Swami joins Brad Porter for a candid conversation about the gap between AI assistants and AI agents, what it means to be on the loop rather than in it, and how Amazon rewired the way it works: one agent for a company-wide Java upgrade, a demo in a week before the PR/FAQ, and no more version 30 of a doc.

The conversation ultimately points toward a future where the models are no longer the constraint and the organization is: the teams that pull ahead stay on the loop, decide in days instead of months, and put deterministic guardrails around probabilistic agents.

Brad Silverberg joins Brad Porter for a candid conversation about why the Lisa and the original Mac were brilliant and still struggled commercially, how he shipped Windows in deliberate steps with Windows 95 in his head from day one, and how Internet Explorer came from two or three percent share to winning the browser before Microsoft gave the lead away.

The conversation ultimately points toward a rule that outlives any single platform: platforms are won not by the best idea but by whoever sequences the hard problems correctly, and they are lost more often to the politics inside the building than to anything a competitor does.

Erik joins Brad Porter for a candid conversation about the distance between a robot demo and a real deployment, what it takes to sell automation to companies a thousand times your size, and why a human in the loop still keeps the robots working.

The conversation ultimately points toward a future where progress comes less from how robots move than from how well hands and eyes work together, built by engineers who have lived with the problem on the operator’s side.  Also, check out the live stream response to Figure's Demo! https://bit.ly/4czQ37G

Russ joins Brad Porter for a candid conversation about leaving the lab for the factory floor, the practical choices behind robots that can work today, and what the physical AI boom could mean for the future of manufacturing.

The conversation ultimately points toward a future where robots don’t simply replace individual tasks, they help factory workers and production engineers improve entire systems faster than ever before.

0:00 Intro 
2:00 Lessons from Atlas: deforming legs and broken hands
6:30 Kung-fu humanoids: entertainment vs. real-world value
8:20 The real world is the ultimate eval — and the Walden pitch
11:30 Humanoid or not? Wheeled base, grippers, and safety cases
15:30 Why floors matter: flatness, wear, and messy facilities
19:20 Generality and embodiment: how much does morphology matter?
22:50 What data is actually salient? Filtering and noisy data
26:50 Challenges as evals: the Amazon Picking Challenge and its alumni
29:00 Capital, bubbles, and whether this time is different
31:00 Reshoring, export rules, and the logistics engine
33:40 Tips for founders and Chesterton's fence
36:10 Factories are dynamic: co-evolving with robots
37:20 The metronome effect and compounding automation gains
41:15 Vibe coding the factory floor and the Toyota Production System
45:30 The vibe at MIT, and closing

They get into the first-principles call that saved Tellme (walking away from a company-defining AT&T check), how to build teams that compound, why he shipped voice AI two decades before the world was ready, and two unforgettable Steve Jobs stories, including the day Jobs picked up an iPad and explained Flipboard's purpose better than Mike could himself.

Aicha traces her path from a childhood between Senegal and Paris–hacking the phone to call home because the bill ran a thousand dollars a month–to Intel, to the Zoox factory floor at the start of production. She dismantles the debate consuming physical AI, arguing that the models will commoditize but hardware-software integration never will, and that the real moat is people who can sit at the same table with equal decision rights.

In this episode of Deployed, Brad Porter and Pat Shanahan get into what it actually takes to put hard new technology into the hands of the people doing the work. Pat tells the story of betting the company on designing the 777 entirely on a computer, and the moment on the factory floor when everyone was sure it would fail. They cover his rule of "only three miracles at once," why every deployment is a people problem before it's a technology problem, the difference between AI "safety" and product integrity, and why a man who has shipped at the largest scale there is wishes he could go back 20 years in his career with these tools.

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