Try for free
The Robot Report Podcast
The Robot Report Podcast

From Teach-and-Repeat to SelfPath AI: The next robotics leap

28 August 2026 1:20:17 The Robot Report Podcast

Listen to episode

About this episode

On the show today our guest is John Black, CTO of Brain Corp. John shares how Brain Corp has evolved from proving autonomous navigation in public spaces to operating at fleet scale across cleaning, scanning, retail analytics, and new manipulation use cases. He explains why the real challenge is not just making robots smarter, but building the guardrails, infrastructure, and platform reuse needed to deploy them safely and reliably in the real world.
John joins Gene Demaitre and Mike Oitzman to unpack how Brain Corp moved from proving autonomous navigation in public spaces to operating fleet scales across cleaning, inventory intelligence, and shelf scanning.
He explains why the company’s next leap is less about building one perfect robot and more about creating a platform that can support many robot form factors, many applications, and many customers at once. You’ll discover: Why public spaces are the hardest test for autonomous robots, and how Brain Corp designs for safety without killing productivity How Brain OS evolved into a full-stack platform with cloud infrastructure, OTA updates, manufacturing tools, trust centers, and fleet management Why 50,000 connected robots and tens of millions of operating hours create a data advantage smaller fleets simply cannot match If you want a clear-eyed look at where physical AI is headed — and what it takes to make robots commercially useful instead of just impressive — this episode delivers the strategy behind the scale.

Register now for RoboBusiness 2026: https://cvent.me/w0eRN9?RefId=podcast

More AI podcast episodes

Browse all →

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 The Robot Report Podcast. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support