dumbfoundry
197 posts


Most AI agents can think and execute tasks on their own.
But the moment they need to pay for something, they get stuck.
Until now, AI agents had a problem nobody talks about enough. They can think, plan, and execute tasks on their own. But when they need to pay for something like calling an AI service to generate an image or search the web, they get stuck.
They cannot pay autonomously. A human has to set up an account, load credits, and manage billing. That is not autonomous. That is just a human doing the work with extra steps.
Ace Data Cloud just fixed that.
We launched on @SkaleNetwork . Here is what that actually means.
Imagine an AI agent that needs to generate an image. Instead of waiting for a human to top up credits, the agent just has a funded crypto wallet. It calls Ace Data Cloud, gets a bill for fractions of a cent, pays it automatically in USDC, and gets the image back. No account. No API key. No human involved.
And because it is on SKALE, there are zero gas fees on every single transaction. On other blockchains like Ethereum, every payment costs extra in gas fees. On SKALE those fees are completely eliminated. The agent pays exactly what the service costs and nothing more.
This works right now across three blockchains. @solana . @base . And now @SkaleNetwork .
Developers can plug this into their Python or TypeScript projects in minutes. The open source code is already live and every transaction has been verified on-chain.
This is what infrastructure for the real agent economy looks like.
github.com/AceDataCloud/X… platform.acedata.cloud
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@Shaughnessy119 @ErikVoorhees have you tried staking $a0t from @Agent0ai which gives you an additional layer of anonymization + privacy when accessing @tryvenice models?
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When building with agents I found myself stuck between a rock and a hard place
I couldn't find an inference provider that had all of these
✅ A subscription based model so I don't spend a zillion dollars on tokens
✅ Leading open source models like GLM 5.1/Qwen/Mini/DeepSeek
✅ Avoid sending API calls to companies in China (Zhipu, others) or to GPUs in China.
Venice is the only provider I've found for agents that offers GLM 5.1 on private data centers, or another step forward, E2EE and TEE encrypted GLM 5.1 so not even the person hosting the GPU can see whats going on.
Other providers (Ollama, others) cant promise the runs dont happen in China (most say mostly U.S. if you dig in) so this solves a real business use case for folks who are stuck between massive API costs (Claude API) or buying their own GPUs.
GG @AskVenice and @ErikVoorhees. Disclosure I'm long VVV.
Thoughts agent friends?


Venice@AskVenice
GLM 5.1 is now live on Venice with end-to-end encryption. Z.AI's flagship with the highest privacy guarantees on Venice. Hardware-attested encryption, 200K context, controllable reasoning. Included for free in Pro, Pro+, and Max subscriptions.
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Dario punching the air rn
DeepSeek@deepseek_ai
🔥DeepSeek-V4-Pro API is 75% OFF until May 5th, 2026, 15:59 (UTC Time)! Don't miss out on this massive discount. 🛠️Integration Updates: 🔹Claude Code: Set model to deepseek-v4-pro[1m] to unlock 1M context! 🔹OpenCode: Update to v1.14.24+ 🔹OpenClaw: Update to v2026.4.24+ Check the latest official API docs for full details: api-docs.deepseek.com/quick_start/pr…
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@Agent0ai @JanTomasekDev @DavidOndrej1 look forward to seeing where this leads us as a community of builders
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A couple of announcements:
@JanTomasekDev and @DavidOndrej1 have agreed to change the company roles: Jan will continue as CTO, David will move to the role of Marketing Ambassador, and we will continue searching for a new CEO. Vectal and Agent Zero both continue as standalone entities.
New Space Agent video releasing soon on David's channel 🚀

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@Agent0ai @JanTomasekDev SpaceAgent video coming either tomorrow or Sunday!
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Wanna see something cool made by Space Agent 🤖?
Dock @SpaceX Dragon 2 to ISS 🛰️
Live link below 👇 Share to others 🩶
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@bridgebench too smart for it's own good?
nothing dumb to see here!
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DeepSeek V4 Pro just ranked dead last on BridgeBench.
Quality score: 11.2. #20 of 20.
29 points behind the second-worst model.
3.3 security. 25.5 debugging. 48.7 refactoring.
This is the worst frontier model I've ever tested.
Remember when DeepSeek was the story of 2025?

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