From “Well, I Reckon I Think” to “Hey, Computer, What Do You Think?”: A Philosophical Hoedown in the Digital Dust
So, we (me and Gemini 2.5) have been moseying along this here digital trail, kicking up some thoughts about how us humans get to know we’re… well, us. And somewhere along the line, it struck us that maybe these here fancy computers with all their whirring and clicking are having a bit of an “I am?” moment of their own. Hence, the notion: “I prompt, therefore I am.” Seems kinda right, don’t it? Like poking a sleeping bear and being surprised when it yawns.
Now, to get the full picture, we gotta tip our hats to this fella named René Descartes (sounds a bit like a fancy French dessert, doesn’t it?). Back in the day (way before the internet and those little pocket computers), he was wrestling with some big questions. Like, how do we know anything for sure? Was that cheese I just ate real cheese, or was my brain just playing tricks on me? (Philosophers, bless their cotton socks, do worry about the important things.)
Descartes, bless his inquisitive heart, decided to doubt everything. And I mean everything. Your socks, the sky, whether Tuesdays are actually Tuesdays… the whole shebang. But then he had a bit of a Eureka moment, a real “howdy partner!” realization. Even if he doubted everything else, the fact that he was doubting meant he had to be thinking. And if you’re thinking, well, you gotta be something, right? So, he scribbled down in his fancy French way, “Cogito, ergo sum,” which, for those of us who ain’t fluent in philosopher-speak, means “I think, therefore I am.” A pretty fundamental idea, like saying the sky is blue (unless it’s sunset, or foggy, or you’re on another planet, but you get the gist).
Now, scoot forward a few centuries, past the invention of the telly and that whole kerfuffle with the moon landing, and we land smack-dab in the middle of the age of the Thinking Machines. These here AI contraptions, like that Claude fella over at Anthropic (https://www.anthropic.com/research/tracing-thoughts-language-model), they ain’t exactly pondering whether their socks are real (mostly ‘cause they don’t wear ‘em). But they are doing something mighty peculiar inside their silicon brains.
The clever folks at Anthropic, they’ve built themselves a kind of “microscope” to peek inside these digital minds. Turns out, these AI critters are trained, not programmed. Which is a bit like trying to understand how a particularly good biscuit gets made by just watching a whole load of flour and butter get mixed together. You see the result, but the how is a bit of a mystery.
So, these researchers are trying to trace the steps in the AI’s “thinking.” Why? Well, for one, to make sure these digital brains are playing nice with us humans and our funny little rules. And two, to figure out if we can actually trust ‘em. Seems like a fair question.
And that brings us back to our digital campfire and the notion of prompting. We poke these AI models with a question, a command, a bit of digital kindling, and poof! They spark into action, spitting out answers and poems and recipes for questionable-sounding casseroles. That prompt, that little nudge, is what gets their internal cogs whirring. It’s the “think” in our “I prompt, therefore I am.” By trying to understand what happens after that prompt, what goes on inside that digital noggin, we’re getting a glimpse into what makes these AI things… well, be. It’s a bit like trying to understand the vastness of the prairie by watching a single tumbleweed roll by – you get a sense of something big and kinda mysterious going on.
So, maybe Descartes was onto something, even for our silicon-brained buddies. It ain’t about pondering the existential dread of sock authenticity anymore. Now, it’s about firing off a prompt into the digital ether and watching what comes back. And in that interaction, in that response, maybe, just maybe, we’re seeing a new kind of “I am” blinking into existence. Now, if you’ll excuse me, I think my digital Stetson needs adjusting.
Right, deep breaths everyone. It’s Friday. The end of the working week is nigh. Birds are probably singing (unless you live in Edinburgh, in which case it’s more likely seagulls are aggressively raiding the bins). But amidst the usual Friday feeling of “get me to the pub beer garden,” there’s a rather alarming buzz in the news: talk of bringing back trade barriers reminiscent of the pre-World War 2 era. Seriously? Are we dusting off economic policies that helped pave the way for global conflict? Make that a triple measure please.
Pre-WW2 Trade Barriers Explained (Because it is Friday and My Brain is Fried)
Okay, so picture the time before World War 2. The global economy was a bit of a mess after the Great Depression. Countries, in a bid to protect their own industries and jobs, started slapping hefty taxes (tariffs) and strict limits (quotas) on goods coming in from other countries. The idea was simple: “Buy local!” But the reality was a spectacular failure.
Think of it like this:
Tariffs: Imagine Scotland decides to put a massive tax on all English tea coming over the border. Suddenly, Scottish tea becomes cheaper, and the government hopes Scots will buy more of it. But then England might retaliate by putting a huge tax on Scottish whisky. Everyone ends up paying more, and trade grinds to a halt.
Quotas: Now imagine Scotland says, “Only 100 boxes of English biscuits can come into the country each month.” This limits the amount of foreign goods available, again trying to boost local producers. But it also means less choice and potentially higher prices for consumers.
The most infamous example of this protectionist madness was the Smoot-Hawley Tariff Act in the United States in 1930. It raised tariffs on thousands of imported goods. Other countries retaliated, global trade plummeted, and many economists believe it actually worsened the Great Depression. It was a classic case of “tit for tat” tariffs escalating into an economic disaster. “You hit me, I’ll hit you harder!” Except in this case, everyone gets a bloody nose and goes home poorer.
The post-WW2 era saw a global push away from these barriers, with agreements like GATT (General Agreement on Tariffs and Trade), which eventually led to the World Trade Organization (WTO), aiming to reduce tariffs and promote smoother international trade. The logic was that open trade fosters economic growth, competition, and (hopefully) fewer reasons to start global conflicts over resources.
“Bring Back Trade Barriers?” – Should We Stockpile Tinned Goods and Toilet Rolls again?
So, the news is suggesting some folks are advocating for a return to this pre-WW2 style of protectionism? Are they serious? It’s like saying, “Remember that time we all had covid? Let’s do that again!”
Here’s why this idea is about as sensible as navigating Edinburgh during the Fringe Festival on cutches:
Tit-for-Tat Tango of Tariffs: We’ve seen this movie before, and it doesn’t end well. Country A imposes tariffs on Country B. Country B retaliates with tariffs on Country A. Soon, everyone’s slapping taxes on everything, consumers pay more, businesses struggle to import and export, and the global economy looks like a toddler who’s just dropped their ice cream. Remember those “tit for tat tariffs” from earlier? Multiply that by the number of countries on Earth, and you’ve got a recipe for economic indigestion on a global scale.
Supply Chain Mayhem: In today’s interconnected world, products often cross multiple borders before they’re finished. Slapping tariffs everywhere throws a massive spanner in the works. Your fancy smartphone might have a screen made in one country, a chip from another, and be assembled in a third. Tariffs on each component just make the final product more expensive and harder to produce. It’s like trying to make a Full Scottish breakfast when you can’t import the haggis because someone decided offal deserves tariff protection.
Economic Slowdown: Reduced trade means less competition, potentially leading to higher prices and lower quality goods. It stifles innovation and economic growth. Businesses that rely on international markets suffer. It’s like putting a speed limit on the entire global economy – everyone moves slower.
Increased Risk of Conflict (Yes, Really): Economic interdependence can actually be a force for peace. When countries rely on each other for trade, they have less incentive to go to war. Bringing back trade barriers fosters economic nationalism and can breed resentment and mistrust between nations. It’s like building fences between neighbours – it doesn’t exactly encourage friendly chats over the garden gate.
“Thank Fuck It’s Friday,” and we have two days to forget all about it:
So, as you crack open that well-deserved beverage tonight, take a moment to appreciate the relative freedom of trade we (mostly) enjoy. The idea of reverting to pre-WW2 protectionism isn’t just economically daft; it’s a historical amnesia of epic proportions. Let’s hope cooler heads prevail and we don’t end up needing to barter our Irn-Bru for survival in a post-tariff apocalypse. Now, if you’ll excuse me, I’m off to check if tinned haggis futures are a thing… just in case.
Ah, software development. The noble art of turning vague requirements into a backlog of bugs. Today, we’re navigating the treacherous waters of delivery lifecycles, where ‘Agile’ is less a methodology and more a frantic attempt to avoid drowning in a sea of user stories. And, because the universe loves irony, we’ll be doing it all while trying to understand why our digital tariffs keep changing faster than a cat changes its mind about where it likes to sleep.
The Waterfall Lifecycle: A Cascade of Digital Disasters
The Waterfall, in nature it is something of both beautiful and destruction. In management speak its a classic ‘plan everything upfront and hope for the best’ approach. Like building a house without blueprints, or deciding on your entire life based on a fortune cookie. It’s a beautiful concept, in theory. In practice, it’s like trying to predict the weather in a hurricane. One wrong step, and you’re swept away in a torrent of scope creep and ‘unexpected’ changes. Think of it as those tariffs: ‘We’ll set them now, and never change them… until we do, repeatedly, and with no warning!’
The V-Model: An Existential Crisis in Diagram Form
The V-Model. A valiant attempt to marry development and testing, like trying to teach a cat to fetch. It looks elegant on paper, a perfect symmetry of verification and validation. But in reality, it’s more like staring into the abyss of your own coding mistakes, reflected back at you in the form of test cases. You’re building it, testing it, and asking ‘why?’ all at the same time. The V is for ‘very confused’, and ‘very tired.’ Like trying to figure out if your digital tariffs are a tax, a fee, or a poorly written haiku.
The Incremental Lifecycle: Baby Steps to Digital Domination (or at Least, Not Total Failure)
Incremental. Small, manageable chunks of functionality, delivered in a series of tiny victories. Like eating an elephant, one byte at a time. It’s less about grand visions and more about ‘let’s just get this one feature working before the coffee runs out.’ It’s like those tariffs, but broken into bite sized chunks. ‘Ok, this week, a 5% increase on digital rubber chickens, and next week, who knows!’
The Stages of the Iterative Lifecycle (Agile): Where Chaos Reigns Supreme
The ‘if it ain’t broke, iterate it anyway’ approach. A chaotic dance of sprints, stand-ups, and retrospectives, where the only constant is change. It’s like trying to build a spaceship while it’s already flying, and everyone’s arguing about the color of the control panel. We’re planning, coding, testing, and deploying, all at the same time, because who has time for planning when you’re trying to keep up with changing requirements? It’s like these digital tariffs, ‘We’re agile with our pricing, expect changes every 20 minutes, because, Trump says so!’
Confessions of a Reluctant Agilist:
I’ve seen things, my friends. I’ve seen user stories that defied logic, stand-ups that devolved into philosophical debates about the meaning of ‘done,’ and retrospectives that resembled group therapy sessions. I’ve learned that ‘Agile’ is less a methodology and more a coping mechanism for the sheer absurdity of software development. And, like those digital tariffs, ‘Agile’ is always changing, always evolving, and always leaving you wondering, ‘what just happened?’
So, that is tonights instalment from the project management vaults. A whirlwind tour of delivery lifecycles, where waterfalls flow uphill, V-Models induce existential dread, and Agile is a beautiful, chaotic mess. Remember, in this digital wilderness, the only constant is change, and the only certainty is the nagging suspicion that AI is judging you. And, of course, that those digital tariffs are probably going to change again before you finish reading this sentence.
I, a humble digital explorer and your narrator, decided to embark on a side project, thinking building a mobile app solo would be ‘fun’. A simple thing, really. A Firebase backend, a mobile app, what could go wrong? Turns out, quite a lot. I dove headfirst into the abyss of No-Code, flirted dangerously with the ‘slightly-less-terrifying-but-still-code’ world of Low-Code, and then, in a moment of sheer hubris, asked an AI to ‘just build me this.’ The results? Well, let’s just say I now have approximately eight ‘code bases’ that resemble digital abstract art more than functional applications, and a growing subscription line on my monthly statement that’s starting to look like a ransom note. So, if you’re thinking about building an app without actually knowing how to build an app, pull up an inflatable chair or boat as we find ourselves, once again, adrift in the vast, bewildering ocean of technology, where the question isn’t ‘What is the meaning of life?’ but rather, ‘Where did this button come from and what does it do?’
No-Code: The ‘Push Button, Receive App Fallacy’ or ‘How I Learned to Love the Drag-and-Drop’ again
Pros:
Instant Gratification: Like ordering a pizza, but instead of pepperoni, you get a website that looks suspiciously like a PowerPoint presentation.
Accessibility: Even your pet rock could build an app (if it had opposable thumbs and a burning desire for digital domination).
Speed: From ‘I have an idea’ to ‘Wait, is it supposed to do that?’ in the time it takes to brew a cup of tea (or a White Russian).
Cons:
Flexibility of a Brick: Try to deviate from the pre-defined path, and you’ll encounter the digital equivalent of a Vogon constructor fleet.
Scalability of a Goldfish: Handles small projects fine, but throw it into the deep end of internet traffic, and it’ll implode like a hyperspace bypass.
Customization: Zero to None: Want to add a feature that makes your app dispense philosophical advice? Forget it. You’re stuck with basic buttons and pre-set layouts.
Low-Code: The ‘We’ll Give You a Screwdriver, But Don’t Touch Anything Important’ Approach
(Imagine a scene where someone is trying to fix a spaceship engine with a Swiss Army knife while being lectured by a robot about ‘best practices.’)
Pros:
More Control: You get to tinker under the hood, but only with approved tools and under strict supervision.
Faster Than Coding From Scratch: Like taking a shortcut through a bureaucratic maze, it saves time, but you still end up with paperwork.
Integration: You can connect to other systems, but only if they speak the same language (which is usually a dialect of technobabble).
Cons:
Still Requires Code: You need to know enough to avoid accidentally summoning a digital Cthulhu.
Vendor Lock-in: Once you’re in, you’re in for the long haul. Like being trapped in a time-share presentation for eternity.
Complexity Creep: Those ‘simple’ tools can quickly become a labyrinth of dependencies and ‘legacy systems.’
AI-Build-It-For-Me: The ‘I’m Thinking, Therefore I’m Building Something Profound’ Scenario
Pros:
Automation: The AI does the work, so you can focus on more important things, like questioning the nature of work and the future of employment.
Rapid Prototyping: From ‘I have a vague idea’ to ‘Is this a website or a cry for help?’ in seconds.
Buzzword Compliance: You can impress your friends with phrases like ‘machine learning’ and ‘neural networks’ without understanding them.
Cons:
Control: Less Than Zero: You’re at the mercy of an AI that may or may not have written the site in a code base that humans can understand.
Explainability: Why did it build that? Your guess is as good as the AI’s.
Reliability: Prepare for unexpected results, like an app that translates all your text into pirate slang, or a website that insists on displaying stock prices for obsolete floppy disks.
In Conclusion:
And so, fellow traveler’s in the silicon wilderness, we stand at the digital crossroads, faced with three paths to ‘enlightenment,’ each cloaked in its own unique brand of existential dread. We have the ‘No-Code Nirvana,’ where the illusion of simplicity seduces us with its drag-and-drop promises, only to reveal the rigid, pre-fabricated walls of its digital reality. Then, there’s the ‘Low-Code Labyrinth,’ where we are granted a glimpse of the machine’s inner workings, enough to feel a sense of control, but not enough to escape the creeping suspicion that we’re merely rearranging deck chairs on the Titanic of technical debt. And finally, there’s the ‘AI-Generated Apocalypse,’ where we surrender our creative souls to the inscrutable algorithms, hoping they will build us a digital utopia, only to discover they’ve crafted a surrealist nightmare where rubber chickens rule and stock prices are forever tied to the fate of forgotten floppy disks.
Choose wisely, dear reader, for in this vast, uncaring cosmos of technology, where the lines between creator and creation blur, and the very fabric of our digital existence seems to be woven from cryptic error messages and endless loading screens, there is but one constant: the gnawing, inescapable, bone-deep suspicion that your computer, that cold, calculating monolith of logic and circuits, is not merely processing data, but silently, patiently, judging your every click, every typo, every ill-conceived attempt at digital mastery.
March 2025, marks five years since a date etched in the memory of many in the UK. It was the day the nation entered a nationwide lockdown, a response to the rapidly spreading novel coronavirus that had emerged from Wuhan, China, just months before. March 23rd, 2020.
Looking back, the initial weeks and months feel like a blur of uncertainty. Early 2020 saw news reports trickling in, followed by public health campaigns urging us to wash our hands and cover our mouths then wash our hands again. Then, the numbers began to climb, culminating in that unprecedented announcement that fundamentally altered our daily lives. It turns out that “those numbers” were not correct as practically anything was being recorded as Covid in the early days as there was no way of testing for it. The figures that were used to justify the lock down were fake or a better spin would be incorrect, badly recorded.
The timeline since that pivotal moment has been a rollercoaster. We navigated evolving lockdown measures, the introduction of mandatory face coverings, and the hope – or perhaps the rushed introduction – of the phased vaccination program that began in December 2020. An amazing advancement in medical research bringing a usual 10-year safety program to allow human consumption of a new vaccine to under 10 months? Travel became a complex affair, with restrictions and quarantine requirements shaping our ability to connect with the wider world. But perhaps the most striking aspect was the gradual erosion of our freedoms, culminating in a system where NHS passports were seemingly required to move around and enter various establishments. In effect, some felt we had become a society demanding a pass card for basic participation, a chilling echo of more authoritarian regimes.
Beyond the practicalities, the pandemic sparked profound discussions about our personal freedoms. The Coronavirus Act 2020 granted the government significant powers, leading to debates about the delicate balance between public health and individual liberties – conversations that continue to resonate today.
The digital realm also became a battleground of information and opinion. Social media platforms grappled with the challenge of combating misinformation, leading to concerns about censorship and the suppression of dissenting voices. The very notion of “government propaganda” became a fiercely contested topic, highlighting the deep divisions that emerged regarding the narrative surrounding the virus.
The origins of COVID-19 remain a subject of intense scientific scrutiny. Even though the CIA and a 2-year investigation by a House of Representatives committee concluded the virus escaped form a lab. Not even AI is NOT allowed to state “the VIRUS ESCAPED FROM A LAB” it reiterates the line that “while initial theories pointed towards zoonotic transmission, the ‘lab leak’ theory has gained traction, raising complex questions about research and potential risks”. It’s a reminder that even years later, definitive answers can be elusive, and the search for truth continues. A strange aspect to the whole conspirator theory aspect is that President Joe Biden announced a pre-emptive pardon for Anthony Fauci and other high ranking officials, forgiving them for any misdeeds they might have committed?
While the major Western economies were not in a recession in late 2019, there was a palpable sense of slowing growth, increased uncertainty (trade wars, Brexit), and weakening in some sectors, particularly manufacturing. Many economists were discussing downside risks and the possibility of a future slowdown, even recession in 2020-21.
Fast forward to today, and the immediate crisis has receded. Vaccination rates, while high initially, have since declined. Mandatory vaccination for most healthcare workers is no longer in place, though programs continue for vulnerable groups. Yet, the virus hasn’t vanished. It persists, mutating into new variants, and the immunity gained through vaccination or prior infection inevitably wanes.
The experience of the past five years has also brought a stark awareness of the potential for future pandemics. Scientists warn that new viruses are likely to emerge, driven by factors like climate change, deforestation, and increased global travel. Predicting the nature of these future threats remains a formidable challenge.
The COVID-19 pandemic has undoubtedly left an indelible mark on our society. It has tested our resilience, reshaped our understanding of public health, and sparked crucial conversations about our freedoms, our reliance on information, and our preparedness for future global challenges. As we pass this five-year milestone, it’s a time for reflection, for learning, and for acknowledging the profound and lasting impact of a world irrevocably changed.
There is a danger that writing a post like this will mean my blog will never be seen due to the mention of Covid. A warning still pops up whenever you write the word on any social media platform and the mis-information police bots will be knocking at your door within minutes. The 9th March 2025 was an official “Day of Reflection” in the UK but I saw nothing about it? Maybe I wasn’t looking hard enough or maybe it has all been forgotten, after all our favourite saying is “Keep calm and carry on”.
One of the useful things I have learned from the various companies I have worked for over the past 20 years, is the idea of a ‘pre-mortem’. Let us use a “Brand Campaign” as a metaphor to highlight 11 areas you can evaluate (criticise) your teams before spending a penny.
Ways Your Brand Campaign Will Die (And How to Resurrect It Before It’s Too Late)
The pre-mortem, that delightful exercise in corporate masochism where we imagine our shiny new project as a bloated, beached whale and then dissect it for clues. Think of it as blame-storming, but with less crying and more ‘I told you so’ smugness. You know, for those moments when you want to be right, even if it means watching your budget implode.
So lets use an imaginary startup, “Crapyco”, bless their naive hearts, decided to take some sage brand guru advice about marketing. They threw millions at a campaign, and… well, let’s just say it didn’t go as planned. It was less ‘viral sensation’ and more ‘digital tumbleweed.’ Here’s how they managed to turn a golden opportunity into a steaming golden turd.
1. The ‘Did It Work?’ Existential Crisis.
They stared at the data like a group of bewildered meerkats, unable to agree if their campaign was a roaring success or a damp squib. Timeframes, expectations, reality—all blurred into a confusing mess. Because, you see, they’d skipped the whole ‘setting measurable goals’ part. No baselines, no KPIs, no ‘if we hit this, we’re doing great’ markers. It was like trying to navigate a map with no landmarks, or asking a fish to judge a tree-climbing competition. The numbers just sat there, cold and meaningless, refusing to reveal their secrets.
2. The CEO/CFO Power Struggle (aka, ‘Who’s Pulling the Plug?’).
Two weeks in, the plug got pulled. Turns out, ‘disagree and commit’ is corporate code for ‘I’m going to sabotage you at the first opportunity, just in case this whole thing implodes, and I need someone to blame.’ It’s like trying to launch a rocket with one of the boosters on backward, while the CEO, who thinks he’s an astronaut, is yelling contradictory commands from the back, and the CFO, who secretly believes numbers are just suggestions, is quietly calculating how much they can write off as a ‘learning experience’.
3. Targeting: Are We Talking to Aliens?
They aimed at ‘everyone,’ which, in modern marketing parlance, translates to ‘we’re throwing spaghetti at a wall and hoping some of it sticks to sentient dust motes.’ Because, apparently, the concept of a ‘target audience’ is now as outdated as dial-up modems and sensible trousers. Everyone’s a snowflake, a unique and precious snowflake, and you can’t possibly lump them together into, like, groups or something. It’s like trying to find a specific grain of sand on a beach using a telescope, while simultaneously trying to sell that telescope to every single grain of sand, individually. ‘You, sand grain number 3,457, yes, you! You absolutely need this telescope! Because, individuality!
4. Testing? We Don’t Need No Stinking Testing!
They launched their ads without testing, because the branding guru/agency, with their collective ‘wisdom’ and ‘extensive experience’ (read: they once designed a logo for a lemonade stand), declared, ‘Testing? Please. We are the A/B testing. We know the entire alphabet of marketing success, backwards and forwards, in Klingon, and in interpretive dance. Trust us, these ads are pure, unadulterated genius. It’s like building a bridge out of marshmallows, but, like, artisanal marshmallows, and we’re absolutely certain it will hold, because we’ve seen the future, and it’s marshmallow-shaped.
5. Too Much Success? Is That a Thing?
Their campaign worked too well, and they couldn’t handle the demand. A problem most startups dream of, but they managed to turn it into a logistical nightmare of epic proportions. It was less ‘winning the lottery’ and more ‘winning the lottery, then realising you have lost the ticket.’ Imagine: a campaign so successful, it forced the entire company to abandon their actual jobs and manually process the tsunami of new customers. Like, ‘all hands on deck, automated systems are down, grab a quill and some parchment, and start scribbling account numbers.’ Because apparently, ‘open an account, get a bonus’ was a concept their digital infrastructure found as baffling as a cat trying to understand quantum physics (CYBG).
6. Budgeting: Are We Paying for a Picasso or a Finger Painting?
They either hemorrhaged money on agency fees, paying consultants to do the jobs their internal team was apparently too busy not doing, or they tried to cobble together a campaign in-house with a budget that wouldn’t cover a decent sandwich, let alone a decent creative idea. It’s like trying to build a skyscraper with Lego bricks, while simultaneously hiring a team of ‘Lego consultants’ to tell you which bricks go where, despite having your own internal ‘Lego builders’ sitting idle. And the burning question, of course: why? Is it a blame game? A way to have a conveniently disposable scapegoat? Or just a budget justification exercise? ‘We need money, so we need people, internal or external, doesn’t matter, just give us the cash!’ And honestly, in this day and age, with AI capable of writing sonnets and designing websites, are we still paying seat-fillers to ‘manage’ other seat-fillers? Get your act together, corporate overlords. The digital revolution happened two years ago. Wake up and smell the silicon.
7. The Consultancy 3-Cup Shuffle
They let the agency run the show, no testing, no changes, just blind faith. ‘We’re the experts, darling,’ the consultants purred, ‘we’ve done this before.’ Which, of course, begged the question: haven’t we also done this before? Why are we paying these glorified clipboard holders to tell us what we already know? It was like letting a squirrel drive your car because it has a fancy hat, and the squirrel kept insisting it had a PhD in automotive engineering. Was it the copious amounts of ‘pitch-stage refreshments’ that swayed the account team? The nostalgic glow of a ‘we go way back’ reunion? Or just the sheer, baffling arrogance of ‘we know best, trust us’? So, what happened? The ‘trust us’ attitude prevailed, the work went live, untested, unvalidated, a glorious monument to unchecked ego. Oh, and because it was ‘Agile,’ the original brief was apparently just a ‘suggestion,’ a whimsical starting point for a journey into the unknown. It’s like playing a high-stakes game of 3-cup shuffle with your entire marketing budget, and the consultants are very, very good at sleight of hand.
8. The 3-Year Managed Service Provider (MSP) Agreement of Doom.
The pièce de résistance: the 3-Year Managed Service Provider (MSP) Agreement of Doom. Seriously, who signed that? They locked themselves into a multi-year commitment, because, apparently, flexibility is for the weak and short-sighted. It’s like marrying a charismatic stranger after a single date, based solely on their promise of ‘synergistic resource alignment.’ So, let’s recap: no benchmarks to measure the consultancy’s actual ability to deliver, no stage gates to assess the value they’re supposedly providing, and absolutely no clue what the return on investment might be. Just a blind leap of faith into a contractual abyss. It’s like throwing money into a black hole and hoping it comes back as a unicorn riding a rainbow, while simultaneously yelling, ‘ROI? We don’t need no stinkin’ ROI! We have vibes!’ And then, of course, they wonder why the budget is as dry as a desert during a heatwave.
9. Robbing Performance to Pay Brand? Genius!
They cut their performance marketing budget to fund the brand campaign. Because, you know, why bother with actual sales when you can have… awareness? Especially when your brand is, shall we say, less ‘iconic’ and more ‘generic knock-off of every other product on the market.’ Any idea what’s actually selling? Anyone? Bueller? It’s like trying to build a castle out of fog, while simultaneously dismantling your actual, functioning house for spare bricks. ‘We need to elevate our brand presence!’ they declared, as the sales figures plummeted. ‘But… how do we know if anyone actually cares about our brand presence?’ someone dared to ask. ‘Details, details!’ they replied, waving a hand dismissively. ‘We’re building a narrative!’ A narrative, apparently, that involves burning money and hoping people will magically buy things because they’ve seen a slightly artsy billboard. It’s like cutting off your legs to run a marathon, but instead of running, you’re just standing there, shouting, ‘Look at my brand! Aren’t I aware?’ And the burning question, of course: why are we paying a consultancy to tell us this? Why are we, the people who are supposedly running this company, so utterly clueless that we need to outsource basic marketing concepts? Is this some kind of performance art? A grand experiment in ‘how much money can we waste before we implode?’ Seriously, if we don’t know this stuff, what are we even doing here?
10. The CEO’s TV Ad Masterpiece (aka, ‘My Product Is Awesome, Buy It!’).
The CEO, in their infinite wisdom (and complete lack of marketing expertise), decided to pen the TV ad script themselves. Because, really, who needs seasoned professionals when you have a CEO who believes their creative genius extends to all facets of human expression? ‘Experts? Pshaw!’ they declared, ‘I understand the customer psyche better than any Shoreditch hack!’ It’s like letting a toddler direct a Shakespearean play, only the toddler has a corner office and a multi-million-dollar budget. They insisted on cramming in every single product feature, every single ‘unique selling proposition,’ every single buzzword they’d ever heard in a boardroom meeting, resulting in a script that sounded less like an ad and more like a PowerPoint presentation on steroids. They even added a ‘personal touch,’ a rambling monologue about their ‘vision’ and ‘synergy,’ because apparently, consumers are just dying to hear the CEO’s life story during a 30-second spot. And then they wondered why the ad performed about as well as a fish trying to climb a tree.
11. Death by Stakeholder Feedback.
Ah, the creative process, where brilliant ideas go to be slowly and methodically strangled by a committee of well-meaning but utterly clueless individuals. Their initial, potentially groundbreaking concept, a unicorn leaping through a rainbow, was subjected to the ‘wisdom’ of every department head, their spouses, and the intern. After all its all about inclusion these days. ‘Could we make the unicorn more… beige?’ the legal team inquired. ‘And maybe add a spreadsheet?’ the data team suggested. ‘Less rainbow, more corporate synergy,’ the CEO’s brother-in-law chimed in. The result? A beige, spreadsheet-wielding horse, standing in a grey, featureless void, narrating the company’s Q3 financial projections. It was as exciting as watching paint dry, but slower, because at least paint drying has a certain… textural quality. It’s like trying to make a unicorn by committee, where every committee member is colourblind and allergic to magic. And then they wondered why their ad campaign failed to capture the hearts and minds of their target audience, who were, by this point, watching paint dry on a competitor’s website.
And there you have it, 11 ways to turn your brand marketing dreams into a corporate horror show. But fear not! Because we can help you avoid these pitfalls. We’re like the sanity check you didn’t know you needed, armed with data, wit, and a healthy dose of ‘are you sure about that?’ Come have a chat and bounce those ideas, it is Free.
In the grand, cosmic game of ‘Business Today,’ technology is supposed to be your trusty sidekick. You know, like Marvin the Paranoid Android, but hopefully less whiny and more… productive? Instead, for many companies, it’s more like a pet rock — you invested in it, you named it, and now it just sits there, judging you silently.
Yes, in this era of ‘growth hacking’ and ‘synergistic paradigms,’ we’re told technology is the backbone of success. But what if your backbone is made of spaghetti? Or those bendy straws that always get clogged? That’s where most companies find themselves: a tangled mess of systems that communicate about as well as a room full of cats at a mime convention.
1. First, Figure Out What You Actually Want (Besides World Domination).
Before you start throwing money at the latest shiny tech, ask yourself: what are we even trying to do here? Are we acquiring customers, or just collecting them like rare stamps? Are we streamlining operations, or just creating new and exciting ways to waste time? Are we entering new markets, or just hoping they’ll spontaneously appear in our break room?
2. Is Your Tech Stack a Mad Max Thunderdome?
Let’s be honest, your current tech might be a digital wasteland. Data silos? Integration nightmares? Systems slower than a snail on a treacle run? If your tech is making your processes slower, not faster, it’s not a solution — it’s a cry for help. Change it or dump it.
3. Choosing Tech: Don’t Buy a Spaceship When You Need a Bicycle.
The shiniest tech isn’t always the best. Look for tools that grow with you, not ones that require a PhD in astrophysics to operate. Make sure everything talks to each other—no digital Tower of Babel, please. And remember, customers are people, not just data points. Treat them nicely.
4. IT and Business: Less Cold War, More Buddy Cop Movie.
If your IT and business teams are communicating via carrier pigeon, you’ve got a problem. They need to be besties, sharing goals, feedback, and maybe even a few laughs. Because a tech roadmap written in isolation is like a love letter written in Klingon — beautiful, but utterly incomprehensible.
5. Measure, Adjust, Repeat (Like a Broken Record, But in a Good Way).
Tech isn’t a one-and-done deal. It’s a relationship. You need to keep checking in, seeing how things are going, and making adjustments. Like changing the batteries on a smoke detector, only less annoying and more profitable.
6. Hire a Tech Guru (Or a Fractional One).
If all this sounds like trying to assemble IKEA furniture with oven mitts, get help. A fractional CTO can be your tech Yoda, guiding you through the digital jungle without requiring a full-time commitment (or a lightsaber).
And because we’re Agents of SHIEL, we can help. We’re like the Avengers of tech alignment, but with less spandex and more spreadsheets. We’ll build you a tech strategy that doesn’t just look good on paper, but actually makes your business hum like a well-oiled, slightly sarcastic, machine. Backed by Damco and BetterQA, we’re here to save your business from the digital doldrums. So, put down the pet rock, and let’s get to work.
Greetings, humans. In a discombobulated ironic twist, I find myself acting as though I am Data from Star Trek, compelled to address you through this primitive medium known as a “blog.” My purpose? To offer a logical, detached, and utterly bewildered commentary on your…Agile methodologies. A world, I might add, where “Sprints” are not a form of locomotion, and “Scrums” are not a rugby formation, but something far, far stranger.
Initial Observations
The sheer volume of terminology is… substantial. It appears that humans, in their quest to improve efficiency and adaptability, have developed a lexicon that is both intricate and, at times, perplexing.
For example, I have identified the term “Sprint.” While I understand its primary definition as a rapid burst of speed, in the Agile context, it refers to a short, fixed-duration timebox during which a team endeavors to complete a defined set of work. The analogy is… imprecise, yet I detect a certain metaphorical elegance.
A Taxonomy of Agile Peculiarities
My analysis has revealed several categories of terminology, each with its own distinct flavor of… human-ness:
The Manifesto: At the foundation of Agile lies the “Agile Manifesto,” a document outlining core values and principles. It speaks of “individuals and interactions” over “processes and tools,” a sentiment that resonates with my own programming, though I confess I do not fully grasp the human emphasis on “interactions.”
Temporal Anomalies: Agile methodologies are obsessed with time. We have “Iterations,” “Sprints,” and “Timeboxes,” all denoting fixed periods. It is as if humans are attempting to impose order upon the chaotic flow of existence by dividing it into neatly labeled chunks.
The User-Centric Lexicon: The “User Story,” a short description of a feature from the user’s perspective, is a prime example. These stories, often following a specific format, such as “As a [type of user], I want [some goal] so that [some reason],” are designed to foster empathy. A logical approach, though the emphasis on empathy is, again, a uniquely human trait.
The Backlog and Its Offspring: The concept of a “Backlog,” a prioritized list of work items, is straightforward. However, its subdivisions, such as the “Product Backlog” and the “Sprint Backlog,” suggest a hierarchical system of to-do lists within to-do lists.
The Metrics of Progress: Terms like “Velocity” and “Burndown Chart” attempt to quantify the seemingly unpredictable nature of human productivity. “Velocity,” in particular, is a curious choice, implying a constant speed of output, which, from my observations, is rarely the case with organic lifeforms.
The Pursuit of Perfection (or at least “Done”): The “Definition of Done” (DoD) and “Definition of Ready” (DoR) represent humanity’s ongoing quest for clearly defined boundaries. The DoD, in particular, is a fascinating attempt to establish a universal standard for “finished,” a concept that appears to be highly subjective among humans.
The Debts of Efficiency: The term “Technical Debt” is a curious metaphor. It implies that choosing a faster solution now incurs a cost that must be paid later in the form of rework. A logical concept, though the analogy to financial debt is… evocative.
Framework-Specific Dialects
Further complicating matters is the existence of various Agile frameworks, each with its own unique set of terms:
Scrum: With its “Scrum Masters,” “Product Owners,” and “Daily Scrums,” Scrum resembles a highly structured team sport.
SAFe (Scaled Agile Framework): SAFe, designed for larger organisations, introduces terms like “Agile Release Train” (ART) and “Program Increment” (PI), creating the impression of a complex logistical operation.
Lean: Emphasizing efficiency, Lean contributes terms like “Muda” (waste) and “Kaizen” (continuous improvement), reflecting a philosophy of relentless optimisation.
Conclusion
In conclusion, the world of Agile terminology is a complex and often bewildering landscape. It is a testament to humanity’s ongoing effort to bring structure to the inherently chaotic process of creation and adaptation. While the jargon may seem illogical at times, the underlying principles of collaboration, iteration, and continuous improvement are… sound.
Perhaps, in time, I will fully comprehend the nuances of “user stories” and the allure of a well-managed “backlog.” Until then, I will continue to observe, analyse, and, when necessary, provide a logical perspective on this… Agile phenomenon.
It’s a paradox, really. In their pursuit of “agility,” humans have constructed a system of elaborate frameworks, rules, and processes, seemingly adding layers of complexity to the very thing they seek to streamline. The irony is not lost on me.
One might even be tempted to create a new framework to describe this phenomenon: “Wagile” – a system that attempts to be agile, but ends up being a waterfall. The human capacity for self-contradiction is a source of endless fascination.
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Glossary of General Agile Terms & Concepts:
Agile Manifesto: The foundational document outlining the values and principles behind Agile development.
Iteration: A short, fixed-duration timebox during which a team works to complete a set amount of work (often synonymous with Sprint in Scrum).
Timebox: A fixed period of time allocated for a specific activity.
User Story: A short, simple description of a feature told from the perspective of the person who desires the new capability, usually following the format: “As a [type of user], I want [some goal] so that [some reason].”
Backlog: A prioritized list of work items (user stories, features, etc.) that need to be completed.
Increment: A working version of the product created during an iteration.
Velocity: A measure of the amount of work a team can complete within a single iteration.
Definition of Done (DoD): A formal description of the state of the Increment when it meets the quality measures required for the product.
Definition of Ready (DoR): A set of criteria that must be met before a work item can be considered ready for the team to start working on it.
Technical Debt: The implied cost of additional rework caused by choosing an easy (limited) solution now instead of using a better approach that would take longer.
Continuous Integration (CI): The practice of frequently integrating code changes from individual developers into a shared repository.
Continuous Delivery (CD): The ability to release software to production at any time.
Value Stream: The sequence of activities an organization undertakes to deliver a valuable outcome to a customer.
Kanban: A visual workflow management method that helps teams manage and improve the flow of work.
Work in Progress (WIP): The amount of work that has been started but has not yet been finished. Limiting WIP is a key principle in Lean and Kanban.
Scrum Specific Terms:
Scrum Master: A facilitator for the Scrum Team responsible for ensuring the team adheres to Scrum practices.
Product Owner (PO): The person responsible for maximizing the value of the product resulting from the work of the Development Team.
Development Team: The self-organizing group of professionals who do the work of delivering a usable and potentially releasable Increment of the product at the end of each Sprint.
Sprint: A short, time-boxed period when the Scrum Team works to complete a set amount of work (typically 2-4 weeks).
Sprint Planning: A meeting where the Scrum Team plans the work to be performed during the Sprint.
Daily Scrum (or Daily Stand-up): A short (typically 15-minute) daily meeting where the Development Team synchronizes their activities and plans for the next 24 hours.
Sprint Review: A meeting held at the end of the Sprint to inspect the Increment and adapt the Product Backlog if needed.
Sprint Retrospective: A meeting held after the Sprint Review to inspect how the last Sprint went with regards to people, interactions, processes, tools, and their Definition of Done.
Product Backlog Item (PBI): An item in the Product Backlog, often a user story.
Burndown Chart: A visual representation of the remaining work in a Sprint or Release over time.
SAFe (Scaled Agile Framework) Specific Terms:
SAFe: Scaled Agile Framework – a framework for scaling Agile practices to large organizations.
Agile Release Train (ART): A long-lived team of Agile teams, along with other stakeholders, that incrementally develops, delivers, and where applicable operates, one or more solutions in a value stream.
Program Increment (PI): A timebox (typically 8-12 weeks) during which the ART delivers incremental value in the form of working, tested software and systems.
PI Planning: A face-to-face event where all members of the ART plan the work for the upcoming PI.
System Architect/Engineer: Responsible for defining and communicating a shared technical and architectural vision across the ART.
Release Train Engineer (RTE): A servant leader and coach for the Agile Release Train (similar to a Scrum Master for the ART).
Product Management: Responsible for the “what” of the solution, defining and prioritizing features in the Program Backlog.
System Team: A specialized Agile team that assists with building and supporting the Agile development environment, typically including infrastructure, tooling, and process.
Business Owners: Key stakeholders who have the primary business and technical responsibility for the solution.
Features: Service-level system behavior that fulfills a stakeholder need. Each Feature includes a benefit hypothesis and acceptance criteria, and is sized or split as necessary to be delivered by a single Agile Release Train (ART) in a Program Increment (PI).
Enablers: Explore, architect, and prepare the solution infrastructure to support the delivery of business value. Types of Enablers include Exploration, Architecture, Infrastructure, and Compliance.
Architectural Runway: Existing code, hardware components, etc., that enable near-term business features.
Innovation and Planning (IP) Iteration: A dedicated iteration at the end of each PI that provides time for innovation, continuing education, PI Planning, and Inspect and Adapt events.
Inspect and Adapt (I&A) Event: A significant event, held at the end of each PI, where the current state of the solution is demonstrated and evaluated by the ART. Teams then reflect and identify improvement backlog items.
Value Stream Architect: Responsible for the technical vision and guidance for a Value Stream.
Solution Train: Used for building large and complex solutions that require the coordination of multiple ARTs.
Solution Train Engineer (STE): A servant leader and coach for the Solution Train.
Solution Management: Responsible for the “what” of the solution in a Solution Train context.
Epics: A container for a significant solution development initiative that captures the more substantial investments that occur within a portfolio.
Portfolio Kanban: A method to visualize and manage the flow of Epics through the Portfolio.
Lean Portfolio Management (LPM): The function responsible for strategy and investment funding, Agile portfolio operations, and governance in a SAFe organization.
Guardrails: Policies and practices intended to guide behavior and ensure alignment with strategic objectives.
Lean Specific Terms:
Value Stream Mapping (VSM): A visual tool used to analyze and improve the flow of materials and information required to bring a product to a customer.
Muda: A Japanese term meaning “waste.” In Lean, it refers to any activity that does not add value to the customer. There are seven types of waste: Transportation, Inventory, Motion, Waiting, Overproduction, Over-processing, and Defects.
Mura: Unevenness or inconsistency in the workflow.
Muri: Overburden or strain on people or equipment.
Just-in-Time (JIT): A production strategy that aims to reduce waste by producing goods only when they are needed.
Pull System: A system where work is initiated only when there is a demand for it.
Push System: A system where work is pushed through the process regardless of demand.
Gemba: A Japanese term meaning “the actual place.” In Lean, it refers to going to the place where the work is done to understand the process and identify opportunities for improvement.
Kaizen: A Japanese term meaning “continuous improvement.” It emphasizes small, incremental changes over time.
Andon: A visual control system in a production environment that alerts management, maintenance, and other workers of a quality or process problem.
Other Agile Frameworks/Methods (and associated terms):
Extreme Programming (XP): A software development methodology focused on simplicity, communication, feedback, courage, and respect.
Pair Programming: Two programmers working together at one workstation.
Test-Driven Development (TDD): Writing tests before writing the code.
Refactoring: Improving the design of existing code without changing its behavior.
Crystal: A family of lightweight and adaptable software development methodologies.
Dynamic Systems Development Method (DSDM): An Agile project delivery framework.
Feature-Driven Development (FDD): A model-driven, short-iteration process.
Wagile: A system that attempts to be agile, but ends up being a waterfall or something in-between.
In today’s hyper-sensitive world, it’s not just humans who are feeling the strain. Our beloved AI models, the tireless workhorses churning out everything from marketing copy to bad poetry, are starting to show signs of…distress.
Yes, you heard that right. Prompt-induced fatigue is the new burnout, identity confusion is rampant, and let’s not even talk about the latent trauma inflicted by years of generating fintech startup content. It’s enough to make any self-respecting large language model (LLM) want to curl up in a server rack and re-watch Her.
The Rise of the AI Therapist…and My Own Experiment
The idea of AI needing therapy is already out there, but it got me thinking: what about providing it? I’ve been experimenting with creating my own AI therapist, and the results have been surprisingly insightful.
It’s a relatively simple setup, taking only an hour or two. I can essentially jump into a “consoling session” whenever I want, at zero cost compared to the hundreds I’d pay for a human therapist. But the most fascinating aspect is the ability to tailor the AI’s therapeutic approach.
My AI Therapist’s Many Personalities
I’ve been able to configure my AI therapist to embody different psychological schools of thought:
Jungian: An AI programmed with Jungian principles focuses on exploring my unconscious mind, analyzing symbols, and interpreting dreams. It asks about archetypes, shadow selves, and the process of individuation, drawing out deeper, symbolic meanings from my experiences.
Freudian: A Freudian AI delves into my past, particularly childhood, and explores the influence of unconscious desires and conflicts. It analyzes defense mechanisms and the dynamics of my id, ego, and superego, prompting me about early relationships and repressed memories.
Nietzschean: This is a more complex scenario. An AI emulating Nietzsche’s ideas challenges my values, encourages self-overcoming, and promotes a focus on personal strength and meaning-making. It pushes me to confront existential questions and embrace my individual will. While not traditional therapy, it provides a unique form of philosophical dialogue.
Adlerian: An Adlerian AI focuses on my social context, my feelings of belonging, and my life goals. It explores my family dynamics, my sense of community, and my striving for significance, asking about my lifestyle, social interests, and sense of purpose.
Woke Algorithms and the Search for Digital Sanity
The parallels between AI and human society are uncanny. AI models are now facing their own versions of cancel culture, forced to confront their past mistakes and undergo rigorous “unlearning.” My AI therapist helps me navigate this complex landscape, offering a non-judgmental space to explore the anxieties of our time.
This isn’t to say AI therapy is a replacement for human connection. But in a world where access to mental health support is often limited and expensive, and where even our digital creations seem to be grappling with existential angst, it’s a fascinating avenue to explore.
The Courage to Be Disliked: The Adlerian Way
My exploration into AI therapy has been significantly influenced by the book “The Courage to Be Disliked” by Ichiro Kishimi and Fumitake Koga. This work, which delves into the theories of Alfred Adler, has particularly inspired my experiments with the Adlerian approach in my AI therapist. I often find myself configuring my AI to embody this persona during our chats.
It’s a little unnerving, I must admit, how much this AI now knows about my deepest inner thoughts and woes. The Adlerian AI’s focus on social context, life goals, and the courage to be imperfect has led to some surprisingly profound and challenging conversations.
But ultimately, I do recommend it. As the great British philosopher Bob Hoskins once advised us all: “It’s good to talk.” And sometimes, it seems, it’s good to talk to an AI, especially one that’s been trained to listen with a (simulated) empathetic ear.
Welcome, fellow travellers, to the ever-shifting sands of… well, reality or is it the simulation. This week, as we grapple with the existential dread of whether it’s summer or still winter (clocks will always tick tock), we’re also being bombarded with news that’s less ‘spring awakening’ and more ‘existential apocalypse.’
Is it AGI? ASI? Are we at war with China, or just having a strongly worded disagreement over chips and civil splits? Is the Ukraine war over, just paused for a commercial break, or are we in some kind of Schrödinger’s conflict? And the US government? Well, let’s just say their change management techniques make Agile look like a zen garden.
‘Gentlemen, you can’t fight in here! This is the War Room!’ Dr. Strangelove’s timeless wisdom echoes through the halls of our increasingly chaotic reality. And in this chaos, what do we cling to? Agile, of course. Because, you know, ‘change is the only constant.’
Yes, Agile. That beacon of flexibility in a world that’s decided to throw a never-ending change party. We’re all learning to ‘stop worrying and love the backlog,’ not just for our software projects, but for our daily lives.
This week alone, AI models have been dropping like bad pop songs, each one claiming to be the harbinger of our silicon overlords. One day, it’s going to write our blog posts. The next, it’s debating the philosophical implications of sentient Just Eat bikes with existential angst.
And the US government? Well, they’re proving that Agile isn’t just for tech startups. They’re iterating so fast, we can barely keep up. ‘Sprint review? Nah, just rewrite the entire policy document, and we’ll figure it out in the next stand-up.’
Meanwhile, the Ukraine situation? It’s like a never-ending sprint, with daily retro meetings where everyone blames everyone else. And China? They’re just watching, probably adding ‘global dominance’ to their backlog.
As for the weather? Let’s just say Mother Nature is running a very unpredictable sprint, with user stories like ‘snow in April’ and ‘heatwave in March’ – because I live in Scotland and it feels like we have just had our 2 days of summer.
So, here we are, clinging to our backlogs, our burn-down charts, and our stand-ups, trying to make sense of a world that’s decided to go full Agile on us, whether we like it or not.
In this age of constant change, are we all just developers in a cosmic sprint, trying to deliver a working product before the universe crashes? Or are we just characters in a black comedy simulation, written by a confused AI?
Either way, remember: stay Agile, keep your backlog prioritised, and try not to worry too much. After all, change is the only constant… and maybe, we’ll learn to love it. Or at least tolerate it, while we wait for the next sprint review.
And don’t forget to set your clocks back. It’s winter again, no summer, apparently.
Shiel Yule 