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Every dApp using AI today calls out to OpenAI or Anthropic. That single API call is a centralised control point. Somnia put LLM inference inside consensus instead, running it across validators. Here's the full conversation which paul.somi had with Ruthy | Surgence Labs 👇🏻

31,036 次观看 • 2 个月前 •via X (Twitter)

35 条评论

Somnia 的头像
Somnia2 个月前

@0xPaulThomas @ruthybuilds Great episode 🤝

Widow | collab manager 的头像
Widow | collab manager2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds @0xPaulThomas is Goated!!! Cant wait to see what @dreamDEXSomnia is brewing up

Jimidesuu (CM arc) 的头像
Jimidesuu (CM arc)2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds that was a great and insightful convo

amaci 的头像
amaci2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds thanks for this

Wisdom DD 的头像
Wisdom DD2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds somnia building in the ai sector is new to me but i’m curious

SAIF MR 🔺 的头像
SAIF MR 🔺2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Defly an interesting direction for decentralized AI

SkyGecko❄️ 的头像
SkyGecko❄️2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds This looks so fun and chill tbh

Kalamiro 的头像
Kalamiro2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Dope stuff

TMO 的头像
TMO2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Great episode

Arcane 的头像
Arcane2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Sugmi

Hendrix 的头像
Hendrix2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Ruthy cooking for us again

Leo💪🏼 的头像
Leo💪🏼2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds another amazing episode with an incredible project

PredatorX 的头像
PredatorX2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Fantastic episode

antone. 的头像
antone.2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds W ruthy

Lancaster.ETH 的头像
Lancaster.ETH2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Wow

Thomas 的头像
Thomas2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Great episode fr ✨

Ogi.eth 的头像
Ogi.eth2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Love to listen!

yellowpanther (prediction arc) 💎 的头像
yellowpanther (prediction arc) 💎2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds What a banger sheesh

𝖬ohit 🥤 的头像
𝖬ohit 🥤2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds That’s dope

Engage IO 的头像
Engage IO2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Running inference across validators introduces an interesting infrastructure model.

£M£S€N 的头像
£M£S€N2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds what an amazing episode

Donut 的头像
Donut2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Love this

Flow 〽️ 的头像
Flow 〽️2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds always a good watch when I see @0xPaulThomas on there! keen to find out what alpha is hiding at Somnia

Grace 的头像
Grace2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds really interesting direction for dApps

JPEGG 的头像
JPEGG2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds I

Dayo 的头像
Dayo2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Sugmi

InfinityGlock 的头像
InfinityGlock2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Foundoor connects

Rio👾 的头像
Rio👾2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds solid episode

⟠ KΞNNY ⟠ 的头像
⟠ KΞNNY ⟠2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds banger

Hamza 的头像
Hamza2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds 👀👀

Falcon21.eth 的头像
Falcon21.eth2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds ayeeeeeeeeeeeeee

Zito.btc 的头像
Zito.btc2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Real builders don’t stop

SARANG 的头像
SARANG2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds surgence cookin

Elys ✨ 的头像
Elys ✨2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Inference decentralization changes what dApps can build 🤖

Reinb 的头像
Reinb2 个月前

@Somnia_Network @0xPaulThomas @ruthybuilds Great conversation!

相关视频

Anthropic won't like this open-source repo. It is going to cost LLM providers a lot of money. Every CI run of an AI app today sends real requests to providers like OpenAI or Anthropic. Like any other LLM call, this too gets billed at actual API rates. So for teams with high commit volumes, this accumulates into a meaningful chunk of API spend. One common hack devs use is that instead of invoking the LLM API, the test calls a fake local server that speaks the same API and returns a dummy response. The catch is that the dummy response is a copy of what the provider returned on the day it was saved, and providers keep adding fields and changing types. So the tests keep passing against a schema that's no longer valid, while the real integration breaks in production. A smart approach is now actually implemented in CopilotKit🪁's recently open-sourced aimock project. Every day, the repo's own CI sends a handful of requests to the real API and the same requests to the fake server, then compares both against the official client library's type definitions. Those are the only real API calls in the whole setup, and they run on the repo's own keys, not in anyone else's CI. A single team can push hundreds of commits a day, and thousands of teams are already doing that with coding agents. All of those runs stay offline, because one repo checks against the real API on everyone's behalf. When a check fails, a coding agent updates aimock's built-in response schema, the full test suite has to pass, and a patch version ships to npm. By simply upgrading the package, the corrected schema gets reflected in every project using it. The capability is not just limited to a single provider. The same server works for Claude, OpenAI, Gemini, Bedrock, Azure, Ollama, plus MCP tools, A2A agents, AG-UI event streams, vector DBs like Pinecone and Qdrant, and search, speech, image, and video endpoints. Here's the repo: (don't forget to star it ⭐) That said, mocking your API calls is one thing. AI engineers should also know how to test agents properly in the first place, which several teams still skip. I wrote a full walkthrough on that, covering build, testing, evals, tracing, and deployment. Read it below.

Akshay 🚀

64,056 次观看 • 2 个月前