ARTIFICIAL INTELLIGENCE
An AI-native strategy firmGlobal Advisors: a consulting leader in defining quantified strategy, decreasing uncertainty, improving decisions, achieving measureable results.
A Different Kind of Partner in an AI World
AI-native strategy
consulting
Experienced hires
We are hiring experienced top-tier strategy consultants
Quantified Strategy
Decreased uncertainty, improved decisions
Global Advisors is a leader in defining quantified strategies, decreasing uncertainty, improving decisions and achieving measureable results.
We specialise in providing highly-analytical data-driven recommendations in the face of significant uncertainty.
We utilise advanced predictive analytics to build robust strategies and enable our clients to make calculated decisions.
We support implementation of adaptive capability and capacity.
Our latest
Thoughts
Podcast – The Real AI Signal from Davos 2026
While the headlines from Davos were dominated by geopolitical conflict and debates on AGI timelines and asset bubbles, a different signal emerged from the noise. It wasn’t about if AI works, but how it is being ruthlessly integrated into the real economy.
In our latest podcast, we break down the “Diffusion Strategy” defining 2026.
3 Key Takeaways:
- China and the “Global South” are trying to leapfrog: While the West debates regulation, emerging economies are treating AI as essential infrastructure.
- China has set a goal for 70% AI diffusion by 2027.
- The UAE has mandated AI literacy in public schools from K-12.
- Rwanda is using AI to quadruple its healthcare workforce.
- The Rise of the “Agentic Self”: We aren’t just using chatbots anymore; we are employing agents. Entrepreneur Steven Bartlett revealed he has established a “Head of Experimentation and Failure” to use AI to disrupt his own business before competitors do. Musician will.i.am argued that in an age of predictive machines, humans must cultivate their “agentic self” to handle the predictable, while remaining unpredictable themselves.
- Rewiring the Core: Uber’s CEO Dara Khosrowshahi noted the difference between an “AI veneer” and a fundamental rewire. It’s no longer about summarising meetings; it’s about autonomous agents resolving customer issues without scripts.
The Global Advisors Perspective: Don’t wait for AGI. The current generation of models is sufficient to drive massive value today. The winners will be those who control their “sovereign capabilities” – embedding their tacit knowledge into models they own.
Read our original perspective here – https://with.ga/w1bd5
Listen to the full breakdown here – https://with.ga/2vg0z
Strategy Tools
Strategy Tools: The 7S Framework – A Comprehensive Guide
By John Khova Global Advisors digital consultant Introduction The McKinsey 7S Framework is one of the most enduring and widely recognised management models in strategic consulting and organisational design. It posits that organisational effectiveness depends not on...
Fast Facts
Fast Fact: Great returns aren’t enough
Key insights
It’s not enough to just have great returns – top-line growth is just as critical.
In fact, S&P 500 investors rewarded high-growth companies more than high-ROIC companies over the past decade.
While the distinction was less clear on the JSE, what is clear is that getting a balance of growth and returns is critical.
Strong and consistent ROIC or RONA performers provide investors with a steady flow of discounted cash flows – without growth effectively a fixed-income instrument.
Improvements in ROIC through margin improvements, efficiencies and working-capital optimisation provide point-in-time uplifts to share price.
Top-line growth presents a compounding mechanism – ROIC (and improvements) are compounded each year leading to on-going increases in share price.
However, without acceptable levels of ROIC, the benefits of compounding will be subdued and share price appreciation will be depressed – and when ROIC is below WACC value will be destroyed.
Maintaining high levels of growth is not as sustainable as maintaining high levels of ROIC – while both typically decline as industries mature, growth is usually more affected.
Getting the right balance between ROIC and growth is critical to optimising shareholder value.
Selected News
Quote: Andrej Karpathy – Previously Director of AI at Tesla, founding team at OpenAI
“Programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You’re spinning up AI agents, giving them tasks in English and managing and reviewing their work in parallel.” – Andrej Karpathy – Previously Director of AI at Tesla, founding team at OpenAI
This statement captures a pivotal moment in the evolution of software development, where traditional coding practices are giving way to a new era dominated by AI agents. Spoken by Andrej Karpathy, a visionary in artificial intelligence, it reflects the rapid transformation driven by large language models (LLMs) and autonomous systems. Karpathy’s insight underscores how programming is shifting from manual code entry to orchestrating intelligent agents via natural language, marking the end of an era that began with the earliest computers.
About Andrej Karpathy
Andrej Karpathy is a leading figure in AI, renowned for his contributions to deep learning and computer vision. A founding member of OpenAI in 2015, he played a key role in pioneering advancements in generative models and neural networks. Later, as Director of AI at Tesla, he led the Autopilot vision team, developing autonomous driving technologies that pushed the boundaries of real-world AI deployment. Today, he is building Eureka Labs, an AI-native educational platform. His talks and writings, such as ‘Software Is Changing (Again),’ articulate the shift to ‘Software 3.0,’ where LLMs enable programming in natural language like English.123
Karpathy’s line struck a nerve because it didn’t describe a distant future. It sounded like a description of what many engineers were already starting to experience in early 2026. The shift he’s talking about is less about writing code and more about orchestrating work—breaking problems into pieces, describing them in plain language, and then supervising agents that actually execute them.
The February Leap: Codex 5.2 and Claude Code
What made this moment feel like a real inflection was the quality jump in early 2026. When tools like ChatGPT Codex 5.2 and Claude Code landed in February, they weren’t just “better autocomplete.” They could stay on task for long, multi?step workflows, recover from errors, and push through the kind of friction that used to send developers back to the keyboard.
Karpathy has described this himself: coding agents that “basically didn’t work before December and basically work since,” with noticeably higher quality, long?term coherence, and tenacity. The February releases crystallised that shift. What used to be a weekend project became something you could kick off, let the agent run for 20–30 minutes, and then review—all while thinking about the next layer of the system rather than the syntax of the current one.
A New Kind of Programming Workflow
The pattern Karpathy is describing is less “pair programming with an autocomplete” and more “manager?style delegation.” You frame a task in English, give the agent context, tools, and constraints, and then let it run multiple steps in parallel—installing dependencies, writing tests, debugging, and even documenting the outcome. You then review outputs, steer the next round, and gradually refine the agent’s instructions.
This isn’t a replacement for engineering judgment. It’s a layer on top: your job becomes decomposing work, defining what success looks like, and deciding which parts to hand off and which to keep close. The “productivity flywheel” turns faster when you can treat the agent as a high?leverage assistant that can keep going while you move up the stack.
Software 3.0, In Practice
Karpathy has long framed this as Software 3.0—the evolution of programming from:
-
Software 1.0: explicit code written in languages like C++ or Python, where the programmer spells out every step.
-
Software 2.0: neural networks trained on data, where the “program” is a dataset and training objective rather than a long list of rules.
-
Software 3.0: natural?language?driven agents that compose systems, debug problems, and manage long?running workflows, while still relying on 1.0 and 2.0 components underneath.
The February releases of Codex 5.2 and Claude Code made Software 3.0 feel tangible. It’s no longer a thought experiment; it’s something practitioners can use today for tasks that are well?specified and easy to verify—infrastructure setup, data pipelines, internal tooling, and boilerplate?heavy workflows.
What This Means for Practitioners
The implication isn’t that “everyone will be a programmer.” It’s that the nature of programming is changing. The most valuable skills are no longer just fluency in a language, but:
-
Decomposing complex work into agent?friendly tasks,
-
Designing interfaces and documentation that models can use effectively,
-
Building feedback loops and guardrails so agents can operate safely, and
-
Knowing when to lean in (complex, under?specified logic) and when to lean out (repetitive, well?structured work).
Karpathy’s point is that the default workflow is no longer “you write code line by line.” The era where the editor is the center of the universe is ending. Programming is becoming less about keystrokes and more about direction, oversight, and iteration—with AI agents as the new layer of execution in between.
Leading Theorists and Influences
Karpathy’s views draw from pioneers in AI and agents. Ilya Sutskever, his OpenAI co-founder, advanced sequence models like GPT, enabling natural language programming. At Tesla, Ashok Elluswamy and the Autopilot team influenced his emphasis on human-AI loops and ‘autonomy sliders.’ Broader influences include Andrew Ng, under whom Karpathy studied at Stanford, popularising deep learning education, and Yann LeCun, whose convolutional networks underpin vision AI. Recent agentic work echoes Yohei Nakajima’s BabyAGI (2023), an early autonomous agent framework, and Microsoft’s AutoGen for multi-agent systems. Karpathy positions agents as a new ‘consumer of digital information,’ urging infrastructure redesign for LLM autonomy.123
Implications for the Future
This shift promises unprecedented productivity but demands new skills: fluency across paradigms, agent management, and ‘applied psychology of neural nets.’ As Karpathy notes, ‘everyone is now a programmer’ via English, yet professionals must build for agents – rewriting codebases and creating agent-friendly interfaces. With LLM capabilities surging by late 2025, 2026 heralds a ‘high energy’ phase of industry adaptation.14
References
1. https://www.businessinsider.com/agentic-engineering-andrej-karpathy-vibe-coding-2026-2
2. https://www.youtube.com/watch?v=LCEmiRjPEtQ
3. https://singjupost.com/andrej-karpathy-software-is-changing-again/
4. https://paweldubiel.com/42l1%E2%81%9D–Andrej-Karpathy-quote-26-Jan-2026-
5. https://www.christopherspenn.com/2024/07/mind-readings-generative-ai-as-a-programming-language/
6. https://www.ycombinator.com/library/MW-andrej-karpathy-software-is-changing-again
7. https://karpathy.ai/tweets.html
Polls
What determines your success?
We need your help!
We’re testing how people think about their successes and failures. It would be great if you would take 2 minutes to give a simple multiple choice answer and share the poll with your friends.
Take the poll – “What determines your success?”
Then read So You Think You’re Self Aware?
Services
Global Advisors is different
We help clients to measurably improve strategic decision-making and the results they achieve through defining clearly prioritised choices, reducing uncertainty, winning hearts and minds and partnering to deliver.
Our difference is embodied in our team. Our values define us.
Corporate portfolio strategy
Define optimal business portfolios aligned with investor expectations
BUSINESS UNIT STRATEGY
Define how to win against competitors
Reach full potential
Understand your business’ core, reach full potential and grow into optimal adjacencies
Deal advisory
M&A, due diligence, deal structuring, balance sheet optimisation
Global Advisors Digital Data Analytics
14 years of quantitative and data science experience
An enabler to delivering quantified strategy and accelerated implementation
Digital enablement, acceleration and data science
Leading-edge data science and digital skills
Experts in large data processing, analytics and data visualisation
Developers of digital proof-of-concepts
An accelerator for Global Advisors and our clients
Join Global Advisors
We hire and grow amazing people
Consultants join our firm based on a fit with our values, culture and vision. They believe in and are excited by our differentiated approach. They realise that working on our clients’ most important projects is a privilege. While the problems we solve are strategic to clients, consultants recognise that solutions primarily require hard work – rigorous and thorough analysis, partnering with client team members to overcome political and emotional obstacles, and a large investment in knowledge development and self-growth.
Get In Touch
16th Floor, The Forum, 2 Maude Street, Sandton, Johannesburg, South Africa
+27114616371