(The scene opens on a dimly lit stage. ALFIE SWEARY stomps out, wearing a suit two sizes too small, sweating profusely. He is shouting.)
ALFIE SWEARY: ALRIGHT! SETTLE DOWN, YOU BUNCH OF SYCOPHANTIC MIDDLE-MANAGEMENT YOGURT-KNITTERS!
I’ve just been reading LinkedIn. Or as I call it, “The Digital Dementors’ Circle Jerk.” And I came across a post by a man called Barnaby Muck. A “Business Futurist.” What a job that is, eh? “Business Futurist.” It’s what you tell the police you are when they find you lurking outside a Dixon’s at 3 AM with a soldering iron and a look of existential dread!
THE COMING DIGITAL LOCUSTS: Why Your Pathetic ‘Enterprise Solutions’ Are Just Seasoning for the AI Swarm
Martyn Rhisiart Jones, Sir Afilonius Rex and a man who once shared a corridor with a fellow who briefly tutored a junior cabinet minister at Balliol, and who is currently vibrating with the righteous, Scouse-infused fury of a man who’s just seen the price of a sourdough loaf in Islington.
Martyn Rhisiart Jones, Thursday of Mysteries, 2nd April 2026
El Jueves y la Puta Mili
Oh, sweet suffering Jesus on a blockchain, here we go again with the latest sermon from the Church of AI Salvation.
Bunty Bower, that internationally bestselling author, keynote speaker, futurist, and professional tomorrow-peddler, has once more floated down from the LinkedIn heavens to bless us with his wisdom: fraud doesn’t just pop up like a surprise erection at the exact moment someone taps “pay.” No, no, no. It leaves clues, darling. Hidden signals. Whispered portents. Like a conspiracy theorist who’s discovered the radical concept of “things happen before other things.”
Martyn Rhisiart Jones, Madrid, mercredi 25 mars 2026
Ah, le 25 mars 2026, le soleil brille, les croissants de Snowflake sont délicieux, et une autre prophétesse LinkedIn est apparue pour nous gratifier de son dernier rapport, fruit de son expertise. Merci, cher lecteur, d’être tombé sur « Les agents spéciaux IA sont sur le point de révolutionner les jeux vidéo et la mutilation », signé par l’incomparable Bernie Barr, futuriste de renommée mondiale, véritable aimant à quatre-vingts millions d’abonnés, et auteure d’une quantité impressionnante de livres sur l’IA.
Martyn Rhisiart Jones, Madrid, miércoles 25 de marzo de 2026
Ah, 25 de marzo de 2026, el sol brilla, los croissants de Snowflake están deliciosos y otro profeta de LinkedIn ha aparecido para bendecirnos con su último informe desde la cima del liderazgo intelectual. Gracias, querido lector, por toparse con «Los agentes especiales de IA están a punto de cambiar los videojuegos y las mutilaciones para siempre», de la inigualable Berneice Barr, futurista de renombre mundial, imán de ochenta millones de seguidores y mujer que ha escrito más libros sobre IA que la mayoría de la gente ha comido una comida caliente.
Martyn Rhisiart Jones, Madrid, Friday 27th March 2026
Warehousing Your Data: A No-Nonsense Guide to the Right DBMS in 2026
Listen, you glorious data martyrs. You noble sufferers who have spent far too many evenings coaxing historical rows into slowly changing dimension tables while the rest of the office has gone home to sensible lives. You know the drill. The star schema looks perfect on paper, the fact table is append-only and cooperative, but then someone asks for last year’s corrected customer segments. Suddenly, your backfill script is performing open-heart surgery on a live production warehouse.
In 2026, vendors are still shouting about infinite scalability and “agentic AI” (whatever that means this week), but what actually matters is a system that lets you shove yesterday’s data into those dimension objects without it feeling like a hostage negotiation.
I have been asked to examine the most appropriate database management systems for effective data warehousing, with particular attention to the pain of backfilling dimensional tables. The brief is clear: functionality, reliability, scalability, extensibility, maintainability, performance, cost, ease of use, and a total lack of corporate nonsense.
Cortex Code: The Agentic Reckoning, Or, How Snowflake Finally Gave Data Engineers a Break from Their Existential Crisis (Now With 300% More Technical Guts)
Martyn Rhisiart Jones, Madrid, Thursday 26th March 2026
Yesterday I attended Snowflake’s breakfast date in Madrid, and here are some of the great things I learned. So, without more ado…
Listen up, you glorious data martyrs, you noble sufferers who’ve spent years knee-deep in the festering swamp of undocumented ETL pipelines, chasing lineage graphs that resemble a deranged spider on acid after a three-day bender, and muttering dark incantations at 3 a.m. because some crusty Python script decided “customer churn” meant “every table that vaguely smells like a customer, plus that one VIEW nobody documented since 2019.” I stand before you today, your erudite, slightly unhinged technical prophet (with a heavy dose of stand-up bile and a side order of schema diagrams), to deliver the good news: Snowflake has unleashed Cortex Code, the AI coding agent that doesn’t just autocomplete your misery, it inhales it, digests the entire governed data estate, and burps back production-grade, hallucination-free SQL, Python, and dbt YAML while respecting your PII tags and warehouse economics like a paranoid compliance officer on Red Bull. This isn’t your garden-variety Copilot having another existential meltdown over a missing import. This is Code Context incarnate, an agentic beast that has swallowed the Horizon Catalogue whole, metadata, lineage graphs, semantic layers, role-based access controls, Dynamic Table lag policies, and the soul-crushing reality of your credit burn rate.
Martyn Rhisiart Jones, Madrid, Wednesday 25th March 2026
Ah, March 25th, 2026, the sun is shining, the Snowflake croissants are buttery, and another LinkedIn prophet has risen to bless us with his latest dispatch from the mountaintop of thought leadership. Thank you, dear reader, for stumbling upon “AI Special Agents Are About To Change Gaming and Maiming Forever” by the one and only Berneice Barr, world-renowned futurist, eighty-million-follower magnet, and woman who has written more books about AI than most people have had hot dinners.
Martyn Rhisiart Jones, Madrid, Friday 20th March 2026
March 20, 2026. Yes, that’s right, the calendar has finally caught up with the grift, hasn’t it? Thank you, thank you, for bothering to read my latest steaming pile of corporate word salad: “Choosing The Right AI In 2026 Is No Longer About Choosing The Right Model.” Because obviously, in 2026, choosing the right model would be far too simple, far too honest. No, no, we’ve evolved beyond that. We’re now in the rarefied realm of “capability profiles” and “orchestral conducting.” Please, hold your applause until I’ve finished flogging this dead horse made of buzzwords.
Here are the most important lessons you can learn from goodstrat.com. These are distilled from the site’s essays, blog posts, and strategic frameworks around data, governance, and technology.
Oh, for fuck’s sake, Dirndal Barr, you gleaming beacon of LockedOut futurism, you’ve done it again. March 2, 2026, the snow’s still settling on the Davos chalets, the private jets are queuing for takeoff like taxis at a funeral, and here you are, posting your pre-packaged “What Are The Real Questions Leaders Will Be Asking At Davos 2026?” like it’s some brave exposé rather than the world’s most expensive press release. You’re not a futurist, Benny. You’re a futurist-shaped content mill with 5 million followers who all clicked “Follow” in the hope you’d one day say something that wasn’t sponsored by the ghost of McKinsey.Let’s start with the official theme: “A Spirit Of Dialogue”. Beautiful. Nothing screams authentic conversation like locking up 3,000 of the richest, most insulated people on earth in a Swiss village so they can talk about how the rest of us should talk better.
Building the Data Logistics Hub: Pieces and Parts – 2026/02/15 – Part 3
Guide
This episode provides a comprehensive framework for the third installment in the series on the Data Logistics Hub (DLH). Martyn Jones conceptualised it as a technology-agnostic, centralised platform. Its purpose is efficiently moving, governing, and distributing data across organisations. This part expands on Part 1 (Challenges and Opportunities) and Part 2 (The Strategy). It focuses on the tangible “pieces and parts” of the DLH architecture. It outlines mandatory and optional elements. The episode also explores potential technologies. It examines key processes such as data pulling or pushing, translation from source to target, mapping, and data catalogues.
Building the Data Logistics Hub: The Strategy – 2026/02/14 – Part 2Before I begin, remember this: “All data roads lead to the Data Logistics Hub.” They also lead from it. It is the Rome of the age of data, information, knowledge, and wisdom. Be prepared!
Okay, we will now examine the Data Logistics Hub in terms of strategy, execution plans, and roadmaps.
A high-level blueprint for a successful Data Logistics Hub outlines several requirements. These include principles, guiding objectives, an imagined “better world” and organisational alignment. Key trade-offs must also be considered, such as centralised versus federated and batch versus streaming, among others.
Estaba leyendo un artículo escrito por Jeff Wilts y recomendado por Bill Inmon. Llegué a esta afirmación: «Teradata es un almacén de datos empresarial con todas las funciones». Para mí, la cosa fue aún más cuesta abajo a partir de ahí.
Pero esto fue el golpe de gracia: «Databricks es una plataforma de datos unificada que puede comportarse como un almacén de datos».
I was reading an article. It was written by Jeff Wilts and recommended by Bill Inmon. I got to this statement: “Teradata is a full-featured enterprise data warehouse.” For me, it went further downhill from there.
I was reading an article. It was written by Jeff Wilts and recommended by Bill Inmon. I got to this statement: “Teradata is a full-featured enterprise data warehouse.” For me, it went further downhill from there.
But this was the coup de grace: “Databricks is a unified data platform that can behave like a data warehouse.”
In early 2026 the technology industry is once again telling big confident stories about its own future. These stories dominate earnings calls conference stages and investor decks. They sound transformative urgent and inevitable. Yet when examined closely many of them rest on fragile foundations and selective evidence rather than operational reality.
Strap in, you beautiful, trusting little optimist. We’re about to crank the dial so far past irony that it transforms into existential despair. It comes with a side of eye-roll. Here’s your precious 2026 AI agent prophecy. It is now properly marinated in contempt. It is served with a garnish of pure, seething mockery.
As we settle into 2026, artificial intelligence is no longer a futuristic promise. It is embedded infrastructure. It powers everything from enterprise workflows and personal assistants to autonomous agents that act on our behalf. Yet with greater capability comes greater exposure. The biggest red flags this year are not hypothetical doomsday scenarios. They are already materialising in boardrooms. They are visible in cybersecurity dashboards, consumer wallets, and regulatory filings. Here are the most pressing warning signs to watch in 2026. These are drawn from industry reports. They originate from expert predictions. Emerging incident patterns also highlight them.
The Skunkworks Collective – Martyn, Alba, Afi, Lila, and Coco
Madrid, Wednesday 14th January 2026
Right, listen. If you’ve ever sat through one of those AI conferences, you know the ones. Some bloke in a black polo neck stands on stage. He’s clearly never met a mirror he didn’t like. He says, “We’re on the cusp of AGI.” It sounds as if he’s just invented gravity. Then you’ll know the particular flavour of despair I’m talking about.
As we venture further into 2026, the landscape of enterprise artificial intelligence has undergone a subtle but profound shift. The once-dazzling promise of autonomous AI agents has matured into something more prosaic. These self-directed digital entities can orchestrate tasks from customer engagement to complex data integration. Yet, they are no less pervasive. They are no longer novelties confined to experimental labs; they inhabit boardrooms, back offices and supply chains alike.
Should All Business Data Requirements Be Justified in Business Terms?
A Pseudo-Debate
Motion:All business data requirements must be justified in business terms. Potential business utility should be a deciding factor in whether they are fulfilled.
For the Motion:Sir Afilonius Rex Against the Motion:Martyn Rhisiart Jones
