On this day in 2009, Satoshi Nakamoto mined the first block of Bitcoin. Buried deep within the coinbase parameter was a hex-encoded string that decoded to a stark headline from The Times:
“Chancellor on brink of second bailout for banks.”
It was a timestamp, but it was also a mission statement. It signaled the shift from opaque centralized finance to a system defined by absolute mathematical transparency.
Yet, nearly two decades later, I still hear people challenge the “vagueness” of blockchain.
My response is always the same: Read the “Bitcoin: A Peer-to-Peer Electronic Cash System” whitepaper.
It is only 9 pages long.
It’s not vague; it is a masterclass in transparency. If you read it, you understand that the “vagueness” exists only in the commentary, not the code.
The same logic applies to the current wave of AI skepticism.
I constantly see posts mocking LLMs because a chatbot couldn’t solve a simple math problem or hallucinated a fact. “It’s broken,” they say.
My response? Read the “Attention Is All You Need” whitepaper.
If you understand the architecture, you understand that these models are probabilistic next-token predictors, not deterministic calculators. When you ask a language model to do strict arithmetic, you are essentially asking a creative writer to do your accounting.
It comes down to this:
🔹 Bitcoin is the right tool for trustless, transparent value transfer.
🔹 LLMs are the right tool for pattern matching, summarization, and generation.
The tools aren’t broken. We just have to stop trying to use a screwdriver to hammer in a nail.
We are rapidly hitting the natural ceiling of the “chatbot era.”
For the last three years, the dominant AI strategy has been refining human-to-machine conversation. We’ve built better models and smoother interfaces, essentially trying to make software “talk” like a human. We have automated the retrieval and summarization of information.
But as we look toward 2026, simply making AI talk better won’t generate competitive advantage. To understand the necessary strategic pivot, consider this insight from Paulo Coelho:
For centuries, humans failed to fly because we were obsessed with flapping wings. We thought flight meant mimicking nature. We only succeeded when we stopped imitating birds and built fixed wings and engines—mechanisms that looked different but achieved the outcome of flight far more effectively.
Right now, many enterprises are still flapping their wings.
We are forcing complex business processes into chat interfaces. While useful for triage, the chat box is a bottleneck for true cognitive work. It mimics human interaction, rather than leveraging machine speed and scale.
𝟐𝟎𝟐𝟔: 𝐓𝐡𝐞 𝐄𝐫𝐚 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐠𝐞𝐧𝐭
If the current phase is imitation, 2026 is about flight. The strategic advantage will shift from Conversational Bots to Autonomous AI Agents.
The difference is the move from imitation to agency:
🔹 𝐓𝐡𝐞 𝟐𝟎𝟐𝟒 𝐂𝐡𝐚𝐭𝐛𝐨𝐭 tells you the steps required to fix a supply chain disruption. It chats with you about the problem.
🔹 𝐓𝐡𝐞 𝟐𝟎𝟐𝟔 𝐀𝐠𝐞𝐧𝐭 detects the delay, re-routes the shipment, updates the ERP, and simply asks for your final sign-off.
The future isn’t a better chat interface; it is cognitive orchestration.
𝐓𝐡𝐞 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐌𝐚𝐧𝐝𝐚𝐭𝐞
To prepare for 2026, stop asking, “How can we add a chat interface to this workflow?”
Start asking, “If we stop imitating human conversation, what outcomes can we empower an agent to execute autonomously?”
2025 has been a year of AI explosion, and honestly, it is a lot to keep up with. Every week brings a wave of new research papers, industry newsletters, blog posts, benchmark reports, and endless social media feeds.
With so much noise, finding time for long-form reading, both AI and non-AI books, has become a challenge. To stay ahead, I’ve developed a new routine: every Saturday, I upload my “must-read” papers and newsletters to Google NotebookLM. I generate an Audio Overview and consume it as a podcast during my Sunday morning jog. It’s the perfect way to complete my “reading” while staying active!
Despite the busy year, I managed to finish 7 books. While many are talking about Nexus by Yuval Noah Harari as the standout, my personal favorite was The Mysterious Mr. Nakamoto by Benjamin Wallace – a fascinating 15-year quest to unmask the genius behind crypto.
Nexus by Yuval Noah Harari – A compelling read that serves as excellent evidence that long-form reading remains vital.
The Singularity Is Nearer by Ray Kurzweil – For those working in the IT / AI industry, this is a must-read.
The Sweaty Startup by Nick Huber – This serves as a great companion to the book The E-Myth, which I first read nearly 30 years ago.
Make Meaningful Culture by Daniel Szuc & Josephine Wong – In the era of AI, fostering a meaningful team culture has become more vital than ever.
The Secret of Secrets by Dan Brown – I have read all of Dan Brown’s books, and this one is quite good as well.
Storyboarding Essentials by David Harland Rousseau & Benjamin Reid Phillips – I chose to read this not for filmmaking, but to improve my skills in crafting more effective video prompts.
How are you tackling your reading list this year? Any AI tools helping you stay productive?
Christmas is around the corner and it’s about time to create my 2026 reading list.
I used to rely on the “Customers who bought this also bought that” feature. While efficient, it has a significant downside: homogenization.
Algorithms tend to feed us more of what we already know. If we all rely on the same suggestion engine, we end up reading the same books and thinking the same thoughts.
That’s not discovery; that’s reinforcement.
To find truly fresh ideas, I go offline. Before I download anything to my Kindle, I tour physical bookstores – specifically the Translated Books section.
The Logic:
If a local publisher is willing to acquire rights, pay for translation, and print physical copies, that book has passed a rigorous vetting process. It implies the content is valuable enough to justify significant financial risk outside its home market.
I browse the shelves to find these gems, then head home and buy the original English versions for my eReader.
It’s a powerful strategy that hasn’t failed me yet. How do you prepare your reading list?
M.Y. Lessons Learnt 