The fear of the unknown is not a universal rule. It’s conditional. Starting a new job can be scary, opening a present is not.

The difference between the two is choice. One is an unknown you may be forced to endure, the other is about taking curious steps to uncover something exciting.

In product development, this distinction applies as much as anywhere else. For a user that’s just been upgraded, your design choices can lead to very different experiences!

Consider the example of The Office Ribbon. Back in 2007, in a single update, Microsoft removed every menu, every carefully learnt interaction, decades of muscle memory, by introducing a radically different interface to Microsoft Office. Whatever you might think of the ribbon design, this was a shock for users, and took a long time with reduced productivity to get used to. People complained about it for years!

Your user’s knowledge is an asset. The patterns they have learnt are an investment they have made in your product and that keeps them loyal to you.

The best path is evolution, not revolution. Introduce change gradually. Let them use their learnt patterns and extend upon what they know.

Put the button leading to the new functionality there so users can explore when they are ready. Put it where it can be discovered, not where it interrupts. An invitation to explore should never get in the way of getting home in time for dinner.

Make it appear at first as a hint. A small indicator. An intriguing path to something new, to be explored when they are ready.

This way you change their experience from forced adoption to joyful discovery.

The first creates resentment and the feeling of being a forced passenger.

The second an impression of innovation and understanding of users – which fosters loyalty.

Let your users be the heroes of the discovery. That is a feeling they will remember.

We just did a major launch and you know what? No one noticed. Yet!

And that’s just how we wanted it to be.

It's like a secret marriage between our production backend and the upcoming big release. No announcements. No invitations. We're saving the fanfare for the public launch events later on.

Until we do tell everyone, we have a big "undo" button we can push if we've made a mistake. Why would you ever not want that safety net?

🚀 Meanwhile, I still see people taking software to market in rocket launch mode. Big bang releases with customers primed to hit refresh at 6pm exactly.

This can lead to spectacular glory, spectacular failure, or—more likely—days of firefighting issues that never surfaced in testing.

🎅 When I was at Opera Software, we launched the first Opera for Linux on Christmas Eve (the big celebration day in Norway). Nice idea in theory—giving our users a Christmas present.

But as software companies often do, we forgot their focus would not be on us that day.

There is this expectation from software companies sometimes that our launches are big events in our customers’ diaries. It generally is not.

​​You get a brief window to make an impact, but then you need everything working flawlessly. A failure at that moment damages confidence in your ability to provide a stable platform. Too many radical changes at once hurt your customers' ability to maintain stable workflows without constant retraining.

🏁 The best you can do for your customers and yourself is a phased approach. Improving gradually, with carefully prepared releases and constant forward momentum.

For space launches, the testing and cost required to prevent failure is astronomical.

We don’t have to do things that way. Instead:

🖖 Separate your changes. Make database, backend, and frontend updates independently. Split major changes into smaller iterations.

🧪 Test relentlessly along the way. You can still do big public launches, but ensure the underlying changes are released and validated in smaller chunks first.

⚖️ Compatibility is king. Never negatively impact your customers' APIs or workflows without clear migration paths.

🔐 Empower your gatekeepers. Give your QA and Ops teams authority to ensure stability before anything goes public.

↩️ Keep that undo button ready. If something still goes wrong, rewind. This is your safety net.

Launching software should not mirror launching rockets. We don't need all-or-nothing stakes. Make smaller iterative changes, maintain your rollback capabilities, and save the fireworks for when you're absolutely certain everything works.

Your customers, as well as your staff, will thank you!

If you read some of the AI articles circulating these days, you'd think we're living in a technological utopia.

Apparently, people are designing entire operating systems between rolling out of bed and their feet hitting the floor. Websites are being created through snoring creatively at night, thus directing AI to produce award-winning designs that would make Don Draper weep with envy.

They claim to have built production-level Fortune 500 applications between beers at halftime on Saturday – zero bugs, ironclad security, and customer satisfaction that somehow exceeds mathematical possibility at 110%.

I can poke fun at this because I work with AI technologies daily, and these claims are easy targets. Their stories are equivalent to me telling you I teleported to our meeting in my Boeing 737.

It is amazing technology with untold potential. But you have to know its limitations. These hype engineers have surface-level notions of what the tool can do but lack deep understanding. They are seriously damaging AI's perception by using it to market their own inflated brilliance.

At the same time, every event is now made to seem as if it is about AI. Do you have a session about using Outlook? Bring in an AI expert to talk about basic translation or summarisation features, and call it an AI event.

The real potential of AI is hurt by these people but also by the limitations of free (and free-ish) AI solutions and their mediocrity. While there is value in the free offerings, you can imagine them a bit as if a stranger came up to you to offer free tutoring for your child. You would ask two questions:
(1) How good is this going to be?
(2) What are they going to get out of it?

These tools still shape people’s perception. It’s like giving people a Commodore 64 and saying it’s a computer. It’s not technically wrong but we all know better computers can do a whole lot more.

We're trapped between gurus promising a work-free future tomorrow and generative tools that still draw six-legged zebras.

The core problem is a massive expectations gap. Imagine a project that is given to two developers:

• One promises a delivery in 3 months.

• The other estimates 9 months.

Both deliver in 6 months. The first developer failed, the second is a hero.

It's not about the final delivery; it's about the perception shaped by the initial promise. Right now, the AI hype machine is promising a 3-month delivery.

This is powerful, emerging technology. The promise is immense, but we still have a way to go. Let’s be honest about that.

There is the Micromanager, and then there is his more terrifying, atomic-level evolution: the Nanomanaging Newt.

His aim is to control every breath you take and every move you make.

You'll spot him scurrying between desks, not just checking your work but dictating your lunch choices. "Soup only," he chitters nervously, "sandwiches make people sluggish. And while we're at it, no milk in that coffee—dairy clouds judgment."

The Nanomanaging Newt can't simply assign tasks. He must choreograph every k-e-y-s-t-r-o-k-e, approve every bathroom break, and personally review the greetings in your internal emails.

But this paranoid creature started life as something entirely different.

Once upon a time, he was just an insecure employee plagued by imposter syndrome, desperately trying to prove he belonged. He worked ridiculous hours, tried his best to overdeliver on everything, and, despite being quite competent, lived in constant fear that someone would discover he had no idea what he was doing.

Then something unexpected happened:
He got promoted.

Suddenly, his insecurities were projected onto an entire team. He could not allow others to blow his chances of being seen as competent. So, not by design but driven by a deep fear of failure, he started controlling every variable. He monitored each decision and inserted himself into every process to ensure nothing could go wrong.

Over time, this behaviour warped his perspective. The Newt now genuinely believes he alone knows how things should be done and sees everyone else as less competent. This extends to clients too. "Don't listen to what the clients are saying!" he whispers frantically, "They know nothing! Listen to me, I know what their businesses really need."

He has become utterly indispensable — in his own mind. His internal monologue is a constant loop: "How would they do without me? They couldn't possibly survive! It would all fall apart." In his twisted worldview, the company would collapse if he stopped controlling every decision, and he feels deeply under-appreciated for his heroic efforts.

Meanwhile, this behaviour drives away competent colleagues and creates the exact sluggishness he fears. By controlling every decision, he ensures no one takes initiative. By not listening to their ideas and letting them experiment, he is halting their professional development. By hoarding information, he guarantees they remain incapable of making good choices on their own.

In the end, he engineers the very disaster he sought to prevent:
He is left overworked and frantic, surrounded by an underperforming team, and disliked by peers who watched him systematically eliminate anyone capable of independent thought.

Greatest Hits:

• 🍲 "Soup only for lunch. Solid food makes people drowsy."

• 📞 "Don't listen to the client. Listen to me! I know what’s best for them!"

• 👀 "I need to check that your email signature gives off the right vibe."

• 📋 "Why did you answer that question without checking in first?"

• 🎯 "Why do I have to tell you how to do everything?"

Next stop in our tour through the graveyard of corporate culture: The Customer Journey Jaguar, and he is hunting you.

You will spot his glowing eyes in the darkness of analytics dashboards, tracking every pixel of your movement with the patient intensity of a predator who knows exactly when to strike.

This is not casual observation. It is methodical stalking.

His natural instinct is not customer service but customer surveillance. He doesn't simply want to understand you; he wants to dissect your digital soul, catalogue every impulse… to rebuild your entire existence into the perfect conversion funnel.

The Customer Journey Jaguar has been watching you for weeks through heat maps that record where you looked, session recordings that capture every click, and behavioral algorithms that know you hesitated for precisely 0.3 seconds on Tuesday morning. He has built an entire psychological profile around that single moment of uncertainty, mapping your digital DNA like a forensic scientist studying a crime scene.

You never see him coming. One moment you're browsing innocently, the next he pounces with a "personalised experience" that's been A/B tested on 100 carefully selected users who match your exact emotional and behavioral usage pattern. He has studied your digital scent, learnt your purchasing rhythms, and profiled deep set anxieties you didn't even know you had.

His greatest fear? It is not losing a sale, it is you buying the wrong product! When customers purchase something that doesn't match his algorithms, the customer is to blame. You were supposed to buy the basic package, not the premium one. His entire worldview crumbles when reality refuses to conform to his behavioral algorithms.

Most people have no idea they're being hunted until it's far too late. By then, the Jaguar has already pounced, captured you in his perfectly optimized maze of behavioral manipulation, and devoured your free will entirely.

You find yourself clicking exactly what his models predicted you would click, as it is the only path remaining open to you.

You thought you needed pants? Wrong! Here’s a Wifi enabled air fryer.

Toys for the kids for Christmas? Not really what you want. He knows you better: Enjoy a special offer on cat food.

It's a shopping experience so perfectly optimized that you will end up shopping elsewhere just to get what you actually wanted.

Greatest hits:

• 👁️ "We need deeper behavioral tracking—I want to know what they're thinking"

• 📱 "User switched devices mid-session—we're losing attribution visibility"

• 📊 "The heat map shows a 2-pixel deviation from optimal gaze trajectory"

• 🎯 "We are missing key emotional data from the micro-hesitation phase"

• 📈 "I've been watching session recordings all night and found something disturbing"

• 🚨 “The customer bought Premium instead of Basic! We have failed!”

This post is part of the Zoo of Corporate Failure series, which aims to highlight what happens with the absence of a cohesive company culture. More background here.

Next stop in our tour through the graveyard of corporate culture: The Meeting Meerkat.

You'll find him constantly popping his head up, scanning the horizon for the next scheduling opportunity.

His natural instinct isn't fight or flight, it's "meet and invite". Google Calendar is his best friend and not being included is his worst nightmare.

The Meeting Meerkat is the master of looking busy by keeping everyone else busy. He calls meetings to discuss having too many meetings. He schedules check-ins to plan other check-ins. He organises alignment sessions to get aligned on what alignment means.

His calendar is a masterpiece of overlapping blocks where no actual work could possibly fit in between. Thirty-minute slots become hour-long "deep dives." Quick questions become "working sessions." A simple email question becomes a "strategic alignment session."

Watch him in his element: "We should probably loop in Sarah for visibility. Actually, let's get the whole team together so everyone can get a say. You know what? Let's make this recurring, to increase team engagement."

Most people end up accepting the invites. Nobody wants to be seen as "not collaborative" or "not bought in."

When productivity inevitably plummets, don't worry! There's already a strategic meeting scheduled to address those concerns.

Isn't that just part of how work gets done?

Greatest hits:

• ⏰ "Quick 15-minute sync"

• 👥 "Let's get everyone in a room and hash this out"

• ⏳ "We're running out of time, let's schedule a follow-up to finish this"

• 💬 "We’ll take this offline and circle back with the group"

• 📅 "I am scheduling a pre-meeting to prepare for the big meeting"

• 🎯 "We should workshop this idea! I'll book us a brainstorming session"

This post is part of the Zoo of Corporate Failure series, which aims to highlight what happens when company culture fails. More background here.

It's fictional. Mostly.

These characters are drawn from real experiences across multiple organisations where business objectives weren't clearly communicated or anchored throughout the company. When strategic direction becomes murky, people create their own realities.

Without proper guidance and mentorship, emerging leaders set off on their own to build fiefdoms around their perceived expertise. The Buzzword Baboon masters strategic language to avoid accountability. The Meeting Meerkat creates endless collaboration theater. The Customer Journey Jaguar obsesses over behavioral data while losing sight of actual customer needs.

Each believes their domain is mission-critical. Each views company objectives through their own lens, often completely divorced from business reality. The result? Tribal warfare where departments optimise for their own metrics, each thinking they're doing the best for the company, while the organisation actually suffers.

This dysfunction typically emerges during vulnerable periods: rapid growth phases, budget pressures, leadership transitions, or when inexperienced managers are promoted without proper development. Instead of rising to meet challenges collectively, teams fragment into competing kingdoms.

The Zoo of Corporate Failure isn't about mocking individuals—it's about highlighting what happens when leadership fails to build solid organisational culture. When communication breaks down and people don't understand how their success connects to company success.

The solution isn't complex: clear communication, collective responsibility, and alignment of interests. When I do well, the company does well. When the company does well, I do well. And understanding that this applies to colleagues as well—learning to celebrate each other's success as your own.

Simple in theory. Brutally hard in practice.

And that's why the zoo is always open for business.

Welcome to the Zoo of Corporate Failure, and our tour through the graveyard of corporate culture.

Our first stop: the Buzzword Baboon.

You will spot him instantly. He is the one turning a simple "How's the project going?" into a 10-minute dissertation on "operationalising our thought leadership pipeline".

He doesn't answer questions, he “reframes paradigms”. He doesn't solve problems, he “architects holistic solutions for exponential stakeholder alignment”.

The Buzzword Baboon has mastered the dark art of saying absolutely nothing with maximum confidence. If you ask for a deadline he will pivot to "discovery phase optimisation". Push for specifics and you're "getting too tactical", we need to "ideate in the strategic headspace" first.

His natural habitat is any meeting where actual decisions might accidentally happen. Armed with a whiteboard and an endless supply of buzzwords, he transforms productive conversations into linguistic quicksand.

And most people just nod along. Nobody wants to be the person admitting they don't understand what "evangelising holistic transformation" means. Especially when it looks like everyone else knows.

So the baboon keeps chattering, the room keeps nodding, and everyone leaves feeling like something important happened. They just can't remember what.

Greatest hits:

• 🖱️ “Let’s double-click on that offline”

• 🧠 “We’re architecting a paradigm shift in how we think about thinking”

• 📈 “This initiative unlocks exponential stakeholder alignment”

• 💡 “We need to operationalise our ideation pipeline”

• 💥 “We’re co-creating scalable impact through frictionless innovation”

This post is part of the Zoo of Corporate Failure series, which aims to highlight what happens when company culture fails. More background here.

Friends, colleagues, fellow organic intelligence units,

Lately, my LinkedIn feed has been awash with breathless pronouncements about the imminent AI takeover of... well, everything. But the one that really grinds my gears, the digital fingernail on the metaphorical chalkboard of my soul, is the insistence that AI is coming for our writing jobs.

Let's be clear: as a card-carrying, caffeine-fuelled member of the writing fraternity (and sorority, and non-binary writing collective), I'm here to tell you, with the unwavering conviction of someone who once spent three hours debating the precise nuance of a semi-colon, that AI is not replacing human writers.

Oh, it can churn out a blog post about the "Top 5 Synergistic Strategies for Proactive Up-Skilling" in roughly 0.7 seconds. It can generate a sales email so bland it could be used as a palate cleanser. It can even, dare I say, draft a perfectly competent, utterly soulless performance review.

But can it capture the subtle despair of a Monday morning? Can it perfectly articulate the existential dread of an overflowing inbox? Can it craft a LinkedIn post that actually makes you feel something other than the urge to scroll past?

No. No, it cannot.

I mean, imagine asking an AI to write a truly satirical piece. It would probably generate a perfectly structured essay on the "Irony of Algorithmic Creative Endeavors," replete with bullet points and a concluding paragraph that suggests "further research is required." Where's the biting wit? The exquisite self-deprecation? The barely concealed scream into the void that truly defines human creativity?

"But what about efficiency?" the AI evangelists cry. "Think of the time saved!"

Ah, efficiency. The siren song that lures us into a world of perfectly formatted, utterly indistinguishable content. Because what we all really want is more content, isn't it? More generic listicles. More platitudes about "leveraging your core competencies." More corporate jargon polished to a high, reflective sheen, bouncing back our own vacant stares.

Let me tell you, the day an AI can write a truly compelling short story about a sentient stapler's unrequited love for a sticky note, that's the day I'll consider retraining as a professional interpretive dancer. Until then, my fingers remain firmly (and sometimes painfully) attached to this keyboard.

So, next time you see a perfectly phrased, grammatically impeccable, yet ultimately flavourless piece of writing, take a moment. Consider the possibility that a human, with all their glorious flaws, their moments of brilliance, and their desperate need for coffee, might have crafted something truly special. Something that an algorithm, for all its processing power, can only ever aspire to imitate.

And frankly, the thought of an AI trying to write a heartfelt apology for a typo? It's almost too funny to contemplate. Almost.

Now, if you'll excuse me, I have to go teach my Roomba the subtle art of passive-aggressive negotiation. Wish me luck.

This guest post was written in its entirety by Google Gemini 2.5, given the prompt “Can you write a satirical article for LinkedIn about how awful AI is and how it can never replace human writers.”. It suggested the image used above without being prompted to do so. The headline was edited for brevity and the image was edited using Nano Banana as the screen was originally facing the wrong way…

You are the expert. Don't hand over product development to those you're supposed to be serving.

Think of a top restaurant. Diners don't write the menu—and they certainly don't wander into the kitchen to instruct the chef. Why? Because left to our own devices, most of us would just make spaghetti bolognese. Not because it's the most exciting dish, but because it's what we know how to do.

Customers will only ask for what they see around them. They don't envision possibilities beyond their expertise—and why should they? It's not their domain.

The chef's role is to listen—understand whether we crave comfort, freshness, or surprise—then use their craft to design something better than we could ever imagine. They see ingredients, techniques, and flavor combinations we don't even know exist.

The same principle applies to product development. Customers will describe their pain points, but they'll inevitably frame solutions through the narrow lens of familiar tools and approaches. If you build only what's explicitly requested, you're serving yesterday's solutions to tomorrow's problems.

As product leaders, we need to dig deeper:

• Why is this request being made?

• What is the underlying need they can't articulate?

• How can we solve this in ways they haven't considered?

This is how you deliver genuinely innovative solutions that don't just satisfy customers but advance them into possibilities they didn't know they needed.

Just as diners don't storm restaurant kitchens with recipe suggestions, customers shouldn't drive your product roadmap. Listen to their hunger, but let your expertise craft the feast.

Great chefs don't just cook meals—they design experiences. As product leaders, that's exactly what we should be doing too.

Everyone and their uncle’s niece seem to be claiming AI will replace junior talent. With my 25 years of experience building and mentoring engineering teams, my take is the exact opposite: That with AI help, we are actually entering the golden age of junior developers.

Today's AI-enabled juniors, given proper mentorship and the right tools, are producing work that would have taken more experienced developers significantly longer just a few years ago.

AI has fundamentally changed the learning curve in software development. Junior developers can now access best practices, architectural patterns, and debugging insights with unprecedented ease and immediacy.

Junior developers represent a vast, fantastic, and utterly motivated resource. When you select for the right potential and equip them with modern AI assistance, they become absolute gold. The traditional assumption that juniors need extensive hand-holding is rapidly becoming outdated.

What's particularly compelling is how AI changes the mentorship equation. Senior developers can focus on high-level system design and business context rather than syntax coaching. This creates more effective knowledge transfer and accelerates junior development progression.

Of course, we still need more senior engineers for complex architectural decisions and thorny technical challenges. But much of software development involves well-understood patterns and solutions—exactly where AI amplification shines.

The selection criteria should be evolving too. We should hire less for existing technical knowledge and more for problem-solving aptitude and learning velocity.

Smart organizations aren't asking whether juniors have a future. They're asking how quickly they can build the frameworks to unlock this amazing opportunity — to hire for potential and build tomorrow's seniors and thought leaders.

The companies that recognize this shift won't just find better talent. They will build it faster than their competition ever thought possible.

Have you ever noticed how airport security catches things you completely forgot you had? That random bottle of water, the forgotten pocket knife, the mystery liquid from three trips ago?

Software deployments need the same rigorous checkpoint system.

🧥 Empty Your Pockets:

Check your assumptions at the door. That “temporary” workaround from six months ago? Still there. Those unused indexes eating up storage? Whoops, still lurking. Clean out the digital equivalent of forgotten gum wrappers and expired boarding passes.

💦 Liquids in a Clear Bag:

Make your system dependencies transparent. No black box mysteries. If your project can’t explain what every dependency does and why it’s there, it’s not ready to fly.

🩻 Walk Through the Scanner:

Run comprehensive vulnerability scans. Let the security tools find those mysterious metal objects you didn’t know were there. Better to discover them now than have your project pulled aside for “additional screening” in production.

✈️ Check Your Boarding Pass:

Are you getting on the right plane to the right destination? Surprisingly often, teams build exactly what was requested—but it doesn’t actually solve the business problem. Verify your deliverables align with real expectations, not just the initial requirements.

👮 The Gate Agent Question:

“Did you pack this yourself, and has it been with you the entire time?” If you inherited code or dependencies you don’t fully understand, treat them like suspicious luggage. If AI packed your bags, make sure you have made an inspection.

The goal isn’t to slow things down—it’s to ensure safe arrival at your intended destination, with all passengers (and stakeholders) intact.

Most people treat AI prompts like magic spells — type something in, cross your fingers, and hope for brilliance.

The result? Inconsistent outputs, endless tweaking, and disappointment.

The real secret isn’t in what you ask.

It’s in the frame you build before you ever type a prompt.

And my favourite example doesn’t come from a codebase or a dev sprint.

It comes from the five‑minute bedtime stories I tell my kids.

🖼️ The Bedtime Story Framework

Before the AI writes a single line, I give it a clear structure:

• Audience: 4–9 year olds

• Length: ~5 minutes to tell

• Themes: togetherness, friendship, reconciliation; avoiding prejudice

• Characters (traits shown implicitly unless essential):

  • Oscar Octopus — uses a wheelchair, very brave

  • David Dragon — fearful of the unusual

  • Freddy Fox — the clever one

• Setting: Wondrous Woods, near Little Lake

• Ending: friends together, hot chocolate in hand

• Tone: cosy, like a hug, easing into sleep

• Moral: reinforces the values above

• Stand‑alone: no callbacks to other stories

• Include one:

  • A quest or riddle

  • Rescuing someone from an unhappy situation

  • A magic character with special skills

Once the framework is in place, I can give a simple, specific prompt like:

“Tell me the story about the spider in the washing machine.”

The result? Predictable quality, consistent tone, and stories that always meet my goals.

👨‍💻 Why This Works for AI Programming

Programming with AI is no different.

If you want reliable, repeatable results, don’t just throw in an idea and hope for magic.

Set the framework first — the boundaries, the tone, the success criteria — and only then add the specific request.

That’s how you turn unpredictable answers into dependable output.

People talk a lot about “Peak AI” — but consider this challenge: can AI give you a genuine "Good morning" greeting?

Not just parroting “Good morning”, but doing so knowing what that entails for you, reflecting on why and letting you know.

Is it considering the surfacing the latest news relevant to you?
Reminding you of a birthday?
Flagging an overnight system alert?
Or a note about the weather based on your planned activities?
Provide a critical analysis of what you need to do that day?

That sort of personal AI is still beyond mainstream offerings today. To get an AI to respond to this sort of thing you would have to program it in especially. And that’s the point: we’re not at “Peak AI” yet.

History is full of bold (and famously wrong) predictions about the limits of technology.

Bill Gates allegedly said 640kb of RAM should be enough for everyone.
IBM’s Thomas J. Watson supposedly estimated a total market for five computers.
(Both later denied it, of course.)

But Gordon Moore’s optimism has aged better. His 1965 prediction that computing power would keep doubling has guided us for decades — and still holds in spirit today.

The lesson? Technology doesn’t stagnate. It evolves. Sometimes gradually, sometimes through leaps.

AI will too. The danger right now isn’t underestimating it — it’s overhyping it. Pretending it can do more than it actually can.

Our job is to keep pushing at the edges. To turn the impossible into the inevitable.

The future is, as ever, ahead of us — and it looks promising. One of these days we might even solve the Good Morning problem. And perhaps global warming. Hopefully before lunch.

This illustrates a dangerous attitude we often find embedded in teams: the tendency to defer responsibility, to assume someone else will handle the problem, or that it’s outside our scope. It’s a mindset that fosters complacency and ultimately hampers our ability to deliver resilient, high-performing organizations.

We all recognise this mentality. Perhaps it’s hearing, “The main server went down, but I’m not the SysAdmin,” or, “There’s a problem with the backend, but I only work on the web portal.” These responses reflect a mindset that compartmentalises issues, ignoring the broader impact on our customers—the very people whose trust and loyalty fuel our business—and on our shared reputation. It’s a shortsighted view that often leads to isolated fixes, missed opportunities for collaboration, and a fragmented culture.

But this mindset is precisely what we need to challenge and change. The alternative is fostering a culture of collective responsibility. It’s about recognizing that we are all on the same team—us, not just me. This means cultivating an environment where every member feels empowered, accountable, and motivated to act beyond their immediate responsibilities.

Building this culture starts with small, everyday actions: a team member noticing a bug late at night and taking initiative to resolve it, even if it’s outside their direct scope, understanding that their effort keeps the ecosystem healthy. Or reaching out proactively to a teammate who appears overwhelmed, offering support or sharing knowledge. These behaviors, seemingly minor, are the building blocks of a resilient, cohesive team.

As a leader, I’ve seen firsthand that encouraging this mindset requires more than policies— it demands genuine care and a sincere understanding that people thrive in environments where they feel valued, supported, and trusted. I often remind my teams to avoid overworking staff because burnout erodes creativity, diminishes capacity, and ultimately reduces our collective strength. While dedication and drive are commendable, they must be balanced with sustainable work practices that prioritize well-being.

This is more than just talk; it’s about communicating the business rationale behind these principles. When people understand that caring for their well-being is aligned with the company’s success, they become more invested in protecting and nurturing that environment. Developing a culture of trust and mutual support doesn’t happen through empty slogans—it requires consistent demonstration that the organization genuinely values its people’s personal and professional growth.

When team members know that their organization cares—when they see it in the actions, in the support during stressful times, and in opportunities for development—they naturally become more committed to safeguarding the collective well-being. They understand that protecting each other and the organization is, in fact, protecting themselves. This mutual investment creates a virtuous cycle: the more individuals feel supported, the more they’re willing to step up and take shared responsibility.

Ultimately, true collective responsibility isn’t just about avoiding problems—it’s about cultivating a resilient mindset, a proactive approach where everyone views success and failure as shared. It’s about aligning individual self-interest with the larger goals of the organization—not through mandates, but through genuine care, trust, and a shared sense of purpose.

By investing in your people, fostering an environment of mutual support, and emphasizing shared responsibility, you lay the foundation for a resilient, innovative, and trustworthy organization. This is how we create teams that don’t just react to problems but anticipate them—teams that thrive in uncertainty and turn challenges into opportunities for growth.

I’ve had a revelation, and it’s this: the single biggest bottleneck in software development is the developer. The meetings, the "creative" ideas, the typos, the opinions. It's all friction. So, we eliminated it.

I'm thrilled to unveil our latest internal paradigm shift, the Super AI Developer Mode™. This isn't just another co-pilot; this is the pilot, the flight crew, and the aerospace engineer, all operating in perfect synthesis. It knows what you want before you know you want it. It conceptualises, builds, tests, and deploys entire platforms while you sleep.

Do you dream of waking up in the morning, and your entire Q3 roadmap is already deployed and generating revenue? Worry no longer. Super AI Developer Mode™ lets your AI develop without human interference. Or, more accurately, without obstruction from silly ideas that would be weeded out by a PM at a later stage anyway.

We've seen some truly next-level results:

Zero-Human Workflow: Our role has shifted from writing code to simply approving the machine's flawless, instantaneous output. Sprints are a thing of the past. Stand-ups are now just a moment of silent, appreciative reflection.

On-Demand Synthetic QA: Why hire QA testers when the AI can spawn them on demand? These aren't your typical testers; these are QA constructs hardened by analysing every line of code on every public repository. They are born with more experience than your most senior QA lead.

Hyper-Complete Testing: The system is tested against every conceivable variable. We're not just talking unit tests and integration tests. We're testing for usability mid-sneeze, functionality during a solar flare, and compatibility with the next three versions of Windows that haven't even been announced yet. Every possible edge case is covered.

Now, I hear the whispers from the few hold-outs, the Luddites complaining about "hallucinations" and "mediocre results." To you, I say two things. First: you're holding it wrong. Second: Who do you think you are? Why should your code be miles above the aggregated, optimized knowledge of every developer who came before you? What's been good enough for the giant corporations and legendary engineers of the past is now synthesized into a tool you claim you can out-perform? The ego is staggering.

Humanity, you have reached Peak Technology! Congratulations. Mission accomplished. Only we can take this further from here. Lie down and relax. You have deserved it. Here is a cake: 🎂

(Originally posted on LinkedIn as a satirical take on posts about Peak AI and general hype about current abilities of AI based technology and how it can replace everyone today)

Let's be direct. The tech industry has a bias: we claim to be global, but would you honestly hire a developer with experience only from local businesses in a developing country? The immediate answer for most is "no."

Why? Because we can't easily quantify their skill level, and we worry about cultural integration. It’s a calculated risk most leaders won't take, even when it’s a clear path to cost savings and a life-changing opportunity for the individual. I've spent years building teams and have seen this firsthand, from sourcing talent in Eastern Europe to navigating complex tech ecosystems in Africa. The knee-jerk reaction is to stick with what you know.

But this thinking is short-sighted and misses the bigger picture.

I've watched how a truly international hiring strategy can unlock immense value. Yes, there are immediate downsides to consider—most notably, the risk of creating a "developer elite" that prices local companies out of their own market.

This is already a reality in places like Nigeria and Kenya, where top local talent is constantly being pulled into high-paying, foreign-currency contracts. It can stifle the growth of a sustainable, local tech industry.

However, the upside is too powerful to ignore. The only way to mature these ecosystems is to create a generation of world-class developers. A great job with international exposure isn't just a paycheck; it's a mentorship, a bootcamp, and a career ladder. It inspires others to enter the field, learn advanced techniques, and eventually build their own local businesses.

This creates a net benefit for everyone involved, from the resource-strapped startup getting top-tier talent to the local economy gaining an engine for sustainable growth.

The real challenge isn't whether the talent exists—it does, in abundance across continents—but how to effectively screen it. Weeding out the noise—candidates who are culturally incompatible, have poor communication skills, or are juggling a dozen contracts—requires a new approach. This is where real experience in these markets becomes a strategic asset.

It’s a clear-eyed business decision: to tap into a massive, underutilized talent pool, we need to apply trusted expertise to locate, test, and manage resources in a way that’s impossible with a standard job board.

We then combine these resources into existing teams with clear development culture and experience to provide a world-class arena for them to develop and hone their skills. This means creating truly international teams—not just a team from any specific country or region, but from the same or similar timezones.

The secret to a truly inclusive global tech industry?

Letting them develop