What is Forward Deployed?
“[Forward-deployed engineers] know that the only valuable software is not how exquisite its code is or how beautiful the language... It’s only valuable if it means something for the end customer.”
Forward Deployed is a weekly-ish publication and podcast exploring the intersection of AI, software development, and the enterprise from the point of view of practitioners who are building with these technologies.
The job of building aligned agents is as much cultural as it is technical. There is a lot to learn from the real agentic systems in the world: companies, farms, markets, militaries, film sets, and the other places humans have found ways to align large groups of agents.
The show started as a conversation about AI, software development, and the enterprise. It has evolved into a conversation about how to align agents.
Much of the current engineering conversation focuses on technical solutions: agent-to-agent protocols, memory systems, orchestration layers. Those things matter. But the challenge of aligning large groups of agents is an ancient one and not something that will be solved purely technically. There is a lot to learn from the systems humans already use to coordinate work, share context, set constraints, create feedback, and keep autonomous actors moving toward a common goal.
Host
Noah Brier
Noah is co-founder of Alephic, an AI-first technology foundry that helps marketing organizations build custom AI systems around their own data, workflows, and expertise. Alephic’s forward-deployed teams work with enterprise clients including Disney, Colgate-Palmolive, PayPal, EY, Meta, Amazon, and Ford.
Previously, Noah co-founded and sold Percolate, a marketing technology platform that worked with brands like Unilever and GE. He’s been recognized as one of Fast Company’s most creative people in business and served on the World Economic Forum’s Global Agenda Council for Social Media.
Why Subscribe?
Subscribe if you are trying to understand what it means to build AI systems that work in the real world: systems with context, evaluation, workflows, failure modes, and some theory of how people and agents stay aligned. The goal is a grounded way to think about AI without getting trapped between hype and dismissal.
