The current economic landscape makes implementing AI in the B2B sphere challenging, and the most sought-after role in enterprises might be out of reach for SMBs.
Why SaaStr’s Own AI Solutions for Sales and GTM Succeed While Others Fail
Before discussing FDEs, let’s reflect on our insights. SaaStr’s AI SDR is the top performer with our outbound vendor. Our SaaStr.AI has assisted over 40,000 founders with their B2B queries. What makes our AI deliver results when many don’t?
We’ve trained them extensively — far beyond what 95% of SMBs will do. Continuous daily training is essential, not just initial set-up.
Can most small businesses manage this?
Most SMBs lack IT staff or additional technical resources. They operate lean, focus on core operations, and hope AI functions out of the box. At SaaStr, we act as our own forward deployed engineers. But this isn’t feasible for most SMBs.
The unspoken truth of AI success is that victorious companies win not just by purchasing superior tools but by making these tools work for their specific needs. This leads to the essential role in enterprise AI success, which SMBs might find economically unfeasible for now.
The TL;DR
Forward Deployed Engineers (FDEs) have become crucial for enterprise AI success, earning $135K-$200K+ salaries to embed with customers and turn AI promises into reality. FDEs guide and implement Gen AI strategies, taking a hands-on CTO-like role, with salaries ranging from $135,000 – $200,000/year. While FDEs are scaling AI deployments at many firms, the economics may not favor SMBs. Businesses needing AI transformation might not afford this effective model.
Even basic deployments can incur upfront costs of $25k+, $60k+ annually, with months of “forward deployed” efforts for training and deploying apps.
The Role of Forward Deployed Engineers (FDEs)
Dismiss what you think about solutions engineers or technical consultants. FDEs are vital in enterprise AI companies, differing fundamentally because:
FDEs don’t just implement — they build. FDEs collaborate closely with customers using the company’s products, assisting them in maximizing platform value. They’re coding in production, not merely configuring systems.
They embed with customers. FDEs work daily on Gen AI strategy and implementation alongside customers, addressing large-scale real-world issues.
They own outcomes, not features. Success is measured by customer business metrics, not just technical achievements.
They’re akin to “technical co-founders for AI projects,” as one Baseten FDE describes the role.
Economic Needs: Why Enterprise AI Requires FDEs
The hidden truth in enterprise AI? Enterprises desiring AI need someone to set it up, much like an iPhone for your grandma.
The market realizes: tools alone don’t change businesses. Investigation of leading AI products and technical documents shows their real differentiation lies in unique implementations across customer sets.
Key statistics reveal:
- 22 of OpenAI’s 311 open roles (7%) focus on forward deployment
- Companies achieve faster implementations, higher adoption, and productivity with embedded engineers
- Hands-on support enables young companies to secure large contracts, fostering growth more efficiently than lighter approaches
But a caveat: Individual deployments may yield poor margins, serving more as R&D than profit opportunities.
The SMB Dilemma: Where the Model Breaks Down
Now confronting the challenge: SMB AI training. If training AI is possible