The FDE Deployment Revolution Goes Hyperscale Building on my earlier post about OpenAI and Anthropic launching dedicated Forward-Deployed Engineer initiatives, AWS has now taken a major step of its own. On June 30, AWS announced a $1 billion investment in a new Forward Deployed Engineering organization. The unit will seed thousands of engineers into small "pizza teams" — pods of roughly 5–6 people — who embed directly inside customer organizations to co-develop and deploy production AI systems, with a clear mandate to leave the customer self-sufficient when the engagement ends. This is more than an expansion of professional services. AWS is applying its long-standing "two-pizza team" philosophy — teams small enough to stay agile, autonomous, and fully accountable — to the challenge of enterprise AI deployment. The approach is explicitly "agentic-first," combining human expertise with purpose-built AI agents to compress timelines that traditionally took months into days or short sprints. What makes this significant is the pattern it completes. Palantir pioneered the Forward-Deployed Engineer model over a decade ago. OpenAI and Anthropic recently adapted it with dedicated, well-capitalized deployment entities. Now AWS — the largest cloud provider — is institutionalizing the model at hyperscale from within its core infrastructure business. The message for enterprise leaders is becoming hard to ignore. The primary bottleneck in AI adoption is no longer access to powerful models or abundant compute. It is contextual deployment — integrating these technologies into real workflows, governance frameworks, data environments, and organizational realities. The organizations that will create lasting advantage are those that effectively partner with these teams, internalize the knowledge being transferred, and build genuine internal capability rather than long-term dependency. Full article: https://kentkaufman.substack.com/p/the-fde-deployment-revolution-goes How are you thinking about preparing your teams to work alongside external embedded AI talent? What capabilities are you focusing on building internally?