Implementing AI solutions for global brands | Co-founder @G3NR8

AI will revolutionise work and business.

If you use it in the right way.

I can teach you how. 

👋 I'm Tom Head, Co-founder at G3NR8. 

We help global brands unlock the power of AI with strategic, thoughtful solutions. 

Here's how I can help you:

🟩 Develop your AI strategy and policies
Turn AI into a goldmine for business growth and efficiency

🟩 Create a competitive advantage using your proprietary data
Use your company data alongside AI to stay ahead

🟩 Automate repetitive tasks 
Find the right tasks to automate, then create reusable frameworks

🟩 Gain actionable insight from data 
Find patterns and relationships in data then do something with it

🟩 Train your teams 
We've trained 120+ large organisations in advanced generative principles and implementation

Welcome to my profile.

You can expect to see me post about:

- AI Toolkits, guides, prompts, and more. 
- AI applications.
- Bad AI - so you know what not to do
- Leadership & Culture.
- What’s hot, what’s not, and what you need to know.
- The good, the bad, and the hilarious from my journey.

For more of my thoughts (and occasional rants), listen to my podcast and subscribe to my newsletter. 
(Links in featured section)

See you there 👋

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Tom Head

Capgemini Invent

→ Spearheading global initiatives focused on AI upskilling within Capgemini Invent's AI Accelerator program.

→ Collaborating with a core team of AI experts responsible for go-to-market strategies, technology development, and strategic partnerships.

→ Responsible for designing and implementing programs to disseminate cutting-edge AI knowledge and practical know-how internally and to external clients.

→ Focused on enabling successful AI transformation by addressing not only the technological aspects but also the critical design of future human-machine interaction and exploring capabilities beyond current human limitations.

Global AI Accelerator Upskilling Lead

In a world where digital transformation dictates market leadership, staying ahead is crucial for your business’s growth and sustainability. As an accomplished Digital Strategist and New Business Model Expert, I am dedicated to guiding businesses through this complex landscape to achieve extraordinary success.

My Core Expertise: Lead for 'Connected Products & Services & Business Model Transformation':

→ Strategic Development of Data-Driven Products & Service Portfolios: I specialize in developing competitive, customer-centric product and service portfolios that align seamlessly with your overarching business strategies. This includes not only strategic planning but also defining the actual content and structure of these portfolios.

→ Business Model Transformation in Response to Global Trends: Adapting to major market shifts like Everything-as-a-Service, AI-driven business models, and exploring new channels such as virtual platforms and metaverses, I help companies transform their existing business models to capture new customer segments and stay at the forefront of innovation.

→GenAI Advisor for Intelligent Industry

In my role as the GenAI SPOC for Intelligent Industry, I empower organizations in manufacturing, life sciences, and MedTech to leverage the extraordinary capabilities of Generative AI. This role involves exploring new business opportunities and achieving unprecedented levels of productivity and efficiency through cutting-edge AI applications.

▶️ Our Commitment:

More than just strategists, we are your partners in transformation. From the initial strategy to the hands-on implementation of new products and services, our team of strategists, designers, and engineers is committed to turning your vision into a tangible reality.

▶️ Ready to Transform Your Business?

Connect with me to discover how we can collaboratively reinvent your business strategy for a digital-first world, ensuring growth, innovation, and a leading edge in your industry.

Director Connected Portfolio & Business Model Transformation | Federated AI in Intelligent Industry

Capgemini

At Capgemini Global AI Lab, I lead initiatives that shape the future of AI technology application, focusing on its merits and potential pitfalls for our clients and society. Our lab is dedicated to true innovation, thought leadership, readiness for new developments, cutting-edge research, education, and promoting the safe and ethical use of AI.

Harnessing emerging trends and technologies, I help you navigate the AI landscape and establish new types of AI models that herald a step change in how we can solve business problems holistically. In my role, I challenge the status quo and empower organizations to reimagine their businesses and amplify their potential for impact.

So, engage with us—let us surprise you with our visionary mix of what's to come.

Capgemini Global AI Lab - AI Strategist & Visionary

OpenExO

OpenExO is the world’s leading global ExO transformation ecosystem made up of more than 1,000 clients, investors, consultants, coaches, collaborators, tech leaders, and innovation specialists. Together we are committed to helping organizations, institutions, and people transform the world for an exponentially better future by implementing and evolving the ExO model and practices.

ExO Certified Consultant

ExO Foundations

Exclusible

Are you ready to explore the endless possibilities of the future internet? I am here to help you take the first step and unlock the power of web3 CRM.

Imagine being able to connect with customers and clients in new and exciting ways, using cutting-edge web3 technology and immersing them in a metaverse. That's exactly what Exclusible does. Empowering brands and communities by expanding the possibilities of both the physical and digital universes.

Exclusibles mission is to build a new generation of the web that is culturally relevant, accessible to everyone and unlimited in its possibilities for creation and creativity. With Exclusible, your brand has the opportunity to push the boundaries of the metaverse and web3, and open up a world of endless possibilities.

Don't wait any longer, take the leap and join the future of the internet. Contact me now to learn more about how we can work together and unlock the power of web3 for your business.

Metaverse Leader, Advisor and Ambassador

STRATEGYON 

𝗦𝗧𝗥𝗔𝗧𝗘𝗚𝗬𝗢𝗡 𝗖𝗢𝗥𝗘 builds on the most advanced AI-enabled context-mining platform for reliable strategic insights.

𝗦𝗧𝗥𝗔𝗧𝗘𝗚𝗬𝗢𝗡 𝗖𝗢𝗥𝗘 services transform unstructured data into quantified and groundbreaking insights and build a foundation for fact-based, strategic decision-making in your strategy and M&A activities. 

Unsupervised AI-driven context mining leads to unbiased discovery and insights for trustworthy strategic decisions. 

▶️ Cross-industry research for technology mapping
▶️ Gaining hidden consumer insights from public forums
▶️ Anticipating significant shifts: future scenario building

Quantifying insights are a solid basis for masterful decision taking. Our innovative metrics and visualizations help to efficiently discover emerging topics, non-trivial correlations, and to compare trends. 

Reliable quantified insights are what really matter.

▶️ Weak signal detection
▶️ Visualize patterns in tailor-made heat maps
▶️ Discover hidden correlations

𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗺𝗮𝗽𝗽𝗶𝗻𝗴:
Technologies evolve at the speed of light. It is vital to discover new technologies and understand the dynamics and drivers to stay ahead of the competition.

𝗠𝗮𝗿𝗸𝗲𝘁 𝗲𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗶𝗼𝗻:
Identifying new applications and markets is a vital – yet complex – exercise to grow your business. However, many hints are to be discovered in the growing amount of technical and public data. Scout for new markets and playing fields in technical literature. Understand your customers: reveal their hidden needs from context-mining public forums. 

𝗙𝘂𝘁𝘂𝗿𝗲 𝘀𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴:
The plurality of trends doesn’t exactly make it easier to decide on the next big shift for your company. Being able to identify, understand and quantify them helps to build reliable future scenarios and make the right decisions.

Co-Founder / Head of Strategy 

AdEx Partners

I am driving digital projects and transformations with impact for Fortune 500 and mid-market companies, helping teams and organizations to become future-ready.

✓ Designing and building digital units with a purpose to drive innovation.
✓ Executing digital strategy with tangible MVP projects that deliver (AI/ML/Crypto)
✓ Re-shaping business models and co-designing new opportunities. 
✓ Leading and managing the strategy execution with objectives and key results (OKR). 
✓ Defining and shaping organizational culture towards purpose-driven outcomes.

Senior Manager Digital Strategy & Business Model Innovation

Digital Strategy & Transformation

Ernst and Young (EY) is one of the largest professional services firm in the world and one of the "Big Four" accounting firms. EY is committed to building a better working world — with increased trust and confidence in business, sustainable growth, development of talent in all its forms, and greater collaboration. 

▬▬▬▬▬▬▬▬▬▬

As the Manager of People Advisory Services, I enable companies to successfully survive digital disruption and transform their core business towards customer-oriented platform models. Preparing and guiding companies on their journey to build the future of work is part of my passion. My responsibilities include leading teams and driving people strategy topics in global business solution services implementation. This includes applying agile methodology like Design Thinking and Business Model Canvas techniques. 

Driving digital strategy and transformation requires a focus on people capabilities, organizational design and technology. Translating technological development into strategic solutions is necessary for every organization to survive disruption and stay relevant in the digital era. The future of work is shaped by data-driven solutions, robotics and AI, assisting people in every day’s tasks. 

I believe that my organizational and people skills along with my passion for this work make a real difference for my clients.

Manager, Digital Strategy ✦ Transformation and Change ✦ People Advisory Services

Fresenius Group

Fresenius, a German health care company, includes the Fresenius Medical Group as one of its four divisions. Fresenius  provides products and services for dialysis in hospitals and outpatient medical centers. The company also focuses on hospital management as well as on engineering and services for medical centers and other health care facilities.  

▬▬▬▬▬▬▬▬▬▬

As Manager of Strategic Initiatives, I supported the CEO of the European, Middle East and Africa (EMEA) division in the design of strategic transformation processes. This requires translation of the CEO’s agenda into business initiatives and working collaboratively with senior executives to assess their needs and define specific projects. 

The focus of  my work was around the digital transformation of Fresenius Medical Care and its business, co-designing strategy roadmaps, building organizational structure and creating awareness for the requirements to succeed in the 4.0 economy.  

By consolidating insights, leveraging the gathered data and developing best practices, I led the development of strategic options and ensured success of the overall digital initiative.

Initially, I joined Fresenius as a Change Manager for EMEA regions and Communications Officer for the inSITE Project. This project enabled FME to become process-driven, connecting all parts of the organization in the EMEA and Latin America (LA) regions.  Through remote and on-site coaching, I enabled the rollout in 5 countries and positioned 5 others for final transition from a people and organizational perspective. 

The common SAP template delivered harmonized processes and standardized applications based on the demands of the business, while respecting the specific local requirements of each country.

Manager of Strategic Initiatives ✦  Digital Strategist ✦ Change Manager 

University of St. Gallen - HSG

The University of St. Gallen is a research university located in St. Gallen, Switzerland. Established in 1898, it is specialized in the fields of business administration, economics, law, and international affairs.  It is ranked by the Financial Times as one of the top business schools in Europe.

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As the Head of the Military Liaison Office, I improved alignment between the University and the external duties of military personnel. By analyzing existing department activities and documentation, I advised administration and external stakeholders on students evolving needs and obligations. By addressing the unmet needs of the University and students, I effectively reorganized military liaison activities. This work led to harmonized military liaison office processes and IT solutions that conformed to campus standards.  I also facilitated the smooth transition to successive liaisons by creating a support and guidance handbook. 

In addition, I contributed to the development of the Master of Management, Organization Studies and Cultural Theory (MOK) program at the Institute for Systemic Management and Public Governance. In this role, responsibilities include; synthesizing the needs and perspectives of two distinct academic departments, supporting the program director, managing  stakeholder communications, evaluating applications and selected candidates, planning and executing workshops. organizing business partner meetings, preparing course materials and supervising examinations. 

To stimulate interest in new graduate programs for prospects with a passion for impacting organizations, politics and society, I organized and engaged in off-campus programs activities.

My task as a Research Assistant was to perform analysis and visualization of study results for senior researchers.

Head of Military Liaison Office ✦ Research Associate and Program Manager ✦ Research Assistant 

University of Zurich

As the largest university in Switzerland, UZH offers the widest range of subjects and courses of any Swiss higher education institution.

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As a Research Associate, I designed and launched a two-semester talent management program with workshops, seminars, real-world cases and hands-on training. I built relationships with external consulting firms, who worked as experienced consultants and program instructors.  My responsibilities included: teaching undergraduate courses in organization theory, consulting, conducting presentations and supervising students’ final theses. My independent research focused on strategy-as-practice, organizational theory, strategic management and systems theory.

I am especially proud of the following accomplishments:

✓ Recruited the Boston Consulting Group to act as founding member of new talent program and 
    provide funding for campus meeting space

✓ Expanded partner network to include McKinsey, Accenture, AT Kearney and Roland Berger

Research Associate ✦ Program Designer ✦ Organization Theory Educator

AI Strategy Pioneer & Innovation Catalyst | Transforming businesses with AI-driven strategies and digital innovation

Pioneering the AI Revolution & Digital Transformation

Over the last decade, I've guided organizations through the AI revolution and digital transformation, unlocking unprecedented growth.

My mission: Empower hundreds of  businesses with cutting-edge AI and digital strategies.

AI & GenAI Expertise:
→ Developed GenAI solutions for smart industries, boosting productivity by 40%+
→ Crafted AI strategies for Fortune 500 companies, driving innovation
→ Advisor on ethical AI implementation and governance

Digital Transformation Mastery:
→ Led dozens of successful digital transformation projects across industries
→ Transformed traditional business models into data-driven powerhouses
→ Expert in leveraging IoT, Blockchain, and Cloud for business growth

Key Capabilities:
→ AI Strategy Development & Playbooks
→ GenAI Implementation for Industry 4.0 and Lifescience 
→ Digital Transformation Roadmapping
→ Emerging Tech Integration (AR/VR, Metaverse)
→ Digital Leadership Mentoring

Impact Highlights:
→ Reduced operational costs by 30% through AI-driven solutions
→ Increased productivity up to 50% with data-driven tools
→ Built a community of 28,000+ digital leaders and innovators

Ready to harness the power of AI and digital transformation?

Drop me a message!

Bora Ger

2026 won't be the year of AI scale.
It will be the year we learn that scale requires chemistry.

Enterprises will pour billions into AI in 2026.

Most of it will fund expensive shelfware.
The culprit? We're measuring the wrong thing.

Wharton just released their Wave 3 GenAI report:

88% of leaders expect budget increases.
80% expect payoff within 2-3 years.
Enterprise adoption is accelerating.

Their prescription for 2026 success?

"Training, hiring, and rollout approaches are key human capital aspects that need to be addressed."

That's it. 
That's the human-side strategy.

Meanwhile:

→ 95% of AI pilots fail to reach production (MIT)
→ 42% of companies abandoned most AI initiatives this year (S&P Global)
→ 75% of employees lack confidence using AI tools
→ 63% cite human factors as their primary implementation challenge

We keep measuring the technology. We keep ignoring the connection.

Here's what I've learned building AI capability at scale:

The problem isn't adoption --> It's readiness.
The gap isn't training hours --> It's cognitive load.
The failure isn't the model --> It's the friction.

High-performing Human-AI systems share four traits:

𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 that delivers accurate outputs.
𝗧𝗿𝘂𝘀𝘁 that's calibrated—neither blind nor absent.
𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗟𝗼𝗮𝗱 that releases mental bandwidth, not consumes it.
𝗦𝘁𝗿𝗲𝘀𝘀 that stays below the abandonment threshold.

When these align, value compounds.
When they don't, you get shelfware with a budget line.

Measure what matters.

Global AI Capability Lead | Creator of the Human-AI Chemistry Index | Chief AI Strategist @ Global AI Lab: Turning Future Signals into Sovereign Assets

𝗧𝗵𝗲 𝗔𝗜 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗘𝗰𝗼𝗻𝗼𝗺𝘆: 𝗬𝗼𝘂 𝗕𝘂𝗶𝗹𝗱 𝗜𝘁, 𝗧𝗵𝗲𝘆 𝗖𝗼𝗻𝘀𝘂𝗺𝗲 𝗜𝘁

Three numbers that should terrify every content creator:

• 79% CTR drop when AI Overviews appear
• 69% of searches now end without a single click
• 1% of users click links inside AI summaries

The traffic-based internet is dying. 
And AI is writing the obituary.

𝗧𝗛𝗥𝗘𝗘 𝗖𝗔𝗦𝗘 𝗦𝗧𝗨𝗗𝗜𝗘𝗦 𝗧𝗛𝗔𝗧 𝗦𝗛𝗢𝗪 𝗧𝗛𝗘 𝗗𝗔𝗠𝗔𝗚𝗘

1. 𝗦𝘁𝗮𝗰𝗸 𝗢𝘃𝗲𝗿𝗳𝗹𝗼𝘄
Built the knowledge base that trained every coding AI.
Now developers get answers from ChatGPT instead of visiting the site.
Monthly questions are back to 2008 levels.
15 years of community growth erased.

2. 𝗧𝗮𝗶𝗹𝘄𝗶𝗻𝗱 𝗖𝗦𝗦
Became embedded in AI coding tools with 75 million developers downloading it monthly.
But those developers never see Tailwind's website, docs, or paid products.
Revenue down 80%.
Three of four engineers gone.

3. 𝗖𝗹𝗲𝗮𝗻 𝗘𝗮𝘁𝗶𝗻𝗴 𝗞𝗶𝘁𝗰𝗵𝗲𝗻
Spent years perfecting recipes Google now summarizes in search results.
Users get the ingredient list and instructions without clicking through.
80% of traffic vanished.
Ten employees became zero.

𝗧𝗛𝗘 𝗕𝗨𝗦𝗜𝗡𝗘𝗦𝗦 𝗠𝗢𝗗𝗘𝗟 𝗛𝗔𝗦 𝗙𝗟𝗜𝗣𝗣𝗘𝗗

𝗢𝗹𝗱 𝗠𝗼𝗱𝗲𝗹:
Create content → Attract visitors → Monetize attention

𝗡𝗲𝘄 𝗠𝗼𝗱𝗲𝗹:
Create content → AI extracts value → Users never arrive

Your content still gets consumed.
Your value still gets delivered.
Your business just doesn't benefit.

𝗧𝗛𝗜𝗦 𝗜𝗦𝗡'𝗧 𝗔 𝗧𝗘𝗖𝗛 𝗨𝗣𝗗𝗔𝗧𝗘

It's a fundamental restructuring of value flow on the internet.

If your business depends on humans clicking through to your site, you're no longer selling to customers.

You're supplying training data to competitors.

Thanks Robin Jose for the inspiration.

𝗡𝗩𝗜𝗗𝗜𝗔 𝗷𝘂𝘀𝘁 𝗽𝗿𝗼𝘃𝗲𝗱 𝗘𝗹𝗼𝗻 𝗿𝗶𝗴𝗵𝘁.

And every car company is about to feel it.

The Alpamayo announcement at CES wasn't just another self-driving upgrade.
It's the moment autonomy started exposing its "thought process" in ways humans can understand.

Old approach: "If pedestrian detected, then brake."
Alpamayo approach: "That person looks distracted, checking their phone, approaching the crosswalk at an unusual angle. 
I should slow down and prepare for unpredictable movement."

𝗧𝗵𝗮𝘁'𝘀 𝗻𝗼𝘁 𝗵𝗶𝗱𝗱𝗲𝗻 𝗰𝗼𝗱𝗲. 𝗧𝗵𝗮𝘁'𝘀 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗶𝗻𝘀𝗽𝗲𝗰𝘁.

Mercedes-Benz CLA will ship with this technology to handle the complex safety scenarios that break traditional rule-based systems.

𝗛𝗘𝗥𝗘'𝗦 𝗪𝗛𝗬 𝗧𝗛𝗜𝗦 𝗩𝗔𝗟𝗜𝗗𝗔𝗧𝗘𝗦 𝗧𝗘𝗦𝗟𝗔

Vision-heavy, end-to-end learning was always the right bet.
While competitors added more sensors and hand-crafted logic, Tesla doubled down on teaching cars to see and behave like human drivers.

NVIDIA just made Tesla's approach the industry standard.

Autonomy doesn't fail at 80% or 90% accuracy.
It fails at 99%.

That last 1% - the weird edge cases no engineer anticipated - is where reasoning beats rules.

And where human-AI interaction becomes critical.

If the model can explain why it's slowing, swerving, or yielding, humans can debug and improve instead of guessing at a black box.

𝗕𝗨𝗧 𝗡𝗩𝗜𝗗𝗜𝗔'𝗦 𝗥𝗘𝗔𝗟 𝗠𝗔𝗦𝗧𝗘𝗥𝗦𝗧𝗥𝗢𝗞𝗘

They opened Alpamayo as a reasoning stack others can build on - while keeping the best performance bound to their platform.

This is Google's Android playbook for autonomy.

Democratize the software patterns, own the compute underneath.
Every car manufacturer can use the reasoning stack, but the fastest path runs on NVIDIA's hardware and cloud.

While AMD scrambles with Ryzen AI 400 and Samsung promises "AI Living," NVIDIA just positioned itself as the default brain for autonomous vehicles.

𝗣𝗛𝗬𝗦𝗜𝗖𝗔𝗟 𝗔𝗜 𝗜𝗦 𝗧𝗛𝗘 𝗡𝗘𝗪 𝗙𝗥𝗢𝗡𝗧𝗜𝗘𝗥

CES made this clear:
→ Hyundai's humanoid robots moving from showcase to factory floors
→ NVIDIA's Vera Rubin platform scaling beyond vehicles into general robotics
→ Samsung's AI-everywhere vision wiring intelligence into every home device

Your environment is about to get smart.
Not just connected - but filled with systems whose internal logic is increasingly exposed and shaped by humans in real time.

Ray Dalio calls this an AI bubble, but bubbles don't come with hard safety cases and robot fleets operating under physics.

Physical AI is where abstraction ends and interaction with the real world becomes the bottleneck.

Software can scale infinitely.
Physical intelligence has to work in three dimensions, with consequences.

𝗧𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗶𝘀𝗻'𝘁 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝘁𝗵𝗶𝘀 𝗶𝘀 𝗰𝗼𝗺𝗶𝗻𝗴. 

𝗜𝘁'𝘀 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝘆𝗼𝘂'𝗿𝗲 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗳𝗼𝗿 𝗮 𝘄𝗼𝗿𝗹𝗱 𝘄𝗵𝗲𝗿𝗲 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗲𝘅𝗽𝗹𝗮𝗶𝗻𝘀 𝗶𝘁𝘀𝗲𝗹𝗳 𝗯𝗲𝗳𝗼𝗿𝗲 𝗶𝘁 𝗮𝗰𝘁𝘀.

𝗗𝗲𝗲𝗽𝗦𝗲𝗲𝗸 𝗷𝘂𝘀𝘁 𝗱𝗿𝗼𝗽𝗽𝗲𝗱 𝘁𝗵𝗲𝗶𝗿 𝗳𝗶𝗿𝘀𝘁 𝗺𝗮𝗷𝗼𝗿 𝗽𝗮𝗽𝗲𝗿 𝗼𝗳 𝟮𝟬𝟮𝟲.

This paper matters more than DeepSeek-V3 did.

"mHC: Manifold-Constrained Hyper-Connections" isn't just research.
It's DeepSeek's blueprint for building frontier AI on a budget that would embarrass Silicon Valley.

While everyone else throws billions at bigger compute, they're rewriting the efficiency playbook.

Here's what this means for your strategy:

𝗧𝗛𝗘 "𝗢𝗨𝗧𝗦𝗣𝗘𝗡𝗗 𝗧𝗢 𝗪𝗜𝗡" 𝗘𝗥𝗔 𝗜𝗦 𝗢𝗩𝗘𝗥

DeepSeek has access to fewer H100s than OpenAI buys in a week.
Their response? Architectural innovation that makes every chip work exponentially harder.

This paper shows how they're squeezing frontier performance from constrained hardware.
The uncomfortable truth: throwing money at AI problems is becoming a luxury, not a requirement.

𝗧𝗛𝗜𝗦 𝗜𝗦 𝗠𝗢𝗥𝗘 𝗙𝗢𝗨𝗡𝗗𝗔𝗧𝗜𝗢𝗡𝗔𝗟 𝗧𝗛𝗔𝗡 𝗩𝟯 𝗪𝗔𝗦

DeepSeek-V3 proved they could compete on performance.
This paper shows they're rethinking the underlying architecture itself.

Manifold-constrained hyper-connections aren't incremental improvements.
They're a fundamentally different approach to how neural networks learn and scale.

DeepSeek-V3 was the product. This is the engine that powers what comes next.

𝗔𝗜 𝗖𝗔𝗣𝗔𝗕𝗜𝗟𝗜𝗧𝗬 𝗜𝗦 𝗗𝗘𝗖𝗘𝗡𝗧𝗥𝗔𝗟𝗜𝗭𝗜𝗡𝗚 𝗙𝗔𝗦𝗧𝗘𝗥 𝗧𝗛𝗔𝗡 𝗘𝗫𝗣𝗘𝗖𝗧𝗘𝗗

Export controls were designed to create a moat around frontier AI.
Instead, they're accelerating innovation on efficiency.

When you can't outspend competitors, you have to outthink them.
The result: architectural breakthroughs that make expensive compute optional.

𝗧𝗛𝗘 𝗥𝗘𝗔𝗟 𝟮𝟬𝟮𝟲 𝗤𝗨𝗘𝗦𝗧𝗜𝗢𝗡

When capable AI becomes commoditized - and it's happening fast - the strategic advantage shifts.

It's not which model you license.
It's how effectively your organization absorbs AI capability.

This is the Chemistry Index: measuring your human system's readiness to work with AI, not just the AI's power.

Most companies are optimizing for model selection.
Winners in 2026 will optimize for organizational integration.

𝗧𝗵𝗲 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝘀𝘁𝗶𝗹𝗹 𝗱𝗲𝗯𝗮𝘁𝗶𝗻𝗴 "𝗢𝗽𝗲𝗻𝗔𝗜 𝘃𝘀 𝗖𝗹𝗮𝘂𝗱𝗲 𝘃𝘀 𝗚𝗲𝗺𝗶𝗻𝗶" 𝗮𝗿𝗲 𝗵𝗮𝘃𝗶𝗻𝗴 𝗹𝗮𝘀𝘁 𝘆𝗲𝗮𝗿'𝘀 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻.

Start designing systems for AI integration, not AI procurement.

𝗪𝗵𝗮𝘁'𝘀 𝘆𝗼𝘂𝗿 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗳𝗼𝗿: 𝗔𝗜 𝘀𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗿 𝗔𝗜 𝗮𝗯𝘀𝗼𝗿𝗽𝘁𝗶𝗼𝗻?

𝗚𝗼𝗼𝗴𝗹𝗲'𝘀 𝗺𝗼𝗻𝘁𝗵𝘀 𝗼𝗳 𝘄𝗼𝗿𝗸 𝗷𝘂𝘀𝘁 𝗴𝗼𝘁 𝗿𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗲𝗱 𝗶𝗻 𝗼𝗻𝗲 𝗵𝗼𝘂𝗿.

Google Principal Engineer Jaana Dogan dropped this reality check yesterday:

Anthropic's Claude Code generated a distributed agent orchestration system in 60 minutes.

The same problem Google had been working on since last year.

Not perfect. 
But comparable.

And that's before the feedback loop.

Boris Cherny, Claude Code's creator, revealed the multiplier: 
Enable the tool to self-check its work.
That iterative process doubles or triples output quality.

Think about it. 
An AI writing code, then reviewing its own code, then improving it. 
Automatically.

𝗧𝗵𝗶𝘀 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗮 𝗰𝗼𝗼𝗹 𝗱𝗲𝗺𝗼. 𝗜𝘁'𝘀 𝗮 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝘀𝗵𝗶𝗳𝘁.

Your engineering capacity just expanded beyond traditional project planning assumptions.

Complex system architecture that previously required months of senior engineer time? Now takes days.
Proof-of-concept development that consumed entire quarters? Done in weeks.
Technical debt that's been sitting in your backlog for years? Finally addressable.

𝗧𝗵𝗲 𝗻𝗲𝘄 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 𝗶𝘀𝗻'𝘁 𝗰𝗼𝗱𝗶𝗻𝗴 𝘀𝗽𝗲𝗲𝗱.

It's knowing what problems are worth solving.
It's architectural decision-making.
It's understanding how systems integrate with your business logic.

Your best engineers won't be replaced by AI. 
They'll be freed from the grunt work to focus on what actually drives value: strategy, optimization, and solving the edge cases that matter.

That's human-AI chemistry working beautifully in action. 

But this only works if you recalibrate what you expect from your teams.

Stop planning like it's 2023. 
Start asking for solutions that seemed impossible six months ago.

This is the best career advice for you in 2026!

Most will miss out on this. 

And it's only $20 a month.

But this isn't another subscription.
This is the gap between who you are and who you could be.

𝗚𝗲𝗺𝗶𝗻𝗶 𝗣𝗿𝗼 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗮 𝘁𝗼𝗼𝗹. 
𝗜𝘁'𝘀 𝗮 𝘂𝗻𝗳𝗮𝗶𝗿 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲.

→ NotebookLM turns any document into your personal expert
→ Google AI Studio builds apps while you think (no code)
→ 24/7 thinking partner that scales with your ambition (gems)
→ Your ideas become reality faster than ever

While everyone else debates whether AI will replace them, you're using it to become irreplaceable.

While they're waiting for "someday," you're building your future today.

𝗧𝗵𝗲 𝗼𝗻𝗹𝘆 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗶𝘀: 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗴𝗼𝗶𝗻𝗴 𝘁𝗼 𝘂𝘀𝗲 𝗶𝘁?

Because the tools exist.
The price is nothing.
The barrier is your decision.

Stop overthinking. 
Start building.

Of course, you could also use Anthropic Claude. 
Or ChatGPT if you prefer.

The tool doesn't matter.

What matters is that you're taking your AI transformation seriously.

𝗪𝗵𝗮𝘁 𝗰𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗰𝗿𝗲𝗮𝘁𝗲 𝗶𝗻 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝟯𝟬 𝗱𝗮𝘆𝘀?

𝗜'𝘃𝗲 𝗯𝗲𝗲𝗻 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲'𝘀 "𝗔𝗴𝗲𝗻𝘁𝗳𝗼𝗿𝗰𝗲" 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗮𝗹𝗹 𝘆𝗲𝗮𝗿.

And it's the perfect cautionary tale.

January 2025: 
"Agentforce will revolutionize everything! 
Cut FTEs in our own organization! 
Full automation!"

Every few months: 
Another pivot. 
Another press release. 
Another "breakthrough."

December 2025: The turnaround.

Significant pullback from LLM-only agents toward deterministic automation, with LLMs now constrained behind rules and data-driven guardrails. 

The reason? "Reliability concerns and hallucinations."

Executives are now on record: trust in LLMs has declined compared to a year ago, and probabilistic models alone won't run mission-critical operations.


Less than 12 months. 
That's how long it took reality to catch up.

The irony? 

It's called "Agentforce" but they're pivoting from the LLM-based autonomous agents they hyped to deterministic automation.

𝗟𝗲𝘁 𝗺𝗲 𝗯𝗲 𝗰𝗹𝗲𝗮𝗿: 𝗜'𝗺 𝗽𝗿𝗼-𝗔𝗜.

LLMs are fantastic technology when used for the right problems. 
Language understanding, research assistance, content generation, summarization.

But enterprise autonomy? 
Full automation of critical business processes?
That was never realistic pure LLM technology plays.

𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:

Every cycle like this damages legitimate AI adoption:

→ Executives get burned by unrealistic vendor promises
→ Teams become skeptical of actually useful automation  
→ Real AI opportunities get dismissed as "more marketing BS"
→ Budgets get frozen after expensive failures

The shift to hybrid approaches and data foundations? Actually smart. Good for them.

But the reputational damage to enterprise AI is already spreading.

𝗧𝗵𝗲 𝗹𝗲𝘀𝘀𝗼𝗻 𝗳𝗼𝗿 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗲𝗹𝘀𝗲:

Don't just listen to vendors trying to sell you the future.

Talk to someone who actually cares about solving your specific problems, not just pushing the latest shiny product.

𝗛𝗼𝘄 𝗮𝗿𝗲 𝘆𝗼𝘂 𝘀𝗲𝗲𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗽𝗹𝗮𝘆 𝗼𝘂𝘁 𝗮𝘁 𝘆𝗼𝘂𝗿 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻? 𝗠𝗼𝗿𝗲 𝗿𝗲𝗮𝗹𝗶𝘀𝗺 𝗶𝗻 𝗔𝗜 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀, 𝗼𝗿 𝘀𝘁𝗶𝗹𝗹 𝗰𝗵𝗮𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗺𝗶𝗿𝗮𝗰𝗹𝗲?

𝗠𝗧𝗩 𝗷𝘂𝘀𝘁 𝘀𝗵𝘂𝘁 𝗱𝗼𝘄𝗻 𝗶𝘁𝘀 𝗴𝗹𝗼𝗯𝗮𝗹 𝗺𝘂𝘀𝗶𝗰 𝗰𝗵𝗮𝗻𝗻𝗲𝗹𝘀 𝗼𝗻 𝟯𝟭.𝟭𝟮.𝟮𝟬𝟮𝟱.

Their final song? "Video Killed the Radio Star" by The Buggles.

The exact same song that launched MTV on August 1st, 1981.

Technology doesn't just evolve - it cannibalizes itself with poetic precision.

𝗧𝗛𝗘 𝗜𝗥𝗢𝗡𝗬 𝗜𝗦 𝗘𝗩𝗘𝗥𝗬𝗧𝗛𝗜𝗡𝗚

MTV didn't just broadcast music videos. 
It created the template for how each generation of media kills its predecessor while birthing its own replacement.

Video killed radio. 
Streaming killed broadcast. 
Algorithms killed curation.
Each convinced it would be different. 
Each eventually consuming its own relevance.

It's the end of shared cultural gatekeeping and the beginning of personalized cultural isolation.

𝗪𝗛𝗘𝗡 𝗘𝗩𝗘𝗥𝗬𝗢𝗡𝗘 𝗪𝗔𝗧𝗖𝗛𝗘𝗗 𝗧𝗛𝗘 𝗦𝗔𝗠𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟

MTV didn't just show music videos. 
It decided which stories an entire generation experienced together. 

The platform amplified voices that radio systematically ignored.
 It created visual representation for artists who looked different, came from different places, told different stories.

They were curatorial choices with cultural consequence.

𝗙𝗥𝗢𝗠 𝗖𝗨𝗥𝗔𝗧𝗜𝗢𝗡 𝗧𝗢 𝗔𝗟𝗚𝗢𝗥𝗜𝗧𝗛𝗠

Now your next song is determined by data points from your last hundred plays. 
Engagement metrics optimize for retention, not revelation.

Personalized feeds give you more of what you already consume, less of what might challenge or change you. 
Art becomes data. 
Discovery becomes prediction. 
Cultural moments become individual consumption patterns.

We gained infinite choice and lost serendipitous discovery.
We got perfect personalization and lost shared cultural experiences.
We optimized for individual satisfaction and lost collective cultural evolution.

The algorithm doesn't care if you see someone who looks like you succeed. It cares if you stay engaged. There's a difference between giving people what they want and showing them what they need to see.

𝗧𝗛𝗘 𝗥𝗘𝗔𝗟 𝗟𝗢𝗦𝗦

MTV's shutdown isn't about nostalgia for music videos.

It's about the fundamental shift from broadcast culture to algorithmic culture. 
From curators who took creative risks to systems that minimize them. 
From platforms that shaped cultural taste to feeds that reflect it back without challenge.

The Buggles predicted their own obsolescence. 
"Video Killed the Radio Star" was both celebration and eulogy.

But what kills the video? 
Data does. 

And what kills human curation? 
Algorithmic optimization does.

Technology doesn't just change how we consume culture. 
It determines whose culture gets consumed, whose stories get amplified, whose art gets discovered.

We're not just changing how we find music. 
We're changing how culture finds us.

Your best tech translators didn't grow up with smartphones.

They grew up in the '90s.
And that's exactly why they matter.

In the rush to modernize, organizations often overlook their most valuable asset for navigating change: 
the generation that lived through the analog-to-digital shift.

They aren't just "digital natives".
They are digital immigrants. 
And that distinction matters.

Because they straddle the divide between the analog and digital worlds, they possess a unique duality that makes them the perfect translators for technology's impact on society and business:

𝗧𝗵𝗲𝘆 𝗛𝘂𝗺𝗮𝗻𝗶𝘇𝗲 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: 
Having lived through the transition, they understand that technology should serve the human experience, not replace it. 
They know the value of "unplugged" presence in a hyper-connected culture.

𝗧𝗵𝗲𝘆 𝗠𝗮𝘀𝘁𝗲𝗿 𝗗𝗲𝗹𝗮𝘆𝗲𝗱 𝗚𝗿𝗮𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: 
Raised in an era where you had to wait for rewards (like saving for a CD or waiting for a show), they bring patience and long-term vision to a business world obsessed with instant results.

𝗧𝗵𝗲𝘆 𝗕𝘂𝗶𝗹𝗱 𝗥𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝘁 𝗖𝘂𝗹𝘁𝘂𝗿𝗲𝘀: 
They learned resourcefulness before Google existed. 
This makes them adaptable problem-solvers who can navigate ambiguity without a roadmap.

The '90s generation doesn't just use technology.
They understand its context, its cost, and its limits.

In an era obsessed with speed, they're the ones who remember that sustainable transformation requires rhythm, not just velocity. 
And that connection, not just connectivity, is what moves organizations forward.

If you're leading change, don't just hire digital natives. 
Find the translators who speak both languages.

𝗧𝗵𝗲 𝗪𝗼𝗿𝗹𝗱 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗙𝗼𝗿𝘂𝗺 𝗷𝘂𝘀𝘁 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 "𝗖𝗼𝗿𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 𝗳𝗼𝗿 𝟮𝟬𝟯𝟬" 𝗿𝗲𝗽𝗼𝗿𝘁.

And it's almost entirely useless.

Analytical thinking. Resilience. Creative problem-solving. Leadership.

Pull a Harvard Business Review from 1985. 
Or 1995. 
Or 2005. 
Same skills, slightly different vocabulary.

𝗧𝗵𝗲𝘀𝗲 𝗿𝗲𝗽𝗼𝗿𝘁𝘀 𝗮𝗿𝗲 𝗰𝗼𝗺𝗺𝗼𝗻 𝘀𝗲𝗻𝘀𝗲 𝗿𝗲𝗽𝗮𝗰𝗸𝗮𝗴𝗲𝗱 𝗮𝘀 𝗳𝗼𝗿𝗲𝘀𝗶𝗴𝗵𝘁.

The quadrant chart looks impressive. 
The data suggests rigor. 
But when was analytical thinking ever 𝘯𝘰𝘵 important? 
When did organizations say "we don't need adaptable people"?

Never.

𝗪𝗵𝗮𝘁'𝘀 𝗿𝗲𝗮𝗹𝗹𝘆 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴:

→ Consulting firms need content that generates citations
→ Executives need frameworks to justify training budgets  
→ "The WEF says" carries more weight than "obviously"

𝗧𝗵𝗲 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝘁𝗿𝘂𝘁𝗵:

Organizations have been told for decades to hire for adaptability. 
Most still hire for credentials and optimize for compliance. 
Another quadrant chart won't change that.

𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻:

It's not 𝘸𝘩𝘢𝘵 skills matter—that list hasn't changed in 50 years.

It's: how do you actually build organizational readiness for human-AI collaboration? 

How do you measure and develop it at scale?

That's harder. It doesn't fit in a 2x2 matrix. 
And it requires actual work, not another PDF.

Stop consuming reports that tell you what you already know.

Start building systems that develop what your people actually need.

𝗪𝗵𝗮𝘁'𝘀 𝘆𝗼𝘂𝗿 𝘁𝗮𝗸𝗲—𝗱𝗼 𝘁𝗵𝗲𝘀𝗲 "𝗳𝘂𝘁𝘂𝗿𝗲 𝘀𝗸𝗶𝗹𝗹𝘀" 𝗿𝗲𝗽𝗼𝗿𝘁𝘀 𝗮𝗱𝗱 𝘃𝗮𝗹𝘂𝗲, 𝗼𝗿 𝗷𝘂𝘀𝘁 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝘁𝗵𝗲 𝗼𝗯𝘃𝗶𝗼𝘂𝘀?

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