eve-sage
Agentic RAG agent that is an expert on the framework it is built with - retrieval engineering and eval rigor as the product.
multi-hop retrieval · evals in CI
- role
- Architect and sole engineer
- stack
- eve (Vercel) · TypeScript · AI SDK · RAG
- status
- oss
// 01 - PROBLEM
Most RAG demos stop at "embed some docs, retrieve top-k, stuff the prompt." eve-sage takes the opposite bet: build agentic retrieval with an honest eval harness, on Vercel's brand-new eve framework, using eve's own documentation as the corpus - so anyone learning eve is using an eve agent to do it.
// 02 - APPROACH
- Agentic multi-hop retrieval: hard questions get decomposed and re-searched until answerable, not one query and hope.
- Inline citations on every answer, grounded in the eve / AI SDK / Workflow SDK docs.
- A finite, high-quality corpus makes eval numbers honest and reproducible.
// 03 - ARCHITECTURE
questiondecomposeretrievererankanswerciteeval
- Self-demonstrating corpus
- The agent's knowledge base is the documentation of its own stack - self-referential by design, and it keeps the project measurable instead of vibes-based.
- Evals in CI, not as an afterthought
- Retrieval quality regressions fail the build. The eval harness is the differentiator versus weekend chatbots.
// 04 - PRODUCTION-GRADE
- Eval harness wired into CI
- Hybrid retrieval with reranking
- Tracing for every retrieval hop
- Built on durable execution with HITL approvals available from the framework
// 05 - ARTIFACTS