The working vocabulary of Forward Deployed AI Engineering for founder-led B2B SaaS. Plain definitions of the role, the offer, the deliverables, and the tools, written the way they are actually used.
An engineer who embeds inside a customer's team and ships AI capabilities directly into the customer's product and codebase, rather than delivering a deck, a dashboard, or a demo. The delivery model comes from Palantir. In May 2026, OpenAI and Anthropic each launched a new company to do this work for their customers. See the full explainer: what is a Forward Deployed Engineer?
FDE as a service
Buying a forward deployed engineer's time or output from an outside provider instead of hiring one. Sold by model and platform vendors' deployment arms, consultancies, talent marketplaces, and independent engineers, usually by the hour or the month. See the FDE-as-a-service market map for 33 providers and their published prices.
Echo (Palantir)
At Palantir, the embedded analyst with deep domain expertise who owns the customer relationship, one half of its two-role FDE model. In Forward Deployed AI Engineering, Echo also names one half of the craft: the deployment that is working now.
Delta (Palantir)
At Palantir, the deployed engineer who ships code inside the customer's environment; the company describes the responsibilities as similar to a startup CTO's. In Forward Deployed AI Engineering, Delta also names the other half of the craft: the change that makes the next deployment work better.
FDE Sprint
A ten-business-day engagement in which an independent forward deployed engineer (FDE) ships one narrow AI workflow into a customer's product. Fixed scope, fixed price, end-to-end delivery and handoff. See the FDE Sprint.
Discovery Day
A two-hour paid working session, priced at $500, to assess whether an AI use case is useful, buildable, and worth a Sprint. The output is a go/no-go memo written on the call, credited toward a Sprint if the customer continues. See Discovery Day.
Workflow
A specific process a user runs, with a clear input and a clear output, that produces a measurable improvement. It is the unit of work shipped in a Sprint. Not a feature, and not a platform.
Output Quality Rubric
A practical checklist, usually on a 1-to-5 scale, that defines what good output from an AI workflow looks like, how the customer's team reviews it, and how the workflow improves over time. It ships as a deliverable with every Sprint.
Sprint Brief
The one-to-two-page document written on Day 1 of a Sprint and signed off by the customer's decision-maker, defining scope, success criteria, deliverables, and what is explicitly out of scope. It is part of the contract.
Workflow Playbook
A short handoff document covering a workflow's purpose, inputs, expected outputs, review steps, edge cases, and maintenance guidance, so the customer's team can run and improve it without the engineer.
Model Context Protocol (MCP)
The open standard Anthropic introduced for letting AI models talk to external systems and data. Many AI workflows connect to a customer's tools and data through MCP servers.
Claude Code
Anthropic's command-line tool for agentic coding. A primary delivery tool for shipping AI workflows directly into a codebase.
AI-native product
A product built around AI workflows from the start, rather than a traditional product with an AI feature added on later.
Vectig
Nasser Ghanemzadeh's AI-native startup finance product: cash-flow forecasting, runway scenarios, and investor update drafting. It serves as the live R&D lab where workflow patterns are proven before they ship to customers. See vectig.com.