Key features
Core capabilities each platform advertises.
Data not available
- Agent hosting & deployment
- Sandboxed compute
- Scheduling
- Message streaming
- Long-running agent support
Updated March 27, 2026
DSPy is a framework from Stanford for programming—not prompting—foundation models. It replaces manual prompt engineering with composable, optimizable modules. DSPy compilers automatically tune prompts and weights for your specific pipeline and dataset, enabling more reliable LLM applications.
Vercel for background agents — hosting and deployment platform for long-running AI agents with sandboxed compute, scheduling, and message streaming.
Core capabilities each platform advertises.
What each tool does well, and the limitations to keep in mind.
Pros
Cons
Pros
Cons
Choose DSPy if you wantChoose if you want
Choose Terminal Use if you wantChoose if you want
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.
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