Luke F. Walton

Founder & CEO, Surmado | Senior Marketing Manager
Amazon

Luke F. Walton is an AI builder and marketing operator, founder and CEO of Surmado, and currently a Senior Marketing Manager and AI Bar Raiser at Amazon. At Amazon, he oversees seller-facing paid social media across 23 regions worldwide and manages eight-figure media budgets supporting programs that deliver more than 1 billion annual impressions. He received Amazon’s 2025 “Bias for Action” Award and won AWS’s Bedrock Data Chunking Challenge, outperforming more than 100 engineers in retrieval-augmented generation design.

His career traces a consistent pattern: working at the edge of emerging technology and figuring out how to make it useful in the real world. At Google, he worked on the early commercialization of Google Glass for enterprise customers and developers. During his MBA, in partnership with U.S. Indo-Pacific Command and Qualcomm, he developed wearable technology for field medics. At NAMM, he led marketing through the post-pandemic return of The NAMM Show, helping welcome more than 100,000 attendees and deliver $8 million in critical revenue recovery.

Today, Walton works across both large-scale enterprise marketing and early-stage AI product development. At Surmado, he builds production AI systems that perform real customer-facing work, including Surmado Sites, an agentic platform that allows small businesses to operate and continuously update their websites through natural language. His work focuses on how models, deterministic software, tools, permissions, evaluations, and human oversight fit together when AI moves from assisting work to actually executing it.

Walton also publishes independent research on AI ethics, responsibility, and answerability, including The Captured Oracle: Authorship and Agency in the Ethics of Answer-Engine Optimization, currently under revise-and-resubmit at AI and Ethics, and Answer Engine, an open-source reference implementation for citation-grounded answerability. He also teaches practical generative AI, agentic workflows, and responsible AI implementation.

A lifelong musician and producer who records as Scoobert Doobert, Walton has hundreds of millions of streams and releases on Sub Pop, Sony Japan, Armada Music, Indiemono, and Beformer. He lives in San Diego and spends as much time as he can in Japan.

 

Luke F. Walton’s Sessions

2:00 p.m.–2:45 p.m. PT — Wednesday, February 24, 2027

Panel: What Humans Own Now: Taste, Judgment and Creative Direction in an AI-Executed Org

AI can now generate a hundred campaign concepts before lunch, write the copy, produce the visuals, and help bring it all to market. As execution becomes faster, cheaper, and more accessible, the real competitive advantage shifts to judgment: deciding what deserves to exist, what gets cut, and which ideas are worth investing in. And as more brands adopt the same AI tools, the risk of producing the same messages, visuals, and creative approaches grows. Human taste, business context, and creative direction become more valuable than ever.

Moderated by Adam Constantine of ACE Creatives, this panel brings together marketing leaders from Getty Images, Amazon, and LinkedIn to explore what humans must continue to own as AI takes on more of the execution. They'll discuss where human judgment creates the greatest competitive advantage, how to maintain originality and authenticity in an increasingly AI-generated world, and how to establish the standards and accountability needed to scale AI responsibly.

You'll leave with a clearer understanding of where human expertise delivers the greatest value, what to delegate to AI, and how to build a marketing organization where technology scales execution without sacrificing creative differentiation.

Key Takeaways:

  • Shift your team's creative value from production to selection, focusing on the ideas, directions, and investments that deserve to move forward.
  • Lead with audience needs and business objectives, rather than adopting AI simply because the technology is available.
  • Bring the business context, creative judgment, and brand understanding AI can't replicate to keep your messaging and positioning distinct.
  • Invest in original creative assets, from real people and locations to authentic brand experiences, then use AI to extend their value and reach.
  • Redefine human oversight by establishing clear objectives, guardrails, and accountability so AI can execute at scale without compromising authenticity, IP, representation, or brand safety.

10:00 a.m.–10:45 a.m. PT — Thursday, February 25, 2027

Case Study: Agentic GTM in Practice: From Copilots to Delegated Workflows

Agentic AI becomes useful when it stops being a chat interface and starts completing real work. Giving a model tools is the easy part. The harder questions are operational: What should an agent actually own? Which steps should remain deterministic? Where does model judgment belong? What boundaries should be enforced in code rather than left to a prompt? When should a human intervene? And how do you know whether delegation is producing better business outcomes rather than simply more output?

Drawing on his experience operating AI inside Amazon and building production AI systems and software at Surmado, Luke F. Walton will break down a practical model for moving go-to-market work from AI assistance toward supervised and delegated execution. He will ground the framework in real operating patterns from global paid media and from Surmado, where an AI agent is entrusted to operate and change customer-facing production websites. The session will show how to decompose work, separate deterministic logic from model judgment, set permissions and escalation paths, enforce critical boundaries structurally, preserve reversibility and human oversight, and evaluate whether the resulting system is actually worth delegating to.

Key Takeaways

  • Learn how to break a GTM workflow into deterministic steps, model judgment, and human decisions
  • Examine what changes when an AI system is trusted to operate a customer-facing production asset instead of just recommending actions
  • Determine when to enforce a boundary in code, architecture, permissions, or CI rather than relying on prompt instructions
  • Calibrate the right level of AI autonomy based on stakes, reversibility, observability, and escalation paths
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