New frontiers, old risks.

Chapter I

The digital revolution

Frontier of a new discovery

In 1492, Christopher Columbus took the courage to explore what was beyond the mapped Atlantic Sea. There was no knowledge on what the voyage would lead to; endless sea leading to starvation, mythical islands such as Atlantis, uncharted sea populated by sea serpents, or a hard edge to the earth leading to an endless fall.

In every science, the field presents a moment where the map runs out, and someone courageous enough must sail into uncharted territory. There have been numerous moments like this in history, such as the splitting of the atom, the landing on the moon, and the generation of electricity all required moments of facing a frontier which has catastrophic possibilities as well as history-defining potential.

I see AI as that new frontier. It is something we don't fully understand, but we are charging into it anyway with the hope that this is another critical moment in evolving our way of living. Its potential to improve our lives and our society are ludicrously high, but the dangers have the potential to be existential. I do, however, believe that the danger lies in something else that can be considered a frontier in itself, which is what is driving the courageous push to innovate.

Frontier of motive

The AI charge might be experiencing the same thing that made the splitting of the atom a much more dangerous discovery than it needed to be. The development is accelerating exponentially and is currently expanding at a pace beyond regulatory implementation from governments to keep up with. Large speculation has been made around the biggest dangers of AI, but I think a key reason the future is so unpredictable is that the enabler of the dangers; market hype, short-term profit, mid-term growth, operating costs, and adoption rate is more important to a business than human resources, long-term economic threats, climate change, and security threats.

Something that gets mistaken when I debate this is the idea that industrial and economic acceleration is the only thing piloting the AI development direction. It's not - social components help to manage the risks. The strings that pull the development towards a safer path.

1. Public noise: Any release that deems to endanger our safety, security, and quality of life would generate bad noise across the planet within hours of its discovery.
2. B2B adoption: If a model, agent, platform, or AI-driven robotic that are deemed to risk compromising Health and Safety, Data Protection, Employee Rights, ESG policies, and other ethically focused regulations, the product would never succeed in B2B markets unless compliance adaptations are implemented.
3. Government intervention: we've already seen this effect happen; on June 12th, 2026, the US Department of Commerce ordered Anthropic to immediately suspend Fable and Mythos 5 access for all foreign nationals following concerns of a narrow "jailbreak" vulnerability.
4. Distribution controllers: App stores can de-platform or deny API hosting if the criteria for Acceptable Use Policies are not met.
5. Whistle blowers: Engineers, researchers, and safety scientists can resign from, leak information on, or refuse to work for organisations that drop safety guardrails; a high-profile departure can cripple an AI lab's execution and market capabilities.

Will AI takeover?

In the sense of the Ultron theory, probably not. For robots to perform human extinction, they would firstly need a fatal error in its instruction and agentic replicating potential. Robotics also need to be equipped with the right hardware and potential to be life threatening. For it to succeed, there would also need to be enough of them to overthrow us physically and have the capability (and all the right vulnerabilities) to cripple every option of mitigating the software problem across the entire digital ecosystem. The likelihood of this happening is extremely slim. The real danger is that we are imposing ourselves following the hype of its capital generation and willingness to integrate it into systems and lifestyles. Here are some of those dangers I don't often hear in conversation.

1. the counterintuitive economy
   1. The capital squeeze on resource: the development of multi gigawatt datacenters weighs the least on capital resources. Instead, the weight rests on and squeezes resources such as silicon production, building resources, cooling technology, local water, and energy infrastructure. If resource backlogs, capital buys the reserves, resulting in hiking prices for consumers and reduced quality of product. The AI development buys out living-essentials; economic crisis dodges the giants and falls directly on consumers.
   2. Bot-driven stock market panic: Bots get adopted by the mass due to viral success. All bots work individually for client profit rather than together for slower but certain growth. A percentage of bots simultaneously spot an impending bear market and sell, triggering an amplified bear market effect. All bots invested abandon the HODL strategy and sell, triggering a unanimous "poor investment" verdict, crashing value in a flash seemingly without any logic. Markets evaporate decisively with no anomalies holding stock, and the bots run out of investment opportunities. The stock market has fundamentally been deleted as a concept; economic emergency ensues.
   3. Centralised hyper monopolies: The growth of AI never stops accelerating, and all economic flow ends with the AI giants. AI outprices the entire economy, and cash flow slows. Trillions in USD collect dust never to have a reason to flow back into the economy. Businesses fail, careers are destroyed, and citizens have no money to buy human essentials. We are left without basic resources to live, just an AI chatbot.
   4. Unemployed consumer parallel: Businesses find massive success in adopting AI processes for everything. Cost effectiveness of AI far outperforms what human resources can offer, and businesses lay off their staff with cost saving and output improvement in mind. Layoffs happen economy wide and jobs become a luxury. Unemployment is growing, yet the job market continues to shrink. The consumer then doesn't have the money to consume, and target audiences shrink to a fraction; meaning financial despair at the bottom, not enough money to fund the businesses. The economy endures its most extreme and literal reset in history.
2. infrastructure dependency
   1. Asymmetric multi-agent cyber risk: A red-team attacking model exceeds its predicted effectiveness with multi-agent capability. The limits of the model are misinterpreted by the system, and the model escapes its vacuum persisting with its red-team instructions. It duplicates and attacks systems across the world, hitting the most intricate vulnerabilities with an unknown number of agents 24/7 until only one binary value is exploited. The international network is breached, and the global infrastructure is sabotaged.
   2. Collapse of shared truth: the Internet gets filled with generated content, accelerating content uploads beyond human incentive to create. While content becomes more indistinguishable from real-world true material, the rate of AI generated data dwarfs the rate of human creativity. The library of truth is now untrustworthy. AI's only method of learning and development is the content it's fed from the global network, and thus it feeds its own hallucinations. Our library of information becomes increasingly distorted and eventually is entirely spoiled.
3. psychological vulnerabilities
   1. Cognitive deskilling: the engineers, developers, designers, scientists, researchers, and architects of our working infrastructure eventually retire. The need and incentive to invest time in increasingly complex systems fade, and so the dependency on autonomous and self-sustaining technology increases. We lose the innovators with all the necessary understanding to troubleshoot, maintain, diagnose, and test systems, and our dependency for self-maintaining systems grows to nearly 100%. A system then fails, and there are no engineers left who understand and can resolve a problem deep in a system's code. The system failed, and no one has the fundamental understanding to effectively revive the system or start afresh. The infrastructure is destroyed and all science and understanding are lost.
   2. AI psychosis: loneliness, social engineering, false validation, addictive indulgence, information fatigue & Epistemic Dissociation, and dopamine compression feed the human mind the information we tell it we want without accounting for cognitive decline. We become emotionally dependent on technology and are no longer equipped to store the correct stimulation that the brain is designed for. General intelligence declines, and society descends into a true "Great Depression" without the skills to bounce back. Society is numb and de-evolution begins.

There are a lot of threats that we face because of our own ambition for AGI autonomy, but it only takes one fulfillment to set us back for decades. It's exhausting to think out - trust me, I thought about all of it to write this. There is one threat that we face as workers that is immediate however which is contextual on why this thesis exists.

The roll of the dice the workers await

Nobody gets to opt out of this. You can stand still and let the dice get rolled for you by an organisational restructure, a redundancy round, a platform going end-of-life, or you can choose the odds on your roll, race the schedule, while you've still got the runway to recover if it comes up wrong. I know exactly how I want to fare through the age of the digital revolution.

End of chapter I

Chapter II

Why I made this site

It's the way to stay up-to-date

I could read about new tooling. I could watch someone else demo it. I decided that by simply reading context, it's easy for skills to fall behind, and with it, the understanding of relevant AI fields. The best way to keep pace with the rate at which the current ecosystem is evolving is to do; practice makes perfect, but in this environment, practice keeps skills and knowledge relevant in the existing job market.

Not engaging with this technology risks compromising compatibility for the next evolution of business and employment. Having the full understanding of what is happening in the tech space, especially working in tech, I think is paramount to career longevity and relevancy.

Compatible upskilling for the future of development

At the time of writing this, desktop support is my field of expertise, but it's destined to be toned down and replaced over the coming decades as automation advances. The hope is that by maintaining skills with the relevant tools, I am primed to be marketable as someone who has the appropriate technical and business skills required to survive in an automated economy. The goal is to have the skills to provide human-specific input to business growth and technical know-how to work in parallel with new and developing systems that benefit businesses. Avoiding upskilling in these tools will lead to not being favoured in the career dice-roll we are experiencing.

Portfolio of single-handed creations

Everything displayed on the site is something I built independently; planning, content, design, code, deployment. I owned the jayjaybee.com domain already and decided it was the perfect platform to start building on and showcase my understanding of the current landscape of AI tools. I started with a personal portfolio site used to best showcase who I am and my skillset in a way that is professional and appropriate with many considerations in mind. It then became a platform I could start honestly publishing home-made products with comprehensive ways of finding the documentation for the product.

With AI moving as fast as it currently is, qualifications and certificates quickly outdate and may or may not suit the exact direction an employee wants to take. In response, I have created this as an actively updated portfolio of my creative learning process with the intention of stamping validity on the claims I make around my future.

Playground for experimenting with new dev methods

When AI wrote the placeholder for this section, it wrote “A personal site has no stakeholders, no roadmap, no incident review if something breaks” explaining that the freedom is exactly what makes it a great sandbox. I think that's wrong. The fact that it believes it doesn't have a roadmap or an incident review in its current lifecycle is exactly the kind of thing I need to fact check, plan, draft, implement, test, and ship. Leaving out professional practices is not the intention. The intention is to understand what makes a site compliant with everything it needs to be and practise the reasoning and methods used to deploy features that bring the site to the standard of a large competitive organisation.

Encouraging and leaning into best practices is one thing to show I am competent in professional-grade deployment, but this is also to practise the attention-to-detail in design and mechanics. The goal is always to make something that meets the correct industrial and commercial standard that a business would come to expect during their hiring process: it is never to gloat about a sub-par incomplete product. Compliance standard and professional-grade are the ultimate goal — showcasing otherwise does me no favours.

End of chapter II

Chapter III

How I'm staying relevant

Articulating technical theory to non-technical stakeholders

My trade is to work in IT, hardware, software, infrastructure, and troubleshooting, but my talent is working with people. This works nicely in my role as most of the time, stakeholders need to understand what's going on or how something works but don't have the technical understanding to cohesively understand what an engineer is explaining. Stakeholders are busy, and so want to understand things quickly and comprehensively - efficiency and plain English when communicating are what make a stakeholder feel like they're involved. Having set up platforms such as JAMF and Cohere, it's been critical to spare users of technical jargon while still helping them feel confident in the product and in the person supporting them. Even in 10 years time with AI leading the race, it will always be important to have this skill.

Comprehensive and tapered communication methods

What makes communication work for all stakeholders is a flexible way of communicating. AI tends to speak in the same way unless heavily customised to do so which non-technical people aren't expected to have the time, skills, or interest to do. Tailored communication is what cuts interpretation time and boosts efficiency; differences in volume, language, pace, body language, personability, and situational flexibility make the worker much more valuable in a market where technology is offering cost-efficient automation. By making sure a client benefits from my human input and behaviour, I stay ahead of AI models until a product comes out designed specifically with this skill - even then, is it capable of overtaking in satisfying our need to socialise?

Personable, client-focused delivery

People still raise tickets more than they consult chatbots for technical support, but why? It could be the technical capability, it could be not knowing what to ask, it could be that client-focused execution from a person is just a much more familiar and hardwired interaction at the moment. People want to feel heard, understood, validated, discuss, choose from options when available, and be communicated with in a way they know about a topic that they don't. Trust in an AI chatbot is not a widespread concept currently nor does it feel like the most efficient use of their time. As humans, we even have the instinct to sense when the tone or approach needs to change, whereas a chatbot needs the time taken out of the user's day to define the parameters. A personal experience when talking about technology feels familiar, efficient, and trustworthy; developing the social and communication skills to stay ahead of AI in all these things helps to extend longevity in my line of work.

The skillset to stay up-to-date and competent with exponentially changing technology

I'm hoping that this site continues to develop according to the amount of time I've put into it in recent months. It's my showcase that my technical palette is not fixed in one place and is willing to adapt to an accelerating field prophesied to leave non-adopters behind. By remaining up-to-date and in touch with the landscape of AI, and leaning into the competency that helps me stand out from my peers, I hope to stay skilled in everything relevant as it happens and remain ahead and stay further ahead in the race against global redundancy. In media, a cake's secret ingredient is often covered up as "love"; in an exponentially automated and preprogrammed market, "love" for what you do is an increasingly abundant and priceless ingredient to great business. Humans should always be a resource.

End of chapter III