← Saturday, October 3, 2026InferencePaper
AgSpec adapts retrieval-based speculative decoding to coding agents
AgSpec retrieves drafts from session, workspace and global corpora, then adapts draft length using verification feedback; it reports up to 4.37× throughput at batch size 1 and 4.76× at batch size 16. The results show how agent-specific context and acceptance behavior can improve inference speed.
- What
- AgSpec adapts retrieval-based speculative decoding to coding-agent pipelines with agent-specific corpora and draft-length policies.
- Method
- It retrieves from session, workspace, and global corpora; offline caps and verification feedback set draft lengths and adapt them online.
- Why it matters
- On two repository-level multi-agent coding benchmarks, it raises throughput over autoregressive decoding up to 4.37× at batch size 1 and 4.76× at batch size 16.
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