The New FDE Model: How to Deploy with Scale in Legacy

About this episode

The episode discusses the forward deployed engineer model and its impact on product development and scaling AI-native companies.

This episode brings together a panel of AI-native founders building at the front lines of enterprise innovation: Aneka Sokhal (Moshi), Hunter Honnessy (Unlimited AI), and John Kalfayan (Collide). Moderated by Alex Gras of Mercury Fund, the conversation explores the rise of the “forward deployed engineer” model—embedding technical, domain experts directly with customers to accelerate product development and build trust. The panel shares how AI tools and agentic workflows are compressing timelines from months to days, reshaping how startups approach product, engineering, and customer collaboration. They also address the challenge of scale: how to turn fast-moving pilots into repeatable systems rather than a services-heavy business. It’s a practical, candid discussion on what it takes to build and scale AI-native companies today. 🎧 Episode Highlights ● [13:45]: Early mistakes deploying FDEs and why subject matter expertise matters ● [21:18]: Speed vs. quality: how AI tools shrink timelines from months to days ● [29:55]: Trust as the real currency for enterprise clients ● [36:21]: Scaling by turning pilots into repeatable templates and systems ● [55:32]: Why today’s AI is just the…

People in this episode

Host: Alex Gras

Guests: Aneka Sokhal, Hunter Honnessy, John Kalfayan

Topics covered

• AI-native companies
• forward deployed engineer model
• product development
• enterprise innovation
• scaling startups
• customer collaboration

Keywords

• AI tools
• product timelines
• enterprise clients
• scaling systems
• trust
• domain expertise

Mentioned in this episode

Organizations: Moshi, Unlimited AI, Collide, Mercury Fund

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