What if your documents got VP-level feedback before the actual review? On this episode of strAIght talk, hear how one builder turned a decade of leadership feedback into an AI-powered review tool now used by over a thousand colleagues each week.

Guest: Isabela Huggins, Sr. Manager, Ops & Enablement, Global Logistics

Beth Galetti, SVP of People Experience and Technology, hadn't written code in 25 years. Then she built a live website with AI on a transatlantic flight and challenged every person in her organization to build something in two hours or less. Over 1,000 did.

Guest: Beth Galetti, SVP, People Experience and Technology, Amazon

The Working Backwards AI tool was built to be your toughest thinking partner for product ideation. The tool walks you through five customer questions, generates personas who react to your idea, and brings in domain experts to test your thinking. Over half of users say their final idea was different from what they started with.

Guest: Phil Nachbar, Principal Product Manager, Working Backwards

Telling your team to "experiment with AI" without a structure usually leads to scattered pilots that fizzle out. One leader built a model that loads both ends: a dedicated Tiger team reimagining one high-value workflow while the broader org gets protected time to skill up and share what's working. On this episode, our guest walks through the full framework, how the two sides feed each other, and why getting to a disappointment fast is more valuable than waiting months for a polished demo. His biggest tip: pick one workflow where the pain is obvious, give a single owner two weeks, and ship something working.

Guest: Ishit Vachhrajani, Director of Tech, AI, and Executive in Residence, AWS Marketing

Reviewing a document against a standard used to mean line-by-line cross-referencing — toggling between the policy and the draft, flagging deviations manually. One team built an agent that takes the first pass, handing back an annotated Word doc with comment bubbles on anything that needs attention. On this episode, the builder shares the full setup, the exact prompts, and one trick that pulls standards from any internal page without a connector. His biggest tip: start with the review task that comes up the most — volume drives the biggest savings.

Guest: Sean Callahan, Sr Program Manager, Legal, AWS Infrastructure

What if the goal isn't getting through your tasks faster, but using AI to handle them more efficiently so you can focus on higher-impact work? In this episode of strAIght talk, one Amazonian shares how he rethought his daily work and freed himself to lead differently.

Guest: Daryl Hammett, Director, Delivery & AI Platforms, AWS ProServe

"Which AI tool should I actually use?" Leo Ohannesian, a product manager on the Amazon Quick team, comes back to strAIght talk with a candid answer: pick one, go deep, and let it learn you. On this episode, he breaks down how Quick's desktop app builds a knowledge graph from your connected tools, learns your working style through procedural memory, and keeps your context fresh through an activity feed that reads your sources every 15 minutes. His biggest tip: open your feed, customize how it prioritizes your work, then ask Quick, "What's a repetitive behavior I've had that could just run for me?"

Guest: Leo Ohannesian, Principal Product Manager, Amazon Quick

In this episode of strAIght talk, the Amazon Luna team breaks down the four-part "harness" framework they used to turn a simple chatbot into Courtroom Chaos, a live AI-native game with celebrity judges. You'll walk away with a repeatable approach for building AI experiences that feel intentional, not generic. Whether you're prototyping your first AI feature or trying to make an existing one stick, start here.

Guests: Pen Szeto, Head of AI and Sergey Rudenko, AI Technologist - Amazon Luna