Larissa Schneider, Co-Founder & COO of Unframe AI, is building one of Europe's boldest enterprise AI platforms - and she's doing it with outcome-based pricing. No per-seat fees. No token meters. Just measurable business outcomes.

In this episode, host Johannes Deubener sits down with Larissa to unpack why seat-based pricing is killing enterprise AI adoption, how Unframe deploys production-ready AI in under a week using a modular "Lego block" platform, and what it actually takes to tie your revenue to client results.

Larissa shares the real story behind outcome-based pricing - from internal debates to live customer examples - including how they helped one of the world's oldest newspapers cut proofreader onboarding from 2-3 years to nearly instant. She also drops a bold prediction: citizen development and quick DIY AI will die at the enterprise level.

Whether you're an AI founder figuring out your pricing model, an enterprise leader stuck in pilot purgatory, or a CIO evaluating build vs. buy - this episode is packed with practical frameworks you can use today.

⏱️ Chapters:

00:57 - International Background & Leading Global AI Teams

02:17 - Building Company DNA in a Remote-First Culture

02:55 - From Farm Kid to AI Founder

06:49 - What Technologists Miss About AI Adoption

08:37 - The Real Root Cause of Pilot Purgatory

10:10 - Build vs. Buy

12:59 - The Honest AI Strategy Conversation with a CEO

15:33 - Unframe Explained: The Lego Box Analogy

19:29 - Customer Story: Oldest Newspaper in the World Goes AI

21:50 - IP, Blueprints & How Custom AI Solutions Work

23:35 - Pricing: Why Seats & Tokens Are Broken

25:41 - Tying Revenue to Client Results

31:14 - Pricing a Chatbot by Outcomes - A Real Example

33:22 - Preventing Adoption Failure & the Free POC Model

35:01 - How Outcome-Based Pricing Changes Product Development

36:13 - Advice for Founders on Outcome-Based Pricing

38:16 - Outcome-Based Pricing as a Competitive Moat

40:26 - Redesigning Enterprise AI Procurement from Scratch

41:44 - Larissa's Bold Prediction

42:11 - Will AI Make Organizations More Human?

43:01 - Larissa's #1 Advice for Enterprise AI Success

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Connect with Johannes: https://www.linkedin.com/in/johannesdeubener/

Follow Larissa: https://www.linkedin.com/in/schneiderlarissa/

Check out Unframe AI: https://www.unframe.ai/

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More about AI To Go: I Real Talk on Enterprise AI

✨ Watch more Episodes on YouTube: https://www.youtube.com/channel/UCiL3_cC9nmXALQiaqlYs2Kw
✨ Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-to-go-podcast/id1866997458

✨ Listen on Spotify: https://open.spotify.com/episode/5X9XgIv1qtCYtExziNMyXK
✨ Receive all Updates on LinkedIn: https://www.linkedin.com/company/ai-to-go-podcast/

If you’re an enterprise AI founder, you’ve seen the same pattern: pilots everywhere, ROI nowhere, governance used as a brake, and leaders asking for “hard numbers by next quarter.”

In this episode, Johannes Deubener sits down with Rajuta Singh, Founder & CEO of Solved Together, to unpack why transformation fails (hint: it’s rarely the tech) and how CEOs can break the “AI anxiety loop” with structured experimentation, cross-functional squads, and outcome-first execution. They unpack real boardroom fears around AI - from stalled pilots and 7-figure “science projects” to data roadmaps, legacy systems, and middle managers secretly blocking change.

If you are an AI founder selling into enterprises or an enterprise leader trying to turn AI hype into business outcomes, this conversation gives a 90-day path you can start using immediately.

• 00:04 Welcome + guest intro: Rujuta Singh
• 00:57 Why people dynamics decide outcomes
• 02:06 Every company has the same collaboration problem
• 04:14 Collaboration brain hacks
• 08:26 Neuroscience of meetings
• 12:29 “Transformation Reality TV”

• 16:11 AI as #1 priority for 2026
• 18:43 Ruthless prioritization: which pilots to kill vs scale
• 20:23 CFO vs AI team: ROI now vs “compounding later”
• 23:16 Integrate AI into business strategy
• 24:35 The Talent Dilemma
• 27:04 Upskilling Challenge
• 32:35 Silent sabotage: how to unblock middle managers
• 37:22 The “AI strategy” all-hands
• 41:06 Data governance vs speed
• 43:20 Legacy systems
• 46:49 First 90 days
• 49:48 What CEOs miss

• 55:45 Don’t try to keep up
• 58:04 The Top Leadership Skill
• 1:00:32 Where to find Rajuta

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Connect with Johannes: https://www.linkedin.com/in/johannesdeubener/

Follow Rujuta: https://www.linkedin.com/in/rujutasingh/

Check out Solved Together - AI Accelerator: https://www.solvedtogether.co.uk/ai-accelerator

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More about AI To Go: I Real Talk on Enterprise AI

✨ Watch more Episodes on YouTube: https://www.youtube.com/channel/UCiL3_cC9nmXALQiaqlYs2Kw
✨ Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-to-go-podcast/id1866997458

✨ Listen on Spotify: https://open.spotify.com/episode/5X9XgIv1qtCYtExziNMyXK
✨ Receive all Updates on LinkedIn: https://www.linkedin.com/company/ai-to-go-podcast/

Ted Shelton has seen the AI wave from every angle - partner at Bain, COO at Inflection AI, now founder of adaptability.com and builder of the Personal Agent aalpi.ai. In this episode, Ted and host Johannes Deubener discuss what happens when AI compute becomes a new form of capital that no longer needs human labor.

Ted explains why owners of compute will capture value faster than overall economic growth, how this breaks the 250-year-old relationship between capital and labor, and why “abundance” does not automatically mean broad participation. On individual level, we explore the human skills that actually compound and how you can practice adaptability in this fast-paced world.

Chapters

00:04 Introduction to Ted Shelton

00:56 Public Skepticism Towards Autonomous Vehicles

04:32 The Future of AI Interaction

08:18 Reflections on AI's Evolution

11:59 Transitioning from Pilot to Execution at Scale

14:17 Rebuilding Inflection AI: Insights and Challenges

16:39 The Importance of Data Ownership in AI

19:31 Achieving ROI from AI Initiatives

23:26 Turing trap - Balancing Automation and Augmentation

25:25 AI as a Coordination Mechanism

31:12 Building Adaptability in a Rapidly Changing World

34:19 How to Teach Adaptability as a Meta Skill

36:13 Navigating the Rapid Pace of Technological Change

39:14 The Importance of Human Skills in an AI-Driven World

40:35 Redesigning Work for the Future

43:30 The Economic Bitter Lesson and AI Inequality

47:15 Collective Action and the Need for Adaptability

50:19 Compute Capital: A New Form of Value

53:37 Winners and Losers in the AI Economy

57:32 Rethinking Wealth Distribution in an AI World

01:01:27 Optimism for Future Generations in a Changing World

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Don't be shy and come say hi:

Connect with Johannes: https://www.linkedin.com/in/johannesdeubener/

Follow Ted: https://www.linkedin.com/in/tshelton/

Subscribe to his Newsletter: https://www.linkedin.com/newsletters/infinite-future-6980527547914534913/

Check out his privacy-first AI Agent Aalpi: https://aalpi.ai/

Check out his Adaptability learning platform: https://www.adaptability.com/

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More about AI To Go:

✨ Watch more Episodes on YouTube: https://www.youtube.com/channel/UCiL3_cC9nmXALQiaqlYs2Kw
✨ Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-to-go-podcast/id1866997458

✨ Listen on Spotify: https://open.spotify.com/episode/5X9XgIv1qtCYtExziNMyXK
✨ Receive all Updates on LinkedIn: https://www.linkedin.com/company/ai-to-go-podcast/