I sat down with Michael Levan, AI Architect and FDE at Solo, to unpack the role from discovery through production.
We talk about why modern FDEs need to be technical generalists, how to uncover the real problem behind a customer’s feature request, when an FDE should influence product rather than build the feature themselves, and why AI security, sandboxing and observability are becoming major enterprise concerns.
We also get into a less technical, but arguably more important part of the job: earning enough trust that customers want your opinion before they make the architecture decision.
In this episode:
What an FDE actually does
Pre-sales vs. post-sales vs. full-cycle FDEs
Turning customer requests into product signals
How to perform deeper technical discovery
AI gateways, governance and agent sandboxing
Designing customer-specific demos
Using AI coding tools without losing technical depth
Why customer trust is an FDE’s most valuable asset
How engineers can prepare for FDE roles
Companion article: The FDE Is the Harness
