Retrieval Abstraction Layer Build (Onboarding)

Retrieval Abstraction Layer Build (Onboarding)

1. 01

   Inventory every client deliverable that returns a source-cited answer

   List the workflows (policy Q&A, contract review, RFP drafting, support deflection) where a wrong citation reaches the client. Rank by retainer value so the abstraction work starts where a retrieval failure costs the most.

2. 02

   Define one internal retrieval contract before any vendor is chosen

   Specify the request shape (query, filters, top-k, recency window) and the response shape (chunks, scores, source URI, page or timestamp). Every provider adapter must satisfy this contract so downstream prompt logic never imports a vendor SDK directly.

3. 03

   Write the golden question set from real client documents

   Pull 40 to 60 questions per engagement from actual support tickets, prior deliverables, and client FAQs, each paired with the passage that should be retrieved. This set is the only thing that decides whether a provider stays.

4. 04

   Wire two providers behind the contract on day one

   A managed context engine such as Ragie handles parsing, entity extraction, and multimodal ingestion; a web data API such as Context.dev covers pages the client does not own. Running both from the start makes the swap path real rather than theoretical.

5. 05

   Instrument retrieval separately from generation

   Log per-query latency, token spend, and which chunks were returned. Per-run tracing tools like telemetry.dev expose cost and error data at span level, which is what lets an agency attribute a bad answer to retrieval rather than to the model.

6. 06

   Attach a verification pass to any answer that leaves the building

   A layer such as CiteLLM links each claim to the highlighted passage in the source PDF, so a delivery lead can spot-check before a client sees it. Verification is a delivery control, not a nice-to-have.

7. 07

   Record the baseline scores and the pricing terms in the engagement file

   Store recall@k, citation accuracy, and per-1,000-query cost for each provider. Without a written baseline, the next quarterly review becomes an argument about impressions.