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Home » AI’s Shift to Forward Deployment Engineering Signals a New Enterprise Skillset
Cloud Wars Minute

AI’s Shift to Forward Deployment Engineering Signals a New Enterprise Skillset

Dewain RobinsonBy Dewain RobinsonAugust 13, 2026Updated:August 13, 20262 Mins Read
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Welcome to the Cloud Wars AI Minute — your AI news and commentary show. Each episode provides insights and perspectives on the AI revolution, exploring the technologies, companies, and leaders transforming business and reshaping the future.

In today’s Cloud Wars AI Minute, I break down the rapid rise of forward deployment engineering and why getting AI into production is becoming the next competitive advantage.

Highlights

00:10 — Today, the topic is going to be why we’re seeing AI move to forward deployment engineering type of scenarios, and this industry trend has actually increased in just year-over-year growth of forward deployment engineering job postings in just the first half of 2026, increasing by 1,000%.

01:29 — You actually have to get to deployment, and the big problem there is that between 88 to 95% of all AI pilots that are being built today are actually never actually getting to production. So we have a whole lot of interest in the market and a lot of stuff that’s being really cool and is being done, but we’re not actually seeing it get to production. Hence the need for FDE, or forward deployment engineers.

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02:04 — Two, you actually have embedded engineers to go help a client to be able to get up and get going. And just to give you guys a typical situation here, now we’re starting to see a lot of the pay for these type of roles. They’re getting very, very valuable in this market space.

03:04 — So this is a major, major shift in what we’re seeing, and it’s also why even in DCI and our training offering, I’m looking at building out how to be able to move toward an FDE-type approach engagement, specifically for partners, because you’re gonna really have to think about how you move to AI being able to get about 99% code coverage in order to be able to play in this space and be able to have fixed-fee, high-quality implementations that actually drive into production implementations.


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