Human In The Loop Ep 4. Tesla's $1B Automation Failure: What Every AI Leader Should Learn From Tesla

Humans In The Loop Ep 7. Why Anthropic and OpenAI Are Copying Palantir's FDE Playbook

Anthropic just raised $1.5B with Blackstone, Hellman & Friedman, and Goldman Sachs. OpenAI raised $4B with TPG, Bain, and Advent the same day. Both labs are building delivery organizations explicitly modeled on Palantir's forward-deployed engineer playbook. In this episode of Humans In The Loop, Kasey Roh and Galina Fendikevich unpack the following question: are FDEs the right model for enterprise AI adoption? 00:00 Trivia: Anthropic vs OpenAI on the secondary market 04:00 The news: $5.5B raised to fund delivery organizations 06:30 Why Wall Street is funding deployment, not just models 08:30 "Having the model alone doesn't change your workflows" — Goldman's quiet admission 12:00 Why enterprise environments are a rat's nest (and why APIs alone don't ship) 15:00 95% of enterprise AI pilots fail. MIT NANDA on the gap between API and production. 17:30 What Palantir's 20-year playbook actually proves 19:00 The 6,000-company ceiling: why this only works at the top 22:30 FDE economics: $350K to $500K+ salaries and what they mean for customers 24:00 The permanent retainer: why FDE deployments don't end 26:30 Lock-in dressed as transformation 28:30 The contrarian take: this isn't bullish, it's the opposite 30:00 The mid-market opportunity nobody is solving yet 🗣️ Follow us on YouTube: youtube.com/channel/UCJbkvAHHTRlo2EXkGyUrA-g/ 🎧 Also on Spotify and Apple Podcasts:  - Spotify: https://open.spotify.com/show/5CAwQDcofIzMM9p5GIChOo - Apple Podcast: https://podcasts.apple.com/us/podcast/humans-in-the-loop/id1892864937 💼 Connect with Us: - Kasey: https://www.linkedin.com/in/kaseyroh/ - Galina: https://www.linkedin.com/in/gfendi/ #enterpriseai #humansintheloop #humanintheloop #generativeai #aiadoption

Humans In The Loop Ep 6. Token Economics in Enterprise AI: Why Your AI Budget is Already Blown

Token Maxing: The New KPI or the Next Enterprise AI Budget Trap? Token economics is reshaping how enterprises think about AI spending. In this episode of Humans In The Loop, Kasey Roh and Galina Fendikevich unpack Jensen Huang's token maxing framework, Uber's blown 2026 AI budget, Meta's failed leaderboard experiment, and why only 28% of finance leaders can measure AI ROI. 00:00 Token Maxing Intro 01:09 Jensen Token Trivia 03:22 Budget Reality Check 06:24 Token Economics Framework 09:57 Tokens Per Employee Debate 12:06 Meta Leaderboard Backfire 17:11 Uber Budget Blowout 21:49 CFO Visibility And ROI Gap 27:10 Governance And Spend Consolidation 30:24 Open Source Comeback 35:44 Platform Over Single Model 37:54 Wrap Up And Where To Listen 🎧 Also on Spotify and Apple Podcasts:  - Spotify: https://open.spotify.com/show/5CAwQDcofIzMM9p5GIChOo - Apple Podcast: https://podcasts.apple.com/us/podcast/humans-in-the-loop/id1892864937 💼 Connect with Us: - Kasey: https://www.linkedin.com/in/kaseyroh/ - Galina: https://www.linkedin.com/in/gfendi/ #enterpriseai #humansintheloop #humanintheloop #generativeai #aiadoption

Humans In The Loop Ep 1. AI Success Stories in the Enterprise: What Actually Works vs. What's PR

Enterprise AI Reality Check: Only 2 Insurers in Fortune 500 Show Quantified ROI (Plus Maersk, HPE & Tiffany Success Stories) In the first episode of Humans in the Loop, Kasey Roh and Galina Fendikevich introduce the show’s focus on the gap between AI hype and real enterprise adoption, especially in regulated industries like insurance. Kasey shares analysis of Q4 earnings-call CEO remarks across ~60 companies, tracking AI mentions, quantified ROI, and 2026 plans; among Fortune 500 insurance carriers, only Chubb and Travelers cited quantified AI ROI, and Travelers mentioned AI about 45 times. They discuss why insurance may be more conservative and argue for small, tangible AI deployments rather than endless pilots. They highlight success cases: Maersk pivoting from a $100M blockchain effort to AI route optimization saving $375–$500M annually in fuel, HPE building a finance-ops AI agent (“Alfred”) with Deloitte, and Tiffany using genAI to create 700+ monograms for engraving. 00:00 Welcome to the Show 00:15 Meet Galina 01:04 Why Humans in the Loop 02:20 Meet Kasey 03:15 Earnings Call AI Study 04:38 Insurance ROI Reality Check 07:20 AI Mentions and Metrics 11:33 2026 Plans and Budgets 15:30 Why Insurance Moves Slow 16:09 Start Small with AI 18:43 Maersk Fuel Savings Win 21:48 HPE Alfred Finance Agent 24:48 Tiffany Engraving with AI 27:10 Wrap Up and Thanks 🎧 Prefer audio?  - Listen on Spotify: https://open.spotify.com/show/5CAwQDcofIzMM9p5GIChOo |  - Apple Podcasts: https://podcasts.apple.com/us/podcast/humans-in-the-loop/id1892864937 💼 Connect with Us: - Kasey: https://www.linkedin.com/in/kaseyroh/ - Galina: https://www.linkedin.com/in/gfendi/ #HumansInTheLoop #EnterpriseAI #AIGovernance #HumanInTheLoop

Humans In The Loop Ep 2. Can AI Rewrite Legacy Work? Rethinking Enterprise Processes in the AI Era

Can AI Rewrite the Past? Mainframes, COBOL Modernization, and Real-World AI Wins Kasey and Galina discuss insights from the NAMIC mutual insurance conference in Chicago and why AI adoption can feel like an uphill battle outside the tech bubble. We dig into mainframes—over 90% of global credit card transactions and about 68% of IT workloads run on them at roughly 6% of global IT cost—and why hybrid architectures can enable AI without migrating off legacy systems. We unpack Anthropic’s claim that Claude can help modernize COBOL and the market reaction that coincided with a $30B IBM market-cap drop, while emphasizing the real challenges of testing and validation amid an aging COBOL workforce. We also cover Marriott’s mixed results with guest-facing AI versus “invisible AI” in core operations, and Hallmark’s approach of keeping humans in the loop while using AI for supply chain, personalization, and workflow efficiency. 00:00 Welcome Back Intro 00:14 Chicago Conference Takeaways 01:37 Can AI Rewrite Legacy 02:53 Mainframe Trivia Shockers 04:57 Why Mainframes Still Win 09:27 Hybrid AI On Mainframe 12:00 Claude Modernizes COBOL 13:32 Talent Gap And Validation 17:26 IBM Watson And Urgency 19:23 Marriott AI Concierge Fail 22:44 Invisible AI Backend ROI 25:42 Hallmark Human In Loop 31:18 Trust But Verify Wrap Up 33:44 Closing And Call To Action 🎧 Also on Spotify and Apple Podcasts:  - Spotify: https://open.spotify.com/show/5CAwQDcofIzMM9p5GIChOo - Apple Podcast: https://podcasts.apple.com/us/podcast/humans-in-the-loop/id1892864937 💼 Connect with Us: - Kasey: https://www.linkedin.com/in/kaseyroh/ - Galina: https://www.linkedin.com/in/gfendi/ #enterpriseai #humansintheloop #humanintheloop #aigovernance #generativeai

Human In The Loop Ep 4. Tesla's $1B Automation Failure: What Every AI Leader Should Learn From Tesla

When Elon's $1B automation turned into a tent full of humans Kasey and Galina discuss how businesses often try to force operations to fit AI, instead of mapping workflows in detail so AI can adapt to the business and reveal high-ROI opportunities. Kasey shares her 2018 Tesla experience during Model 3 “Production Hell,” when Elon Musk pushed near-total factory automation to hit 5,000 cars/week but production lagged, costs soared (about $100M/week), and we resorted to manual work and a tent-based assembly line. We explain the turnaround: breaking work into granular steps, using real-time KPI dashboards, keeping humans in the loop, iterating, and automating only where it fit—paralleling today’s AI POCs that fail in production without integration and workflow understanding. 00:00 AI Adoption Reality Check 02:37 Meet Kasey and Tesla Roots 04:43 Production Hell and Funding Chaos 07:27 The Fully Automated Factory Bet 13:16 Why Automation Broke Down 18:16 The Tent Line Human Pivot 22:22 Workflow Mapping Turnaround 29:43 Leadership Lessons for GenAI 37:55 Avoid FOMO and Cautionary Tales 40:32 Final Takeaways and Wrap Up #enterpriseai #humanintheloop #humansintheloop #generativeai #aigovernance #tesla