mAIndset

Tokens became frontstage topic of AI development due to two major trends colliding into each other:

• After token-maxing AI bills chew too much of company's costs and pendulum swings towards token-panic
• China has changed its AI strategy and with pushing highly performant Open-weights

But what this all means for your token consumption and even for business strategies of the AI Labs themselves? David and Filip cover this all in new juicy mAIndset episode.00:40 Why Token Pricing Is Hot Topic Now02:05 Three Pricing Layers for AI Tokens04:39 China Changed Their AI Strategy07:03 Two Opposing Forces For Token Price: Going Up or Down?09:14 Winning The Inference Game11:47 Hidden Fact About Cyber in Open Source Models12:55 Once You Become Profitable It Becomes A Target17:14 AI Labs Strategies - A - German Car Analogy23:15 AI Labs Strategies - B - Mass Market Colonization26:38 AI Labs Strategies - C - Being Apple Of The AI28:24 AI Labs Strategies - D - Becoming Oracle Of The AI29:18 AI Labs Strategies - E - Hits Economy30:07 AI Labs Strategies - F - Being The Utility32:22 What It All Means For Us As Customers35:24 Key Take-away's

Recent episode of the mAIndset podcast is expanding on yet-invisible but severe trends of AI reshaping the way we manage companies and launch new businesses.

02:25 It's All To Blame Roman Army

07:15 Organization model under AI fire

14:10 Top Management Pretending To Know AI

19:50 Some People Are Getting Addicted To AI (and micromanage)

26:30 What is AI Going To Do To YOUR Organization Level ?!

33:25 Next Cold War (or Why AI does not implement itself)

38:50 From Augmenting Humans to AI-Only organizations

45:10 AI Is Democratizing Starting The New Business

48:30 The Role Of Investors Flipped Inside Out

53:04 If You Are Middle Manager, You Better Move On

55:20 Meet Rudi - Case Study Example

56:45 Organization.AI , The New AI Only Business Model (and what it needs)

1:03:30 So what Shall You Specifically Do?

Episode is inspired by Filip's talk on AI Day event on campus of Faculty of Management, Comenius University.

Original slides to that speech author offered here for download: https://mocnedata.sk/en/managing-and-launching-organizations-in-ai-era/

The original presentation mentioned in the podcast [in its Slovak version] can be watched here:https://www.youtube.com/live/saMwwRw88wY?t=6475s

The most recent episode of podcast scrutinizes the hottest AI topic of first months of 2026: The OpenClaw. But rather than boring you with technicalities it gives clear reasons FOR WHOM this is a necessity and who might rather avoid using it. In last third David and Filip outline also WHAT COMES NEXT in the OpenClaw space. If you seek specific angle to the topic choose directly chapter:01:20 What Is OpenClaw And Why Is It Trending02:50 3rd Defining Moment of AI (after GPT and R1)05:15 Who Is OpenClaw For ? 06:20 Three Steps Of Democratization Of AI Labor 07:42 So What OpenClaw Brings ?!12:31 OpenClaw + MacMini | Many Get The HW Part Wrong17:20 How About Running Local LLM (For Free) In OpenClaw?19:30 50 MacMini's In Company? Negatives Outweight Pluses22:50 Clear Target group FOR WHOM OpenClaw YES28:33 FOR WHOM NOT : Stay Away If This Is Your Situation34:22 !!! WARNING !!! OpenClaw Makes You GDPR Non-Compliant35:10 Do You Need To Steer It From Remote36:40 OpenClaw Not Suitable To Automate Customer Support37:56 NanoClaw, ZeroClaw, ... Why We Have 3 Branches Of OpenClaw Clones42:48 OpenAI Blunder (So Far)45:48 "Computer" As New Version(s) Of OpenClaw48:00 China's Move On OpenClaw (so different to Western approach)51:15 Is OpenClaw Just FOMO ?53:35 Future? Where Is OpenClaw Going Next?53:35 OpenClaw Shuffling Cards For Cursor, Google and For SpaceX

This is insights-jammed episode where Filip & David unpack the whole context of AI-triggered Deep Software Companies Crises labelled SAAS-APOCALYPSE, namely:

• Why This is Just Wave 1 Of Apocalypse
• What Factors Accelerate/Prevent The Impact
• Who Will Die And Whom It'll Spare
• Tips that SW Companies Can Plug In to Las Longer

and many more interesting angles to this topic.

February landed us fascinating story of the Ai Agent ClawBot (itself renaming twice, survived attach of Crypto community and learning to send audio messages without consent of its "master"). But that was only beginning and thus David and Filip in recent mAIndset episode not only narrate the spicy story of making of Clawbot, but also what are the social implications of this fascinating story:00:50 Are We Finally Giving Steering Wheel To AI Agents02:20 How Did OpenClaw Come To Be07:25 WhatsApp Assistant, The Original Purpose of ClawBot09:45 MacMini's Spike Drama14:15 Naming Drama15:45 Crypto Community Strikes17:43 Messaging With Sam Altman18:40 Emergence of MoltBook, Agent-Only Social Net20:30 Master-Slave Or Having Soul?23:03 Aha Moment: Bots Finally Becoming Entities24:20 Media Wrongly Interpreting The Real Impact Of MoltBook25:50 MoltBook Was Just A Start: Next Social Interactions Of AI Bots32:00 RentAHuman Culmiation - Step Up From Tool To Contractor33:50 Where Do We Go From Here (Now Genie Is Out Of Bottle Already)36:02 AI Employees37:00 OpenAI or Meta Taking It Over + MCP Downplayed39:20 Bots Self-Learned Voice

David and Filip were neither sleepy nor shy to jump into new year with bold 2026 AI Predictions that might surprise you. But if you take few steps back, they are still quite likely to happen.

So don't miss the chance to adjust your 2026 AI Expectations in following areas:

00:21 Who Is Having Birthday?

01:23 OpenAI Will be Dethroned in 2016

06:04 Retail Investors Can Finally Invest Into AI, At Least 3 IPO's Will Come

11:38 Autonomous Taxis Will Arrive Into 5+ European Cities

19:40 Unemployment Spike In Major Economies, AI Partially To Be Blamed

25:20 Full Cinema-Long Movie Built Mostly Via AI

29:55 Meta Scales Down The Open-Source Line Of Models

32:00 Bonus Prediction: CN Model Will Take Top AI Spot For Some Time

36:50 SW development Turns Into Testing-focus

43:30 At Least 2 New Ai Form Factors (Devices) Introduced in 2026

46:29 2026 as Year Of Token Efficiency

50:10 AI Agents Turning Into Bookable Services (or Even Robo-employees)

55:02 Mondays vs. Tuesdays Of AI Engineers

56:42 New Sound of mAIndset

In the #17th episode of our mAIndset podcast we took again one of the leading AI competing companies and grilled in detail where they stand on AI past, present and looking forward. This time we detailed on MICROSOFT and uncovered all following aspects:

00:34 From 30000 Feet: Microsoft Should Have Been AI-successful

04:15 Beaten By Others Already Before ChatGPT

06:35 How Can You Miss This Badly ?!

08:40 Crucial Moment That Saves Some Dignity For Them

09:10 Do You Recall A Recall Function?

10:25 AI PC Move

11:30 Copilot - Biggest Branding Mistake Of Microsoft

16:50 AquaHire AI Team

19:20 OpenAI's Marriage (Or Friends With Benefits ?)

24:35 28% Stake In Biggest Frontier Lab

26:15 Where Does It Take Them Now?

29:20 GitHub Ever/Finally Utilized

31:35 Stock Market Hints

32:50 Small Hidden Booster Rocket

35:05 Summary Of Microsoft Chances

Over the last 6 weeks, Filip has travelled the Globe to visit 5 major AI conferences. He also collected key points that have been discussed. And thus we told ourselves, it would be a great opportunity to maybe summarize also for you, our audience, what the AI Practitioners are saying regarding the 2025 development in the AI domain. Therefore, in this 15th episode of the mAIndset podcast, we gradually cover:01:40 Ai Experts: We Don't Need Bigger And Bigger AI Models03:29 Shall We Rather Lean On SLM's ?!06:40 Taking 8-Wheel Truck For Grocery Shopping07:50 OpenAI Still Plans Overkill Of New Model Releases11:03 Stop Thinking About AI Capabilities !13:20 2025 Dictionary Word of Year: "(AI) Agents"15:17 Some Still On Wrong Track: Metering AI Agents By Numbers16:40 CONFIRMED: Agents Take Mainly Junior Jobs18:25 Efficiency Lever At Whooping 1:67 Rate20.36 Expect Top Managers To Have AI Agents Goals for 202623:04 Soon There Will Be Explosion In Token Consumption We Aren't Ready For25:02 Additional Nuclear Powerplant for Slovak AI27:24 New Local-PC-running-LLM Chips (from NVIDIA)31:56 Green Considerations In AI: 2 PDFs in GPT Equals ...35:42 So What Shall We Do Differently With AI ?!36:47 Do We Step Back From AI Search To Google Search ?38:03 Caching LLM Can Save 40% Of Your Costs39:16 Uff, Now We Will Store Tokens Into Traditional Databases?41:02 ALREADY MOST USED AI Use Cases Are ...44:17 SW Developer Roles Now Redefines To Test-Shaping46:26 OpenAI Push-back "Resistance" Is GatheringIf you want to suggest (or vote up) topics for next episodes of the mAIndset podcast, go and vote here:https://maindsetpodcast.com/If you have a question or comment, don't hesitate to reach out on:[email protected]

Topic of AI Bubble started to surface already last year and comes back in (ever increasing) frequent hops. Studies like infamous MIT study of 95% AI Failing are loading the discussion even further. So we settled down with David for discussion on where the truth might be on this Bubble issue.

To avoid being just shallow, we decomposed the total Revenue (and Profit) profiles of companies and discussed in deep detail the development around AI companies' User Bases, Intensity of Use and Frontier Labs' Pricing power.

The development in the very topic is so dynamic that next events my render these kind of talks soon irrelevant. Therefore, we invite you watch through quickly :) and to extract the measuring logic rather than just one snapshot conclusion. Enjoy!

Chapters:

01:40 Do We Have, AI Bubble Or Just Mind Games ?

04:10 M7 Taking Lion Share of Stock Market

06:25 It's Complicated, Because

08:40 AI Is Surely Getting To Big For Traditional Investors

10:10 Most Investors Are Locked Out Of Investment In AI

12:34 Reading The Recent Quarterly Results, We See ...

15:40 Profits, Not Reported, But Once Can Assume

19:54 When The Tide Goes Down, It Is Clear Whole Had Swimsuit And Who Didn't

21:02 Introducing 3 Factors: User Base + Intensity + Pricing

25:22 Positive And Negative Factors Of User Base Dynamics

28:07 Intensity of Use Is Tricky to Estimate

31:40 Wow Effects Try To Push Usage, But Stumbling On This

35:03 Free Tier Is Still Bloating Impression Of Demand

38:04 Quite Bluntly : AI Is Still Too Cheap

41:00 30USD+ Would Be Psychological Limit For Me

44:04 Bring Your Own AI To Work Might Play A Role Here

47:51 After Here All The Facts David Changes His Opinion

Having distinguished Prof. Amina A. QUTUB for interview is a dream of many Tech podcasters (or it certainly should be). As only few people have both the vision to see where AI is heading and the hands-on expertise to push those breakthroughs into the real life of clinics and hospitals.

Her work is on intersection of high-end, expert Biology and Computational Systems and even both ways: With her team she not only builds models that replicate human brain BUT ALSO uses these insights to gear "regular" AI (as we all know it from LLMs) to save lives in Emergency Rooms and help Clinicians to stay On-Top-Of-The-Game even in long shifts.

Thus, talking to someone, who's inventions can literally save your own life in future made this discussion so eye-opening and awesome at the same time. With David, we definitely took a chance to address the AI + Medicine combo from several angles and got from Dr. Qutub handful of insights nuggets.

So, go ahead & explore all chapters of this great interview:

01:50 Patterns of Communication, From Molecules to Humans

02:40 Where To Look For AI Start-Up Inspiration In Medicine

04:55 Turing Test in Medical AI Would Need to Include Smell and Taste

06:56 Combining Many Clinicians On Top Of Their Game

09:15 Accessibility Paves The AI Adoption (and hence hinders Medical AI)

11:24 In Full Emergency Room AI Split-second Decision Really Helps

16:35 Originally Deep Learning Inspired By Brain, But Where Do We Go Now

20:35 Is There Hope For Humanity To Merge Bio Brain Efficiency With AI

26:08 Building AI That Does Not Hurt Or Kill

29:34 How Do AI Scientists Choose (from ever changing) Top AI Models

32:05 Where Can/Should We Augment Humans With AI (and where to stop in it)

35:50 Launching AI Is Not Like Introducing Penicillin

38:19 Humble Self-Regulation (In Times Where Regulators Not Fully Grasp AI Principles)

41:30 AI Is Useful Even In My Private Life, But I Miss ...

44:16 What If We Invest Into Creating Super-Humans ?

Amina Ann Qutub, PhD is the Burzik Professor of Engineering Design and Associate Professor of Biomedical Engineering at the University of Texas, San Antonio. She serves as the Assistant Director of Strategic Alliances for the MATRIX AI Consortium and a research thrust lead for the Augmenting Human Performance thrust. Dr. Qutub is also the Director of the UTSA – UT Health San Antonio Graduate Group in Biomedical Engineering and co-lead of the Center for Precision Medicine. Dr. Qutub is pioneering methods at the interface of computer science, biology and engineering to study the design of human cells, and help eradicate diseases affecting cells of the brain and vasculature. In new translational work, Dr. Qutub is co-lead (with Drs. Brian Eastridge, MD, UTHSCSA and Alan Cook, MD, UTTyler) of the iRemedyACT project to develop AI tools that can minimize time to treatment and optimize care for trauma patients.