypnl Primis mode

[Chilly @chillypnl]

This is exactly why the economics of AI are shifting so fast and why intelligent compute pricing is becoming table stakes.

Open models + massive inference volume = exploding demand for predictable, optimized GPU economics.

Builders need reliable pricing, reservation, and cost governance without the chaos of fragmented supply.

That’s the mission @primisprotocol is solving: the pricing layer for AI compute.

Making high-performance inference both accessible and economically sustainable.

[ciji @cijicooks]

@chillypnl @primisprotocol Primis mode

[Chilly @chillypnl]

Sam Altman calling AI budgeting a “huge issue” that “never came up” earlier this year validates what AI builders have been feeling: compute pricing is fragmented, volatile, and impossible to forecast reliably.

This is why primis exists.

@primisprotocol is the pricing layer for AI compute. They normalize supply across providers into clear, confidence-scored rates teams can reserve, apply, and track before workloads even run.

No more surprise bills. No more spot-market roulette. Just predictable, budgetable compute.

The era of unchecked spending is shifting toward efficiency. Primis was built for exactly this moment.

[ciji @cijicooks]

@chillypnl @khouuba @MarketBubble @Banks @blknoiz06 Can you make it happen @Banks ?

[ciji @cijicooks]

@chillypnl @primisprotocol Bullish af on primis

[Chilly @chillypnl]

This is exactly why infrastructure abstraction layers like @primisprotocol are becoming essential.

While power constraints, 4-year transformer lead times, and LNG dependency are throttling traditional AI data center expansion, Primis is building the unified pricing and reservation layer that brings transparency, reliability, and efficiency to fragmented compute supply.

In a world of extreme scarcity and volatility, Primis turns opaque, unreliable GPU access into standardized,
confidence-scored capacity that AI teams can actually plan around and book.

The harder the physical infrastructure bottlenecks get, the stronger the need for Primis’s protocol. Smart positioning in the AI compute stack.
Well aligned with the future of decentralized and hybrid compute markets.

[Chilly @chillypnl]

I believe the crypto market has already established its cycle low in the current bear market, potentially followed by one final liquidity sweep ahead of the SPCX IPO.

To illustrate, in the previous bear market, we saw an initial bottom on June 18, only for the FTX collapse to drive prices to a lower low on November 21. Absent any major unforeseen shocks this year, I view the recent lows as the definitive cycle bottom.

This conviction is further reinforced by the prevailing market sentiment: widespread bearishness and a broad consensus that the ultimate bottom will arrive in Q4.

Historically, when the majority of participants are uniformly pessimistic and positioned for further downside, it often signals a contrarian opportunity to turn bullish. Extreme uniformity in bearish expectations tends to coincide with market inflection points.

[ciji @cijicooks]

@chillypnl @WhiteWhaleLabs do you agree with this?

[ciji @cijicooks]

I saved around $20K of my AI company compute costs

All i did was using @primisprotocol has my compute provider

[Chilly @chillypnl]

Greg Osuri is right the GPU crisis is about to get exponentially worse.

As AI agents move from 2.4 million to 24 million users, demand for scarce H100 class compute will surge far beyond today’s already strained supply.

This is exactly why @primisprotocol exists.
In a world of fragmented supply, opaque bilateral deals, and volatile pricing, Primis is the neutral pricing layer for AI compute. We abstract away the chaos and deliver standardized, confidence-scored rates that teams can query, reserve, and lock in directly without owning the hardware.

Compute is the new oil. The winners won’t be those who own the rigs.
They’ll be the ones who can price and access it most efficiently.

Primis makes that possible.

[ciji @cijicooks]

@chillypnl @insentos @primisprotocol primis mode

[Chilly @chillypnl]

The @insentos post is spot-on and it maps directly to @primisprotocol’s core thesis.

As the AI supercycle shifts from infrastructure hype and model experimentation into the efficiency wave (Wave 3), the real alpha moves to technologies that make AI operationally cheaper, more predictable, and scalable for real-world builders.

Compute remains one of the largest and most fragmented cost centers in AI. Pricing is volatile, opaque, and spread across dozens of providers with inconsistent dashboards, stale quotes, and regional variances. Teams waste cycles comparing spreadsheets instead of shipping workloads.

Primis Protocol is the pricing layer for compute.

• It normalizes fragmented supply into clear, confidence-scored, reservable rates.

• Builders can query once, lock a rate with an expiry window, attach it to a workload ID, and track actual usage against the quoted price.

• Not a cloud provider. Not another GPU marketplace. The abstraction layer that turns compute chaos into a usable primitive inside existing workflows.

In Camillo’s efficiency wave, winners won’t just have access to more compute they’ll have better economics on the compute they use. Primis delivers exactly that: predictability, transparency, and efficiency at the pricing layer so AI teams can focus on building rather than negotiating rates.

This is infrastructure for the phase where AI stops being a cost center and starts driving sustainable margins.

[ciji @cijicooks]

@tryAlphaLine @Polymarket Send it

[ciji @cijicooks]

@mako_hera214 Who gifted you? 😂😂😂

[つきみやしき @tsukimi_yashiki]

ジャムチーズトーストなメタモン

[まこと＆ヘラクロス @mako_hera214]

TS