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Datacean

01

The AI was fine. The Forward Deployed Engineer was missing.

An FDE is the engineer who turns an AI model into business value.

Your pilot did not stall because your team was weak or your model was wrong. It stalled because nobody in the building held that job.

Get your AI readiness score →2 minutes.
Forward deployed engineering listings, indexedListings for the role are up 729%, indexed at 829 against a baseline of 100. Top posted salaries reach $785k.
FDE listings, indexed on 2024829 · +729%
Top posted salaries$785k
Engineers who can name the jobalmost none
Miguel Fierro, LinkedIn

02

This is measured, not anecdotal.

RAND · 2024>80% of AI projects fail — twice the failure rate of non-AI IT projects.

>80%

of AI projects fail — twice the failure rate of non-AI IT projects.

RAND · 2024

Gartner · 2024~30% of GenAI projects were forecast to be abandoned after proof of concept by the end of 2025.

~30%

of GenAI projects were forecast to be abandoned after proof of concept by the end of 2025.

Gartner · 2024

MIT NANDA · 202595% of enterprise GenAI pilots show no P&L impact, self-reported.

95%

of enterprise GenAI pilots show no P&L impact, self-reported.

The five in a hundred that report P&L impact.

MIT NANDA · 2025

Over the same window, the models got dramatically better. So whatever kills these projects, it is not model quality.

03

The demo was never the hard part. Going to production is.

What a demo has to satisfy, and what production has to satisfyClean samples. Dirty data from systems nobody has cleaned in a decade. Nothing to integrate. Legacy ERP and the internal systems around it. No permissions. Row-level permissions and your IAM. No review. Security review, vendor review, change control. No SLA. Uptime, on-call and someone to page at 03:00.A demo1 conditionProduction6 of 6 conditionsThe feature worksThe feature worksDirty datacan reject on its ownLegacy systemscan reject on its ownPermissions and IAMcan reject on its ownSecurity reviewcan reject on its ownUptime and on-callcan reject on its own

A demo has to be true once, on a laptop, for five minutes. Production has to be true every day, and any one of those five can stop it on its own — which is why the gap between them is a job rather than a sprint.

Five things break between a demo and production. In most companies, nobody’s job description contains any of them.

04 — The role

The gap has a job title now.

An FDE is the engineer who turns an AI model into business value.

One drawing in four states: the three disciplines a forward deployed engineer holds at onceThe same schematic becomes an AI engineer's pipeline, a business developer's value chart against target, a product manager's delivery plan, and finally all three wired into one system — which is the forward deployed engineer.

All three, wired together

One person holding all three at once. That is the whole definition, and it is why the role is scarce: each discipline is common on its own, and almost nobody carries the three into the same room.

One drawing, four states. Nothing is added between them — the same strokes rearrange, which is what holding three disciplines actually looks like.

05

How we can help.

For enterprises whose AI is stuck between pilot and production

We ship it with you.

A forward deployed engineer inside your environment, accountable for a production outcome on your stack.

See the 90-day engagement

For leaders training a team, and engineers wanting to become an FDE

We train your people to ship it.

Your engineers can be taught this — it is a craft, not a talent. The same work, taught hands-on, by the person who does it.

See the training tracks

06

Five things break between a demo and production. Which one is killing yours?

Get your AI readiness score in two minutes. A straight diagnosis of what is actually blocking you, and the one next step that matches it.

Get your AI readiness score →2 minutes. Your score on the spot, and the plan by email.