I've been using Agentkit + Inngest to build out an agentic customer support network for the past week and the experience so far has been wonderful.
I've been evaluating n8n and Mastra.ai at the same time to determine the best platform for my use-cases and Agentkit + Inngest has been the clear winner IMO.
The fact that Agentkit is able to leverage Inngest's durable workflow execution engine is awesome as it makes the interaction with the agentic network waaaayy more reliable.
How's the performance compared to LangGraph? I'm working on a project that needs to handle high throughput agent interactions.
Great stuff. Would be neat to have an adapter make the output stream match the ai-sdk format so it plugs in to existing UX (https://sdk.vercel.ai/docs/ai-sdk-ui/stream-protocol)
Interesting, have you considered adding benchmarks comparing AgentKit to other frameworks? Would help teams evaluating options
This looks really good. I'm going to take a detailed look at this for sure. Thanks!
Really love the decoupling of the logic and the runtime for the actual tool calls.
That is great! How does debugging work with the local DevServer?
good stuff
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AgentKit and Inngest are awesome. Thank you @tonyhb and the Inngest team for building such an amazing DX.
I've been testing Inngest realtime with AgentKit and it's an awesome combo already despite being a few weeks old.
I highly recommend the Inngest demo checking out their SWE bench example and the E2B example (https://github.com/inngest/agent-kit/tree/main/examples/e2b-...) to build a network of coding agents. I've also got this working with Daytona sandboxes.
Some feedback: - Would love an llms.txt for your docs like https://developers.cloudflare.com/agents/llms-full.txt - clear way of accessing realtime publishing from within AgentKit.