{AI} in Production is back.
Thursday, July 2nd at the Inngest office in San Francisco. I'm really excited to host this amazing group of speakers!
Four talks from teams running AI in production at scale:
🔧 @cursor_ai
🔐 @TryArcade
🎙️ @Vapi_AI
⚙️ @inngest
Whether you're in
Inngest
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Inngest is agent infrastructure that lives in your codebase. Write your logic as functions that automate retries, control flow, and unlock full observability.
- Replying to @inngestLet's say you wanted to score a response from an LLM call. If you're using a traditional queue, you know the context that produced that score evaporates unless you stand up a separate handler and pre-define and maintain a payload contract across two disconnected files.
- In our recent AI in production report, we asked how confident teams were in their app's ability to handle just 2-3x scale. The most confident teams had three things in common: 1. Durability—Use of a durable execution platform 2. Observability—Speed of diagnosing failures 3.




