AWS has set up a dedicated AWS Forward Deployed Engineering (FDE) organisation, backed by a $1-billion investment.
The AWS FDE model is agentic-first, compresses timelines from months to days, and is designed so customers are self-sufficient when a deployment ends
Jonathan Allen, AWS executive in residence, explains that AWS FDE embeds AWS frontier teams, working with purpose-built agents, inside customer teams.
“These experienced engineers, many of whom build our AWS AI services, partner with a customer’s business, engineering, and security teams to build and deploy production AI systems with their data, governance, and processes.
“Unlike traditional consulting that assesses, recommends, and treats each deployment as a standalone project, AWS FDE builds for the long term.
“Customers leave AWS FDE deployments with both new solutions and new engineering capabilities. Along with agentic systems running in their own AWS environment, they gain lasting AI skills, workflows, and patterns they can use to innovate independently. Deployments are structured around shared goals and business results, not billable hours.”
AWS FDE uses agentic deployment technology and the AI-Driven Development Lifecycle – a new approach to software development that emphasises AI-powered execution with human oversight and dynamic team collaboration. Each customer project compounds intelligence for their next.
AWS Partners will contribute model expertise, industry knowledge, and complementary skills to ensure the right engineers are available to customers.
“We are investing in partner training, tools, and resources to accelerate AWS FDE engagements,” Allen says.
Self-sufficiency
AWS FDE engagements are designed to make customers self-sufficient: as projects advance, customer engineers move from observers to co-builders and then to autonomous operators.
Customers gain deployed systems, knowledge graphs, runbooks, architectural documentation and trained internal champions ready to operate independently.
FDE teams deploy into the customer’s own AWS account. It connects to enterprise data sources, enriches metadata, and uses AI to publish a governed, versioned knowledge graph. Agents reason over that knowledge graph, so domain expertise lives in the customer’s code, not in institutional knowledge that could rotate off.
In addition, security is built in from the start, including hardware-based isolation, end-to