Your strongest FDEs are carrying the hardest deployments back to back — and every new one starts from zero. Hiring can’t close a gap that compounds; heroics don’t renew. HALDEMAN builds the operating model that turns each deployment into the next one’s head start — so the program scales without burning the people who run it.
§ 01 · The evidence
The demand for FDEs has become a limiting factor on AI-Native platforms’ ability to scale. There are only so many experienced FDEs in the market — so serving client needs through heroics leads to stagnation.
Year-over-year growth in forward deployed engineer postings — the role went mainstream in two years.
Bloomberry · Revealera data · 2025
Enterprises predicted to abandon vendor-run agentic engagements by 2028 — scarce headcount they can’t sustain.
Gartner · via TechRepublic
Every platform and every consultancy answered the same way: hire. The market’s own numbers say that can’t scale.
§ 02 · The system
A Forward Deployed System is the operating model your program runs on. Every deployment still serves the client — and leaves two things behind: signal that sharpens the product, and reusable capability that makes the next deployment start ahead. Heroics reset to zero; the model compounds.
Palantir — the firm that pioneered forward deployment — shows the shape in its own filings: revenue grew 311% while headcount grew 82%. Output outran the org chart by nearly 4×.
The same pattern shows up across the AI-Native frontier — the programs that win make each deployment the next one’s starting point.
Palantir 10-K filings · revenue vs. headcount, 2020→2025
§ 03 · Two offerings
A productized engagement that installs the system, and a standing advisory relationship for the calls that set a transformation’s trajectory — two separate offerings, one operator behind both.
/ 01 · Forward Deployed Systems
Assess the program. Build the system. Scale the value.
Three pillars hold the system: pods built of four roles, a process that mandates a client outcome and a reusable artifact from every engagement, and FD/IO — the substrate where field learning lands and returns as capability.
/ 02 · Advisory
An operator across the table for the calls that set a transformation’s trajectory.
A standing advisory relationship for the leader driving an AI-Native transformation — at an enterprise or a platform. The operator across the table has made the call before, on all three sides: the client, the technologist, the consultant.
§ 04 · The pattern
While the market hires FDEs, HALDEMAN builds the system they work in. While the market deploys AI, HALDEMAN rewires the operating model around it.
Flat programs and compounding programs run the same roles, the same tools, the same talent. The difference is structural — a small set of levers most programs never find because everyone is staring at headcount. Finding them is the work, so the investment produces results. The full argument
Independent by structure: no delivery consortium, no platform to protect. HALDEMAN works with whoever the client’s system needs.
Not a pitch, not a deck — a working conversation about the wall your program is hitting and the pace it needs. You reach Cory directly, and you’ll hear back within a day. If a Forward Deployed System fits, the Maturity Map is the first move. If it doesn’t, the conversation will say so.