Hi, I’m Vivek Gupta, Founder & CEO at MemCode. Trigger.dev provides durable, long-running AI workflows with retries, queues, checkpointing, human-in-the-loop steps, realtime updates, and observability. That makes it a natural execution layer for agents, while MemCode can provide the semantic memory that remains useful across runs and deployments.
Would Trigger.dev consider a MemCode reference integration for durable chat agents? A first example could recall scoped memory when a run starts, write approved decisions after a run, persist memory job status alongside task metadata, and define failure/retry behavior without blocking the agent when memory is unavailable. This could live as an example/package rather than a core dependency.
This is a technical integration proposal; any partnership or optional 10% revenue-share discussion can be handled separately through the appropriate channel. I’d be happy to open an example PR or short RFC showing the TypeScript integration.
Hi, I’m Vivek Gupta, Founder & CEO at MemCode. Trigger.dev provides durable, long-running AI workflows with retries, queues, checkpointing, human-in-the-loop steps, realtime updates, and observability. That makes it a natural execution layer for agents, while MemCode can provide the semantic memory that remains useful across runs and deployments.
Would Trigger.dev consider a MemCode reference integration for durable chat agents? A first example could recall scoped memory when a run starts, write approved decisions after a run, persist memory job status alongside task metadata, and define failure/retry behavior without blocking the agent when memory is unavailable. This could live as an example/package rather than a core dependency.
This is a technical integration proposal; any partnership or optional 10% revenue-share discussion can be handled separately through the appropriate channel. I’d be happy to open an example PR or short RFC showing the TypeScript integration.