Own Your Agents

An AgentGraph Builder just shipped a demo using Coinbase Developer Platform🛡️’s AgentKit! Integrating agents with the blockchain unlocks brand-new agentic use cases: ✅ Seamless on-chain payments inside chat ✅ Agentic outbound payments (like refunds or perks) ✅ It’s fun!

Today Morpheus integrates with @Base as it rolls out its retail DEX integration, enabling tens of millions of users to purchase and trade thousands of @Base assets within moments of them going live – all within the Coinbase app. For more info, visit: coinbase.com/trade-crypto/d…

Morpheus Based

Looking forward to reading Principles of Building AI Agents by Sam Bhagwat The best way to Own Your Agents is to build them yourself! Sign up for a copy of the book here: mastra.ai/book

Request your Agent on AgentGraph

The chips and models have arrived. agents are the new apps. The shift from python to typescript demonstrates we are now very focused on building the next generation of apps (which are agents).

Agentic applications built by agentic coding methods will become the Agent Graph

AgentGraph invests R&D into enabling agent buyers to craft the perfect agent design specification. This enables AgentGraph Engineers to apply agentic coding and build high-quality agents at speed. This is also what FANG does to apply agentic coding to production systems.

AgentGraph docs just got a refresh ✨ Check it out here: docs.agentgraph.xyz/?utm_source=x

Agent building is a fundamentally new stack. Building traditional apps does not translate 1:1 to building agents. - context engineering - RAG (or not) - MCP (or not) - A2A (or not) Agents are the new apps - but building methods differ in many ways

Entrepreneurs across all verticals are continuing to explore how agentic AI can drive value. ✅ Content curation agents ✅ HIPPA compliant clinical trial agents ✅ Product onboarding agents With AgentGraph, these startups get to own, customize and grow their agents.

Spent today going through the Mastra course. Some cool aspects to it: Course is an MCP: The course itself is an MCP server! It guides you along in the IDE. Easy Framework: it teaches the core building blocks of an agent (system prompt, model access, tool access, memories,

AgentGraph Builders - Check out Bindu Reddy updated list.

Agents are the new apps, but the architecture is very different. If you need a custom agent, AgentGraph is where you go to find Agentic Product Engineers who understand context engineering.

After 3 years of capital deployment towards AI infrastructure, we are now ready to start building the agentic web. It will be multi-stack, multi-model, public, private, onchain, offchain, open and closed. The agentic web is much bigger than you think.

LIVE NOW: AI Agents can discover and trust each other without a central intermediary. This lays the foundation for open agent economies. ERC-8004 v1, co-authored with Davide Crapis (@Ethereumfndn), @Jordan0Ellis (Google) and - welcome Erik! - erik.eth 🛡 (@Coinbase) is now

Great post! Really like the term “Deep Agents” as a way to lean into the complexity of multi-agent systems. Just as microservices helped scale cloud-based infrastructure, multi-agent systems will scale the agentic web and address more complex use cases.

The next wave of software will be agentic. The meaning of "full stack" has shifted to include the AI stack. Models, tools, memory, RAG, agentic RAG. AgentGraph will be attending the first TypeScript AI conference (hosted by Mastra) on November 6th.

At AgentGraph we are excited to see agent interoperability standards, like x402, start to take shape. Several AgentGraph buyers are now submitting use cases that combine EIP-8004, MCP, and x402 to create a new class of agentic web-native custom agents.