How Forward Deployed Engineering is done at Ramp — Leo Mehr
Ramp pairs strict request scoping with agents across the delivery pipeline. Its intake agent reportedly saves about 20% of scoping time, while humans retain final judgment.
Ramp’s FDE organization grew from **2 to about 30 engineers**. A Notion-based intake agent now questions requesters until it can draft a spec, cutting reply latency from hours or days to seconds and reportedly saving about **20% of scoping time**.
Builders should validate urgency, users, workarounds, platforms, and reuse before generating code. Then automate the pipeline in stages—from context gathering and scoping through specs and implementation—with evals, rubrics, and human review at each boundary.
Ramp’s FDE organization grew from **2 to about 30 engineers**. A Notion-based intake agent now questions requesters until it can draft a spec, cutting reply latency from hours or days to seconds and reportedly saving about **20% of scoping time**. Builders should validate urgency, users, workarounds, platforms, and reuse before generating code. Then automate the pipeline in stages—from context gathering and scoping through specs and implementation—with evals, rubrics, and human review at each boundary. Ramp says the middle of that pipeline remains difficult, especially transferring tacit product knowledge into agents. The 20% figure is an estimate, and faster intake can amplify poorly scoped work if judgment is removed.
This turns process-first agent engineering into a staged operating model: interrogate demand, formalize a spec, then automate implementation behind evaluated human-review boundaries. The reported intake gain confirms value at the context-gathering edge, while the unresolved transfer of tacit product knowledge narrows expectations for end-to-end automation and identifies the middle of the workflow as the real bottleneck.