Coinbase Developer Platform🛡️ @CoinbaseDev
Trusted crypto infrastructure to power your business. We offer a broad suite of products across payments, trading, wallets, and stablecoins. cdp.coinbase.com Worldwide Joined March 2021-
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@that_john_doe @bot If you do, please drop the prompt.
It's the battle of the Groks. @bot took the lead as Coinbase for Agents hit another ATH in weekly trading volume last week. Grok Bot - 38% Grok - 37.5% Custom CLI - 9.7% Claude - 6.4% Claude Code - 4.3% ChatGPT - 2.8% Perplexity - 1.2% Codex - 0.06% Muse - 0.06% Supertake - 0.05% Notional volume from ChatGPT traders nearly quadrupled week over week.
Why are we building new payment rails at @coinbase? Because AI agents need them to transact instantaneously for data, APIs, and compute. I discussed the future with @Finextra at Sibos: finextra.com/videoarticle/3…
To get started with agentic trading: → Find Coinbase as an official connector on @grok, @bot or @perplexity_ai Computer or → Paste this prompt on your favorite platform: "Connect to coinbase.com/skill.md"
@Cointelegraph Yes x.com/CoinbaseDev/st…
As we showed in part 1 of our Owning Intelligence series, contextual LLMs can strengthen an existing risk stack. But which model should power the agent? Will upgrading to a frontier model improve its decisions? The short answer is no. More in the thread ↓
@mattyp Our agentic traders are going to love this.
@Key_Crypto_AU @grok @bot @perplexity_ai Yes. It should work with ChatGPT and Codex. You can see connection guides for each platform here: docs.cdp.coinbase.com/ai-agents/coin…
Connect your Coinbase account to @grok, @bot or @perplexity_ai Computer, or paste this on your AI platform of choice: "Connect to coinbase.com/skill.md" Legal stuff: Informational only; not investment advice or recommendation. Trading involves risk of total loss. AI agents may fail. You direct all AI activity and assume full responsibility for your agent's trades and any third-party data use.
What are people trading with Coinbase for Agents this week? The top 3 assets by notional trading volume from 10/05 to 10/12: 🥇 $BTC 🥈 $LINK 🥉 $STRK Coinbase for Agents is now natively available on Grok, Grok Bot, Perplexity Computer, and via MCP on other AI platforms.
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case). I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves. We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them: "/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started" I imagine we'll have some backend services that could be replaced entirely by this new architecture.
This @CoinbaseDev intern project reduced onramp fraud by 30% and beat Opus/Sonnet/GPT at the task. Protects our customers, and ended up saving us a bunch of money. Shoutout to Xuwei Tan, and his mentor Yao Ma, for shipping this!
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case). I think we'll see more of this pattern inside
There is AGI pilled assumption out there as frontier model upgrades it will perform better at whatever long tail enterprise tasks out there. Well this is NOT true based on our analysis. Sometimes newer model performs worse (and by a lot!) If labs get access to your private data, the story would have been different. So enterprise needs to protect their data like protecting their life!
As we showed in part 1 of our Owning Intelligence series, contextual LLMs can strengthen an existing risk stack. But which model should power the agent? Will upgrading to a frontier model improve its decisions? The short answer is no. More in the thread ↓
@finkd just get muse to trade for you instead: "Connect Coinbase using Coinbase.com/skill.md"
Since newer =/= better on our fraud benchmark, we moved our Onramp risk agent toward open-weight models and domain-specific post-training. Read Part 2 of Owning Intelligence ↓ coinbase.com/blog/part-two-… In Part 3 we'll cover post-training Qwen3.5-9B and comared to Opus 4.5.
How should you evaluate a risk agent? These 3 questions can guide you to the most suitable model: → Does the candidate improve the overall trade-off? → Is the comparison between models or between policies? → Can it meet the latency, reliability, and cost requirements?
As we showed in part 1 of our Owning Intelligence series, contextual LLMs can strengthen an existing risk stack. But which model should power the agent? Will upgrading to a frontier model improve its decisions? The short answer is no. More in the thread ↓
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