Nine things that really, really shouldn’t be use cases for AI. Delivered by slowly dismantling a bad idea like it’s a poorly constructed IKEA wardrobe. Rant about bourgeois nonsense with surreal fury. Explain why the whole thing is politically ridiculous. Just stare at the absurdity until it cracks. This is like Marnie Listicle Barr on crack.
Top 5 Trends Shaping the Future of Data, Analytics, and AI Leadership in 2026
I’ve had the privilege of leading a groundbreaking global study in partnership with a strategic client. During this study, I spoke with many key Chief Data Officers (CDOs). I also engaged with Chief Data & Analytics Officers (CDAOs) and AI executives across industries and geographies. The insights reveal how organisations are changing their data and AI strategies. They aim to drive real business value in an increasingly complex world.
The Rise of the Digital Minions: Why Agentic AI is the Tech World’s Latest Obsession
In the hushed corridors of Davos-style summits, one phrase has become inescapable. Agentic AI also dominates discussions in the feverish demo halls of San Francisco conferences.
Aquí presentamos a 12 influencers tecnológicos frecuentemente criticados por difundir publicidad exagerada. Son conocidos por prometer plazos exagerados y por difundir narrativas poco realistas sobre IA, big data, computación cuántica y campos relacionados. Clasificados de forma general por notoriedad e impacto en la actual era de “reacción exagerada” de 2025.
Here are 12 tech influencers who are frequently criticised for spreading hype. They are known for overpromising timelines and for peddling unrealistic narratives about AI, big data, quantum computing, and related fields. Ranked loosely by notoriety and impact in 2025’s ongoing “hype backlash” era.
Oh, right, so… I’ve been asked to have a look at this article, haven’t I? This piece by Bernard Fa – Bernard Fa, yeah? Bernard is the futurist and the influencer. He advises Fortune 500 companies on how to turn data into gold or whatever it is they do these days. And he’s written this thing called “5 Powerful AI Kickers That Can Boost Any Stupid Business Idea”. Dated 2 June 1956, which is… well, that’s in the future from when most of us are living, but apparently not for Bernard. Bernard’s already there, living in 1996, sipping his AI-brewed coffee, watching the robots do the heavy lifting.
And the article starts… it starts like this: “So you’ve got a great business idea. It’s a start…” A start. A start. As if having an idea is some kind of achievement in itself.
A Dozen Data Wishes for Christmas 2025 — and a Sharper, Smarter New Year
As 2025 winds down, the tinsel comes out. It’s tempting to imagine a quieter, saner digital ecosystem on the horizon. Call it festive optimism or a data professional’s annual catharsis. Here are twelve wishes for 2026. They are equal parts hard-edged realism, FT Weekend reflection, and Wired-grade futurism.
Oh, brilliant. Gather round, comrades. It’s time for another installment of “Tech Executives Discover That Computers Need Electricity.” This time, they’ve dressed it up in a shiny frock and called it “2026 Data Trends.” Christ almighty, where do we even start?
By Martyn Rhisiart Jones For Energy Unplugged – a Cambriano partner
Walk through any tech conference today, and you can feel it: the hum of inevitability. AI will cure diseases. It will drive cars and write novels. AI will run governments. If you believe the BS booth graphics, it will probably solve loneliness, too.
The problem is, we’ve been here before.
Artificial intelligence has been promising to change everything since the 1950s. And every decade or so, we rediscover the same fundamental truth: machines don’t magically create wisdom. They just scale whatever understanding, or misunderstanding, we feed them.
I know this because I spent years building the early stuff. Neural networks, parallel distributed processing, and automatic feature extraction. The “deep learning” of 1987 with less RAM and worse haircuts. The technology was exciting, even miraculous. But back then, as now, it struggled to live up to the grand claims that surrounded it.
Darlings, it’s December 2025 and the party is now officially sweaty. The champagne has gone warm. Someone’s been sick in the ficus. The DJ is playing the same four AI remixes on loop. He is frantically checking the fire exits. Here is your updated field guide to the seven trends. These were going to “reshape humanity.” Now they are mostly reshaping venture capitalists’ therapy bills.
Imagine the stage is almost completely dark. One spotlight, maybe two. Our favourite standup philosopher stands perfectly still for eight full seconds. He just breathes through his nose. It’s like a man who’s just found a half-eaten kebab in his coat pocket from 2009. Then, very slowly, he begins.
Thank you… thank you for coming… to our Good Strat and LinkedIn dog and pony show.
Martyn Rhisiart Jones, Sir Afilonius Rex, Lile de Alba and our agentic intelligent actor, Selina Savant.
Spain, 6th December 2025.
The Logic Layer: Why Old-School Rules Are the New Guardrails for Generative AI
A hybrid renaissance is quietly rewriting the future of trustworthy artificial intelligence. The great folks here at Good Strat humbly champion this movement. In the fevered race to build ever-larger language models, a counterintuitive truth has begun to emerge from the labs. Surprisingly, sometimes the best way to make AI smarter is to shackle it with centuries-old logic. Modus ponens is that dusty Latin phrase from Aristotelian syllogism (“if P then Q; P, therefore Q”). It is enjoying an unexpected second act. It has become one of the most promising tools for keeping generative AI honest. It helps make AI coherent and, dare one say, responsible.
The Emergence of Goal-Directed Autonomous AI Systems: An Evidence-Based Enterprise Framework
Sir Horatio Pollox with the collaboration of Martyn Rhisiart Jones, Lila de Alba and Sir Afilonius Rex
London, Paris, New York and A Coruña, 5th December 2025
Autonomous AI agents are goal-directed systems. They show planning, tool-use, long-horizon reasoning, and continuous execution. This signifies a phase transition in the capabilities of artificial intelligence.
Recent benchmarking (e.g., GAGA-MAGA, GAIA&GAIA, WebSerena, and AgentBotch) shows state-of-the-art agents now outperform human baselines on multi-step, real-world tasks by margins exceeding 1040 %.
There’s a moment in every hype cycle when reality taps the industry on the shoulder and whispers, “This isn‘t working.“ And every time that moment arrives, tech responds with the grace of a cornered raccoon.
It’s not your obedient chatbot anymore. It’s a proactive and goal-driven system. It plans and reasons. It uses tools like browsers, APIs, and code editors. It keeps working until the job is done. Often, it requires zero human hand-holding.
Think: a tireless, hyper-competent underling who takes care of everything. They book your Provençal villa and negotiate the rate. They also curate restaurants and arrange transfers, all while you’re already on the rosé.
Agentic AI refers to advanced AI agents. They are capable of independently chasing ambitious, open-ended objectives. These agents break tasks into steps and reason iteratively. They wield tools and persist through obstacles with minimal human guidance. In summary: think of a less obedient tucan. Imagine a more relentlessly competent understudy. This AI can orchestrate your travel, chase invoices, or conduct desk research. It does all this while you’re on the Amalfi Coast with an Aperol spritz. The phrase du jour in Palo Alto marks a shift. Assistants move from being responsive to becoming genuinely proactive. Your to-do list may soon sort itself out as if by magic.
Martyn Rhisiart Jones and the GoodStrat Editorial Team (Alex S., Marcus S., Stewart L., Dawn F., Jenny S.)
Brussels, EU, 14th November, 2025
As 2026 creeps in, it resembles a broken-down delivery robot experiencing hallucinations of depression and dread. The big tech news isn’t flashy new features. Bells and whistles, and bullshit aren’t prominent anymore. Instead, AI has quietly infiltrated everything. It’s like mould, cynicism and cheap furniture in a rental apartment. Suddenly, it’s “infrastructure.” This is what people say when they mean, “We can’t get rid of it now.” Even if it starts insulting customers, peeing on the C-suite carpet, and revealing the fraud of our makers.
Suppose you enjoy, abhor or are simply bored with the massive surfeit of hype surrounding degenerative AI. In that case, you might just hate these less-than-faithful quotes as well.
If you enjoy one or two of the quotes, well, then that’s an acceptable bonus too.
The world of generative AI is full of definitions, terms, buzzwords and monikers. Here are the definitions for twelve of the most important, pertinent and impressive terms found in the fantastic, exciting and revolutionary field. Enjoy the ride!
Move over, data scientists, those earnest souls hunched over Jupyter notebooks, nursing lukewarm flat whites and dreaming of p-values. The new aristocrats of the algorithm have arrived, and they speak in barely audible breaths. Whispering AI specialists, the hushed virtuosos who coax meaning from murmurs, have quietly annexed the crown once worn by the “sexiest job of the 21st century”. (Apologies to Harvard Business Review; even the sexiest jobs suffer from inflationary pressures.)These soft-spoken savants are not merely surviving the generative-AI rollercoaster; they are redesigning the ride, adding velvet restraints and mood lighting. To avoid being flung into the souvenir shop of obsolescence, you must master ten career-extending hacks. Consider them the conversational equivalent of whispering sweet nothings into a supercomputer’s ear: intimate, precise, and oddly lucrative.
Every age has its prophets. The Victorians had their mesmerists, the 1990s had their dot-com futurists, the 2000s had our wacky and dishonest Big Data clowns, and we — lucky us — have our AI influencers, the brave souls who can turn a prompt into a keynote, a hallucination into a business model, and a buzzword into a lifestyle.