# Last-mile deployment

> Last-mile deployment adapts a working product to a customer's real systems until the paid-for outcome lands - the gap Forward Deployed Engineers close.

URL: https://bartlomiejkrupa.dev/notes/last-mile-deployment/
Category: concept | Updated: 2026-07-26
Summary: Last-mile deployment adapts a working product to a customer's real systems until the paid-for outcome lands - the gap Forward Deployed Engineers close.

Last-mile deployment is adapting a working product to a customer's real systems until the outcome the customer paid for actually lands. Product engineering ships the capability; last-mile work keeps it alive after it hits the customer's environment. Field success needs a [verifiable completion condition](/notes/verifiable-completion-condition) and [LLM-as-a-judge](/notes/llm-as-a-judge) evals, not a demo that worked once.

## Why it exists

Customer environments rarely match the demo - fragmented data, legacy workflows, compliance constraints. Shipping the feature is not the same as the customer getting value.

## Who closes it

A [Forward Deployed Engineer](/articles/forward-deployed-engineer-last-mile) embeds on-site: builds, configures, and keeps it running. Without that embedding, implementations stall on blockers that never came up in discovery calls.

## Related

Measurable scoping before you build: [how to plan and scope a build with an LLM](/articles/plan-and-scope-a-build-with-an-llm). Field success needs evals, not vibes: [five metrics for an agent eval pipeline](/articles/five-metrics-for-an-agent-eval-pipeline).

Sources:
- Forward Deployed Engineer (FDE), San Francisco: https://openai.com/careers/forward-deployed-engineer-(fde)-sf-san-francisco/
- Inside OpenAI's Forward Deployed Engineer Role: https://newsletter.eng-leadership.com/p/inside-openais-forward-deployed-engineer