Jonathan Moore

investing @tcg_crypto

[Jonathan Moore @jonmoore202]

@sershokunin https://t.co/YTkB11v6II

[Dirichlet @0xdirichlet]

We're running into too many new customers than we know how to deal with - across multiple markets, languages, and cultural expectations.

So we're rethinking the entire customer lifecycle from first principles.

Looking for 0-1 operators from all backgrounds.
All that's required is the desire to think quantitatively, with a curious mind and collaborative spirit.

[Jonathan Moore @jonmoore202]

@Credib1eGuy Seven

[Jonathan Moore @jonmoore202]

this is exactly why dynamic pricing for inference feels inevitable

we all max out on tokens and <1% of us are using these models correctly

market structure for efficient inference allocation feels massively under-discussed

[Hedgie @HedgieMarkets]

🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an internal memo warning the company burned through its entire 2026 AI budget in just four months. American AI software prices have jumped 20% to 37%, and GitHub (owned by Microsoft) is dropping flat-rate plans for usage-based billing across its products.

My Take
The AI subsidy era is ending in real time. The same company that put $13 billion into OpenAI and built the Azure infrastructure powering most of Anthropic's compute just looked at the bill from a competitor's coding tool and decided it was not worth paying. That is not a productivity failure on Anthropic's end. Token-based pricing is forcing every enterprise customer to confront the actual cost of running these models at scale, and the number turns out to be far higher than the flat-rate experiments suggested.

This ties directly to my Gemini Flash post yesterday. Anthropic, OpenAI, and Google all raised effective prices in the last six months. Enterprises that built workflows assuming AI costs would keep falling are now watching annual budgets evaporate in months. Two outcomes look likely from here. Either enterprises scale back AI usage to fit budgets, which slows the revenue ramp the labs need to justify their valuations ahead of IPOs, or the labs cut prices and absorb the losses, which makes the unit economics worse at exactly the wrong moment. Both paths land in the same place, the numbers stop working, and somebody has to take the writedown.

Hedgie🤗

[Jonathan Moore @jonmoore202]

@degcap orbital compute shill at 22:40

https://t.co/KI9kKAimV9

[Jonathan Moore @jonmoore202]

@benroy 10/10 no notes 👏

[Jonathan Moore @jonmoore202]

@benroy

[Jonathan Moore @jonmoore202]

i think we'll see a resurgence in CPG

applied AI helps create better, personalized products that can command more attractive margins at lower CAC

improved unit economics will expand the surface area of interested VCs and capital who are priced out of AI at the app layer / concerned about constant disruption from foundational models

atoms and bits. not one or the other

[mungi @mungimungimungi]

https://t.co/VdQVi2lBcK

[Jonathan Moore @jonmoore202]

@luffistotle @benroy @0xsmac @derekedws Fine. If I must expose smac, so be it

[Jonathan Moore @jonmoore202]

birds by @nicedayJules

[Jonathan Moore @jonmoore202]

@nicedayJules

[Jonathan Moore @jonmoore202]

@kingbtc @sphere_labs

[Jonathan Moore @jonmoore202]

@RohanNayak2 @PocketFM_App 🔥

[Jonathan Moore @jonmoore202]

@0xdirichlet @solana @theodoroswhite @SolanaInstitute @sphere_labs year of @sphere

[Jonathan Moore @jonmoore202]

@nicedayJules happy birthday 👑

[Jonathan Moore @jonmoore202]

@MartinShkreli @sphere_labs

[Sphere Labs @sphere_labs]

From stablecoins in your favorite wallet to your bank account in a matter of minutes.

Off-ramping, as it should be. Only with Sphere.