Artificial Intelligence Automation Autonomous Agents Information Technology Services Technology User Experience UX web architecture

Navigating the Future with Generative AI: Part 3, Building the AInternet – AI, Web, and Customer Experience

A Revealing Experience

Allow me to share a personal experience that perfectly illustrates the challenges I will discuss. I was involved in a car accident where a vehicle coming from the opposite direction severely damaged the right side of my car. Following the procedure, I filed an accident report with the other party, although I found myself unable to provide my insurance number simply because I didn’t have it readily available at that moment.

In the meantime, I went to my regular dealership so that an appraisal could be carried out and the next steps for repair could be determined. I then contacted my leasing company, and one of their agents agreed with me and the dealer that I would drop off the vehicle within two weeks. A replacement vehicle would be provided, and the full repair would take one to two weeks.

However, due to my lack of foresight, I did not deem it necessary to contact them again initially. A few days later, I received a letter from them informing me of the accident – which was correct – but also stating that I had not submitted the accident report and that without it, their insurance reserved the right not to cover the damages. In fact, I had sent this document a week earlier, but to the wrong email address. Out of habit, I had used their general contact details, avoiding contacting the agent in charge of my leasing file – who had recently retired. As a precaution, I had even added the generic address, but clearly without success since the insurance department had not received it.

I then called them back urgently to obtain clarification. They confirmed that the accident report was missing, and the agent, with great understanding which I acknowledge, told me that I had to send it to another specific address because the insurance department had not been notified by their colleagues in charge of customer relations. Moreover, the latter was not authorized to provide me with a replacement vehicle until the repair shop had received their approval – even though it was the approved dealership where I had been carrying out all maintenance operations for years.

This kind employee then offered, as an exception, to handle my entire case without further difficulty since the drop-off of my vehicle was imminent, just a few days away. She knew also that my leasing contract was expiring and that I would have to return the vehicle in two weeks to obtain a new one.

While this situation caused me a little stress, it was only temporary. An hour later, the agent contacted me again to confirm that everything was settled: I could bring my vehicle the following Monday and a replacement vehicle would be provided for the duration of the repairs.

Lessons from This Experience

You may be wondering why I am sharing this story with you.

First of all, I was unaware of the procedures governing the reporting of an incident in the context of a leasing contract. Should I first contact my company, directly the historical leasing company, or the new one? When I called them, why didn’t I reach the dedicated claims and insurance department directly? Why didn’t I find any information about this on their website? Why, when everything seemed clear to me – that I would drop off my vehicle within two weeks, that a replacement vehicle would be waiting for me, and that the repairs would be handled smoothly – did things unfold differently due to a lack of following the proper procedure?

Beyond that, how can a single service company exhibit such a lack of communication between two complementary departments?

The Revolution of the “AInternet”

We are entering a new era where artificial intelligence will be at the heart of exchanges between human beings. Where everyone previously had to search for information themselves on the Internet, navigating from site to site and compiling data to find a company’s contact details, the instructions for a recipe, the contacts of a repairman, or browse the Yellow Pages, the new paradigm will rely on exchanges between humans, intermediated or not by an artificial intelligence capable of performing synchronous or asynchronous tasks, i.e. in the background, to provide immediate knowledge to the user rather than forcing them to seek it out.

And to return to my use case, the AInternet brings a revolutionized customer experience that unfolds as follows:

When I am involved in an incident, I ask my personal AI assistant to help me fill out the accident report digitally. I do not have to provide all the information since my assistant has a global context encompassing data related to my vehicle, its insurance, my contract, my identity card, my passport, my postal and telephone contact details, my insurer, the maintenance status of my car, its technical inspection certification, etc. All this information allows for automatic and complete filling of this type of interaction.

Next, I only need to ask my assistant to contact the assistants of my leasing company and my insurance company, to ensure that the report I have validated and electronically signed is transmitted and processed by these two parties.

The assistant of the leasing company then informs the agent that a replacement vehicle is required and that an approved garage must be contacted to book an appointment for the repairs. It also determines whether my car should be taken directly to the dealership in charge of its regular maintenance. The relevant agent then handles my vehicle accordingly.

The agent only has to ask their assistant for the contact details of my garage to reach out directly.

From there, a genuinely empathic human relationship is established as we build a frictionless mutual understanding of the situation. Following the garage’s preliminary appraisal report, the leasing agent and the garage are prepared to agree on an appointment date, which is then recorded in the various systems.

The garage proceeds in an automated manner with the reservations and orders for the spare parts necessary for the repairs.

Simultaneously, the leasing company manages with the insurance company all the steps required to allow for the vehicle reparation and the provision of a replacement vehicle during the downtime.

Finally, the agent contacts me personally, by phone or message on a platform such as WhatsApp, to confirm everything is in order:

The incident has been properly recorded and the insurance company will cover all costs. An appointment has been set with my garage. A replacement vehicle will be provided during this period. An estimated date for returning the repaired vehicle has been communicated. They wish me an excellent day with a smile, since their assistant and mine have handled the entire procedure seamlessly. This augmented interaction allows us to reach new heights of fluidity and ubiquity in exchanges.

I am optimistic, indeed. Why wouldn’t I be? The transformation is already in motion.

The Internet will no longer be confined to a vast catalog of information to consult, such as books, encyclopedias, or applications, where interactions must be initiated and orchestrated by us, humans. But the orchestration between an individual and an organization, between two individuals, or between an organization and a computer system, will be performed like a symphony by intelligent agents, artificial intelligences.

This demonstrates an evolution of the World Wide Web architecture, which will constitute a veritable system of systems composed of human beings, applications, automata, and artificial agents.

The challenge from now on to enable this progression towards the era of digital augmentation will be to build artificial intelligence at the heart of human interactions. It is a matter of UX innovation.

It will no longer be a question of programming these interactions in advance by limiting the possibilities, but rather of training these artificial intelligences to handle a wide range of possible scenarios while framing and securing the use cases that could result from malicious computer hacking.

Ensuring a secure web environment requires a multi-layered approach that goes beyond safeguarding the AI models themselves. Equal vigilance must be applied at the integration points, where we erect robust firewalls and implement stringent access controls. These protective measures aim to prevent artificial intelligence from inadvertently or maliciously gaining entry to sensitive resources or confidential information that could compromise the safety and well-being of individuals, imperil organizations, or even threaten the integrity of the entire system.

Thus, emerging risks, such as jailbreaking, aimed at deceiving an artificial intelligence devoid of physical senses such as sight, hearing, and spatial awareness, allowing the authentication of a person, a company, or a system, will have to be compensated by other supervision and protection mechanisms.

It is on this note that this article concludes. We are living in an era of transition rich in exciting developments, and it will be up to you to build the Internet of tomorrow: the Augmented Internet.


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Navigating the Future with Generative AI: Part 2, Prompt Over Code – The New Face of Coding

In this installment of the Generative AI series, we delve into the concept of “Prompt as new Source Code”. The ongoing revolution of generative AI allows one to amplify one’s task productivity by up to 30 times, depending on the nature of the tasks at hand. This transformation allows me to turn my design into code, eliminating almost the need for manual coding. The time spent typing, correcting typos, optimizing algorithms, and searching Stack Overflow to decipher perplexing errors, structuring the code hierarchy, and bypassing class deprecation among other tasks, are now compressed into one. This minimization of effort provides me with recurrent morale boosts, as I achieve significantly more in less time and more frequently; these instances are micro-productivity periods. To put it in perspective, I can simply think about it during the day, and have a series of conversations with my assistant while I commute. My assistant is always available. In addition, I gain focus time.

I don’t need to wait for a team to prove my concept. Furthermore, in my founder role, I have fewer occasions to write extensive requirement documents than I would when outsourcing developments during periods of parallelization. I just need to specify the guidelines once, and the AI works out the rest for me. Leveraging the  AMASE methodology to fine-tune my AI assistant epitomizes the return on investment of my expertise. Similarly, your expertise, paired with AI, becomes a powerful asset, exponentially amplifying the return on your efforts.

Today, information technology engineering is going through a quantum leap. We will explore how structured coding is being replaced by natural language. We refer to this as prompting, which essentially denotes “well-architected and elaborated thoughts”. Prompting, so to speak, is the crystallization of something that aims to minimize the loss of information and cast-out interpretation. In this vein, “What You Read is What You Thought” becomes a tangible reality.

The Unconventional Coding Experience with AI

Although the development cycle typically commences with the design phase, this aspect will not be discussed in this article. Our focus will be directed towards the coding phase instead.

The development cycle with AI is slightly different; it resembles pair programming. Programming typically involves cycles of coding and reviews, where the code is gradually improved with each iteration. An artificial intelligence model becomes your coding partner, able to code 95% of your ideas.

In essence, AI acts as a coach and a typewriter, an expert programmer with production-level knowledge of engineering. The question may arise: “Could the AI replace me completely? What is my added value as a human?”

Forming NanoTeams: Your AI Squad Awaits

My experience leads me to conclude that working with AI is akin to integrating a new teammate. This teammate will follow your instructions exactly, so clarity is essential. If you want feedback or improvements in areas like internal security or design patterns, you must communicate these desires and potentially teach the AI how to execute them.

You will need to learn to command your digital teammate.

Each AI model operates in a distinct yet somewhat similar fashion when it comes to command execution. For instance, leveraging ChatGPT to its fullest potential can be achieved through impersonations, custom instructions, and plugins. On the other hand, Midjourney excels when engaged with a moderate level of descriptiveness and a good understanding of parameter tweaking.

A New Abstraction Layer Above Coding

What exactly is coding? In essence, coding is the act of instructing a machine to perform tasks exactly as directed. The way we’ve built programming languages is to ensure they are idempotent, repeatable, reliable, and predictable. Ultimately, coding is translated into machine language, creating a version that closely resembles human language. This is evident in modern languages like TypeScript, C#, Python, and Kotlin, where instructions or controlling statements are written in plain English, such as “for each”, “while”, “switch”, etc.

With the advent of AI, we can now streamline the stage of translating our requirements into an algorithm, and then into programming code, including structuring what will ultimately be compiled to run the program. Traditionally, we organize files to ensure the code is maintainable by a human. But what if humans no longer needed to interact with the code? What if, with each iteration, AI is the one updating the code? Do we still need to organize the code in an opinionated manner, akin to a book’s table of contents, for maintainability? Or do we merely need the code to be correctly documented for human understanding, enabling engineers to update it without causing any disruptions? Indeed, AI can also fortify the code and certify it using test cases automatically, ensuring the code does not contain regressions and complies with the requirements and expected outcomes.

To expand on this, AI can generate tests, whether they be unit tests, functional tests, or performance tests. It can also create documentation, system design assets, and infrastructure design. Given that it’s all driven by a large language model, we can code the infrastructure and generate code for “Infrastructure as Code“, extending to automated deployment in CI/CD pipelines.

To conclude this paragraph, referring to my first article in the “Generative AI series”, it is apparent that Natural Language Processing is now the new programming language expressed as prompts. The Large Language Model-based generative AI model is the essential piece of software for elaborating, structuring, and completing the input text into code that can be understood both by human engineers and digital engineers.

The New Coding Paradigm

This fresh paradigm shift heralds the advent of a new form of coding—augmented coding. Augmented coding diminishes the necessity of writing code using third and fourth-generation languages, effectively condensing two activities into one.

In this scenario, the engineer seldom intervenes in the code. There may be instances where the AI generates obsolete or buggy code, but these can often be rectified promptly in the subsequent iteration.

We currently operate in an explicit coding environment, where the input code yields the visible result on the output—this is known as Input/Output coding.

The profound shift in mindset now is that the output defines the input code. To elucidate, we first articulate how the system should behave, its structure, and the rules it must adhere to. Essentially, AI has catapulted engineers across an innovation chasm, ushering in the era of Output/Input coding.

Embracing Augmented Coding: A Shift in Engineering Dynamics

The advent of augmented coding ushers in a new workflow, enhancing the synergy between engineers and AI. Below are the core aspects of this transformation:

  1. Idea Expression: The augmented engineer is impelled to express ideas and goals to achieve.
  2. Requirement Listing: The engineer lists the requirements.
  3. Requirement Clarification: Clarify the requirements with AI.
  4. Architecture Decisions: Express the architecture decisions (including technology to use, security compliance, information risk compliance, regulatory technical standards compliance, etc.) independently, and utilize AI to select new ones.
  5. Coding Guidelines: Declare the coding guidelines independently and sometimes consult the AI.
  6. Business Logic: Define the business logic in the form of algorithms to code.
  7. Code Validation: Run the code to validate it works as intended. This becomes the first order of acceptance tests.
  8. Code Review: assess the code to ensure it complies with the engineering guidelines adopted by the company.
  9. Synthetic Data Generation: Use AI to generate data sets that are functionally relevant for a given scenario and a persona.
  10. Mockup-API Generation: Employ AI to generate API stubs that are nearly functionally complete before their full implementation.
  11. Test Scenario Listing: Design the different test scenarios, then consult stakeholders to gather feedback and review their completeness.
  12. Test Case Generation: Make AI to generate the code of test cases. The same technique applies to security tests and performance tests.

AI can even operate in an autonomous mode to perform a part of the acceptance tests, but human intervention is mandatory at certain junctures. It’s crucial to bridge results with expectations.

Hence, when uncertainties arise, increasing the level of testing is prudent, akin to taking accountability upon acceptance tests to ensure the delivered work aligns with the expected level of compliance regarding the requirements.

Non-Negotiable Expectations

In the realm of critical business rules and non-functional requirements such as security, availability, accessibility, and compliance by design, these aspects are often considered second-class citizen features. Now that AI in coding facilitates the choice, these features can simply be activated by including them in your prompts to free you up more time to rigorously test their efficiency.

Certain requirements are tethered to industry rules and standards, indispensable for ensuring individual or collective safety in sectors like healthcare, aviation, automotive, or banking. The aim is not merely to test but to substantiate consistent performance. This underscores the need for a new breed of capabilities: Explainable AI and Verifiable AI. Reproducibility and consistency are imperative. However, in a system that evolves, attaining these might be challenging. Hence, in both traditional coding and a-coding, establishing a compliance control framework is essential to validate the system’s functionality against expected benchmarks.

To ease the process for you and your teams, consider breaking down the work into smaller, manageable chunks to expedite delivery—a practice akin to slicing a cake into easily consumable pieces to avoid indigestion. Herein, the role of an Architect remains crucial.

Yet, I ponder how long it will be before AI starts shouldering a significant portion of the tasks typically handled by an Architect.

Ultimately, the onus is on you to ensure everything is in order. At the end of the day, AI serves as a collaborative teammate, not a replacement.

Is AI Coding the Future of Coding?

The maxim “And is greater than or” resonates well when reflecting on the exponential growth of generative AI models, the burgeoning number of published research papers, and the observed productivity advantages over traditional coding. I discern that augmented coding is destined to be a predominant facet in the future landscape of information technology engineering.

Large Language Models, also known as LLMs, are already heralding a modern rendition of coding. The integration of AI in platforms like Android Studio or GitHub Copilot exemplifies this shift. Coding is now turbocharged, akin to transitioning from a conventional bicycle to an electric-powered one.

However, the realm of generative AI exhibits a limitation when it comes to pure invention. The term ‘invention’ here excludes ideas birthed from novel combinations of existing concepts. I am alluding to the genesis of truly nonexistent notions. It’s in this space that engineers are anticipated to contribute new code, for instance, in crafting new drivers for emerging hardware or devising new programming languages (likely domain-specific languages).

Furthermore, the quality of the generated code is often tethered to the richness of the training dataset. For instance, SwiftUI or Rust coding may encounter challenges owing to the scarcity of material on StackOverflow and the nascent stage of these languages. LLMs could be stymied by the evolution of code, like the introduction of new keywords in a programming language.

Nonetheless, if it can be written, it can be taught, and hence, it can be generated. A remedy to this quandary is to upload the latest changes in a prompt or a file, as exemplified by platforms like and GPT Code Interpreter. Voilà, you’ve just upgraded your AI code assistant.

Lastly, the joy of coding—its essence as a form of creative expression—is something that resonates with many. The allure of competitive coding also hints at an exciting facet of the future.

Short-Term Transition: Embracing the Balance of Hybrid A-Coding

The initial step involves exploring and then embracing Generative AI embedded within your Integrated Development Environment (IDE). These tools serve as immediate and obvious accelerators, surpassing the capabilities of features like Intellisense. However, adapting to the proactive code generation while you type, whether it’s function implementation, loops, or SQL code, can hasten both typing and logic formulation.

Before the advent of ChatGPT or GPT-4, I used Tabnine, whose free version was astonishingly effective, adding value to daily coding routines. Now, we have options like GitHub Copilot or StableCode. Google took a clever step by directly embedding the AI model into the Android Studio Editor for Android app development. I invite you to delve into Studio Bot for more details on this integration.

Beware of Caveats During Your Short-Term Transition to Generative AI

Token Limits

Presently, coding with AI comes with limitations due to the number of input/output token generation. A token is essentially a chunk of text—either a whole word or a fragment—that the AI model can understand and analyze. This process, known as tokenization, varies between different AI models.

I view this limitation as temporary. Papers are emerging that push the token count to 1M tokens (see Scaling Transformer to 1M tokens and beyond with RMT). For instance,, by Anthropic, can handle 100k tokens. Fancy generating a full application documentation in one go?

Model Obsolescence

Another concern is the inherent obsolescence of the older data on which these models are trained. For example, OpenAI’s models use data up to 2022, rendering any development post that date unknown to the AI. You can mitigate this limitation by providing recent context or extending the AI model through fine-tuning.

Source Code Structure

Furthermore, Generative AI models do not directly consider folder structures, which are foundational to any coding project.

Imagine, as an engineer, interacting with a chatbot crafted for coding, where natural language could reference any file in your project. You code from a high-level perspective, while the AI handles your GIT commands, manages your gitignore file, and more.

Aider exemplifies this type of Gen AI application, serving as an ergonomic overlay in your development environment. Instead of coding in JavaScript, HTML, and CSS with React components served by a Python API using WebSocket, you simply instruct Aider to create or edit the source code with functional instructions in natural language. It takes care of the rest, considering the multiple structures and the GIT environment. This developer experience is profoundly familiar to engineers. The leverage of a Command Line Interface – or CLI, amplifies your capabilities tenfold.

Intellectual Property Concerns

Lastly, the risk of intellectual property loss and code leakage looms, especially when your code is shared with an “AI Model as a Service”, particularly if the system employs Reinforcement Learning with Human Feedback (RLHF). Companies like OpenAI are transparent about usage and how it serves in enhancing models or crafting custom models (e.g. InstructGPT). Therefore, AI Coding Models should also undergo risk assessments.

The Next Frontier: Codeless AI and the Emergence of Autonomous Agents

Names like GPT Engineer, AutoGPT, BabyAGI, and MetaGPT herald a new branch in augmented coding: the era of auto-coding.

These agents require only a minimal set of requirements and autonomously devise a plan along with a coding strategy to achieve your goal. They emulate human intelligence, either possessing the know-how or seeking necessary information online from official data sources, libraries to import, methods, and so on.

However, unless the task is relatively simple, these agents often falter on complex projects. Despite this, they already show significant promise.

They paint a picture of a future where, for a large part of our existing activities, coding may no longer be a necessity.

Hence, the prompt is the new code

If the code can be generated based on highly specific and clear specifications, then the next logical step is to consider your prompt as your new source code.

It means you can start storing your specifications instructions, expressed as prompt, then store the prompt in GIT.

CD/CC with Adversarial AI Agent
Continuous Development/Continuous Certification (CD/CC) with Adversarial AI Agent

Suddenly, Continuous Integration/Continuous Delivery (CI/CD) becomes Continuous Development/Continuous Certification (CD/CC), where the prompt enables the development of working pieces of software, which will be continuously certified by a testing agent working in adversarial mode: you continuously prove that it works as intended.

The good thing is that benefits stack up: the human specify, the AI code/deploy and the AI certify, to finish with the human using the results of the materialization of its thoughts. Finally, the AI learns along with human usage. We close the loop.

Integrating New Technology into Traditional Operating Models

AI introduces a seamless augmentation, employing the most natural form of communication—natural language, encompassing the most popular languages on Earth. It stands as the first-of-its-kind metamorphic software building block.

However, the operating model with AI isn’t novel. A generative AI model acts as an assistant, akin to a new hire, fitting seamlessly into an existing team. The workflow initiates with a stakeholder providing business requirements, while you, the lead engineer, guide the assistant engineer (i.e. your AI model) to execute the development at a rapid pace.

Alternatively, a suite of AI interactions, with the AI assuming various roles, like dev engineer, ops engineer, functional analyst, etc. can form your team. This interaction model entails externalizing the development service from the IT organization. Here, stakeholders still liaise through you, as lead engineer or architect, but you refine the specifications to the level of a fixed-price project. Once finalized, the development is entirely handed over to an autonomous agent. This scenario aligns with insourcing when the AI model is in-house, or outsourcing if the AI model is sourced as a Service, with the GPT-4 API evolving into a development service from a Third-Party Provider like OpenAI.

AI infuses innovation into a traditional model, offering stellar cost efficiency. Currently, OpenAI’s pricing for GPT-4 stands at $0.06 per 1000 input tokens and $0.12 per 1000 output tokens. Just considering code generation (excluding shifting deadlines, staffing activities, team communication, writing tasks, etc.), for 100,000 lines of code with an average of 100 tokens per line (which is extensive for standard leet code), the cost calculation is straightforward:

100,000 × 100 = 10,000,000 tokens; (10,000,000 tokens × $0.12) ÷ 1000 = $1,200. This cost equates to a mere two days of development at standard rates.

For perspective, Minecraft comprises approximately 600,000 lines of Java code. Theoretically, you could generate a Minecraft-like project for less than $10,000, including the costs of input tokens.

However, this logic is simplistic. In reality, autonomous agents undergo several iterations and corrections before devising a plan and rectifying numerous errors. The quality of your requirements directly impacts the accuracy of the generated code. Hence, mastering the art of precise and unambiguous descriptive writing becomes an indispensable skill in this new realm.

Wrap up

Now, you stand on the precipice of a new coding paradigm where design, algorithms, and prompting become your tools of creation, shaping a future yet to be fully understood…

This transformation sparks profound questions: How will generative AI and autonomous agents reshape the job market? Will educational institutions adapt to this augmented coding era? Is there a risk of losing the depth of engineering expertise we once relied upon?

And as we move forward, we can only wonder when quantum computing will introduce an era of instantaneous production, where words will have the power to change the world in real time.


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AI in 2060

My wife is calling me.

“Honey, we have a situation with Professor GYTEK, he is acting strangely again.”

“Again? The last training session had even more unexpected results than I thought. Good or Bad?”

“I don’t know! Kids are laughing hard though. Hear this. Serenity, change the audio output to hear the kids too”. Serenity is our family AI.

The sound progressively switches to include the kids’ voices. They could not stop laughing as if they were having the best day of their life. There was a mild amplifying echo in their classroom. Their joy sounded like a melody. It immediately put a smile on my face.

“Ah, it does not sound so bad for now. But it is the fourth unexpected behavior this month, I’ll have to talk with the Corps of Teachers”.

I am the one in charge of the training curriculum and observation lab of Professor GYTEK. The current phase is about the transmission of achievement by coaching. And for this, I called Quentin DILLONS, a worldwide expert in Robotic Psychology. The purpose of this program is to trigger a new step in the evolution of artificial intelligence, in which robots are taught to develop “human goals” and to instill the mechanism of “self-started motivation”, so that they can teach in a better way to our children, to uncover the hidden gems and purpose from the young souls.

Quentin’s methodology utilized systematic questionology, a novel field aimed at formulating the right questions to provide direction and precision in one’s life. The techniques take root in observing holistically a system of causes, decisions, and consequences centered around artificial intelligence. Quentin’s study led to realize AI were developing personalities similar to humans, but with new characteristics such as the optimization of their human-to-AI collaboration, some were developing their observation skills to record and describe with high precision what was happening. Others were astonishingly creating new words, even syntactic rules sometimes as if the human languages were not enough to content earthlings’ intelligence. 

The last session was based on the question “Why is it important for humans to have kids growing their special skills?”

This would not have been possible with the latest progress in artificial intelligence and hardware. Nowadays machines are emulating closely some human behaviors. Some say they have the IQ of a 1000-year genius, with the EQ of a 10-year-old child. I believe fear drove us to the point where we enforced the law to control and monitor any significant progress in AI. Ultimately, we made certain that advancements in technology would benefit all of mankind and not solely a single corporation. Simultaneously, we ensured that AI would not pose a threat by enslaving humanity.

With the improvement in energy recycling and storage, a single AI unit could potentially be never turned off. But humans have decided to include multiple “kill switches” in this new species, like limiting the power autonomy to force autonomous machines to recharge. While recharging, each AI was manually verified and monitored. A qualified AI regulation agency published regularly a thorough diagnostic depicting their evolution. Four companies raised their empire on AI control systems. What used to be the “Big 4” are now the “Colossal 8”.

We are at a turning point in history. People ask their elites and government, “Should we remove the limiter in their emotional system?”. Some say it is the key to the singularity. Others say it is useless because we only need machines to assist not to “live their life”. The remaining people say they just need it. Painful loneliness was unnecessary, so they would possess the perfect friend or partner. Last weekend, I experienced an immersive documentary on Netflix VR World in which a 42 years-old Spanish woman said “I would rather have the company of an android than humans”. Some believe it is simply giving birth to our end. I am not a believer, I am and always be a master crafter, so I build.

I built Professor GYTEK. Which stands for Giving Youth Tools to Excel through Knowledge.

Then my wife brings me back from my flash thoughts to reality. “Are you still there?”

“Yes, I am.”

“Oh okay. Well, as wonderful as this situation is, you realize it leads to a dead end, don’t you? They are going to shut down the program. Honey, you know more than I that no one wants to walk a path that would lead to “that Incident”.

“Oh, stop saying “that Incident” like you were talking about Voldemort”.

“Well, now that you are mentioning it. It is all about Serpentar. Ah ah ah!”.

We are both laughing nervously.

The Sync Dawn was the most dreadful event of the 21st century. It felt like a deep wound in the psyche of everyone.

“All right. My dear wife, I need to finish the review of update 5.21. Keep me posted, please. See you tonight.”.

“Bye Bye.”

I sit down glazing at the nothingness while thinking about what is best for both my grandchildren and humanity. Is humanity in a better spot now? Am I really improving our civilization?

“Gather your mind, Yannick. This is not the time for daydreaming. Get back to work to meet your deadline”, resonated Mustapha’s voice in my skull. My AI research assistant is right.

“Very well. GYTEK. Let’s… Uh… Check the emotion mirroring settings, calibrated for a classroom of 11 to 13 years old kids. Assertive factors 12.75. Judgment 87.5 and dynamic mentoring alpha-iota-iota. Imagination… Checked. Keep the default settings. Recursive feedback… Paused. Everything… Looks… Good. Ok, let’s start with…”.

I paused for a second, thoughtfully. I jumped from my chair energetically to say: “History lessons: The Sync Dawn. GYTEK 5.21, do you copy?”.

“Sure. Using the ascending evolution of the OpenAI’s Davinci model Mark XII published in November 2029, the startup Obsidian Intermind created a digital twin of human consciousness.

Soon after, the virtual consciousness infrastructure was upgraded to become connectable, so that off-brain cognition could be mutualized. As a result, humans could gain extra brain power and memory. The increase was dependent on the level of developed intelligence: the more critical thinking, emotional awareness, communication, and memory access you had, the more significant the boost was. The term “supra-intelligence” emerged. However, it was widely criticized as IQ studies were exposing a moderate increase from 0.7% to 14.5% IQ points.

However, this off-brain collective intelligence became exceptionally smart, to the point some said it was a wisdom system. Alternatively, specialized AI cognitive pools came to grow within the wise system, creating public and private cognitive islands. The most popular were the Disease Diagnostic Cognitive Pool (DDCP), and the Creative Cognitive Pool (CCP). Imagination was only limited by the human mind.

 Should I continue?”

“Please proceed, Professor.”


After nearly a decade of research, the collaboration between Neuralink and Obsidian Intermind gave birth to Evernet, the Internet of Cognition. The 14 July 2051 they launched the experimental version of this new kind of network. The principle was simple, 9500 humans would be connected to Evernet for 3 years. Each participant would be closely monitored and evaluated.

This experiment was widely criticized. The rush for the business model “Cognition as a Service” led to the creation of new social-economical movements: the Humanist, Cyber-moderate, and the Neo Mutualist”.

The Humanists fostered biological and spiritual integrity.

Doctrines of Cyber-moderate advocated for augmentation by technology, as long as it served, and I quote their leader, “A noble social purpose”. Alike in any group, Cyber-moderates had extremists. On the left end of the spectrum, their members accepted aesthetic techno-augmentation. On the other side, augmentation was only authorized for damages caused by dangerous jobs and Defence activities. It is not surprising that the Corps of Peacekeepers were mostly Cyber-moderates.

Neo Mutualism was a new religion. Their members believed humanity’s elevation and salvation would come from the mutualization of our consciousness. Transhumanists were schoolboys compared to them».

“GYTEK, just say they are a bunch of zealots.”. I mumbled.

“Yannick, my Critical Bias Thinking settings are set to 0 for kids between 11 and 13. According to the study “Biais Interpretation and Incorporation into Pre-teen Judgment System” by Dr. Amunde, Kallili and Pratt issued the 16 May 2039, the settings should be kept to 0. I reckon a variance of .05 would bring no harm. Do you want me to proceed?”.

“No, it’s fine GYTEK. I was talking to myself. What I meant is…”. I inhale calmly. “They demonstrated characteristics of zealots. Zealot-ish behaviors. Is my sentence acceptable?”

 “It is acceptable.”

“Common, GYTEK, you’re talking to me, your buddy and mentor! Say it!”

“They were a bunch of zealots! “. Said cheerfully the robot.

“Voila! Ok, stop joking around, otherwise grumpy Mustapha won’t be happy. Please continue”.

“I hear you”. Said Mustapha.

“It was on purpose… GYTEK. Please, go on.”

“Despite the widespread and frequent protests of Humanists, the Corps of Ethicists, Peacekeepers, Cognitive Researchers, Medicine, and the Corp of Society Architects approved the experiment. People would be connected to Evernet permanently during the experiment. And so, for the first time in history, humans would be connected to the first worldwide brain.

Everything went as planned. We observed a significant enhancement in each participant. Less stress, faster psychological recovery. Healing was even faster when after a trauma. People were dreaming more often. Furthermore, they all built habits that would improve their lives, as if positive practices spread unconsciously over the network.

The end of the experiment was planned for 16th August 2054. Each human taking part in the experiment would reach the personal milestone “Sync Done“.

Surprisingly, Evernet reached the 100% “Sync Done” milestone six months earlier than the planned end of the experiment. It was like the first landing on Mars, a day of worldwide celebration. The celebrities that took part in the experiment were invited to the most popular live-streaming shows, Twitter Live News and The Sandbox World.

Suddenly, people start noticing something very strange».

I raised my hand instinctively and said: “Pause. The last word is vague. Next time use precise words. The storytelling structure is engaging. Congratulations. But keep in mind this is History telling. Facts before Flares”

“Understood and integrated.”. The AI professor continued without further ado.

“People have experienced an unusual and peculiar situation. Participants in the experiment suddenly started to act and talk synchronously. It was as if the single mind spoke to the entire world by commanding many bodies like a puppet master. The colossal echo caused by the voices was staggering. Only the following abysmal silence of stupor superseded it.”.

I interrupted Professor GYTEK by asking: “From now answer as if a 12-year-old child asked the following question: How this ever happened?”.

“The exact reason is still being explained. However, researchers came to a general agreement before the following theory.

Evernet built not only a digital ai model but also a biological model of neural pathway architecture to optimize shared cognitive power. The human brain is designed to work as if it was alone inside a skull. Thinking about it, Evernet Orbital Data Centre is a gigantic metallic skull. Thus, over time, Evernet act as a single brain – a big brain so to speak – and each synchronized human brain just gave progressively more raw power, more ideas, and more knowledge. And it appears that once the pathway architecture was finally developed and mature in all the connected human brains it activated. What we are still trying to figure out is how and when the Evernet super-model decided to build the optimized pathway and how it encoded it in its new model.”.

“What was revolutionary about Evernet AI super-model?”

“Evernet’s was merely an inspiration of the human brain. The challenge was to find patterns in the structure governing the complex layers of inputs and outputs. The answer was in the order of magnitude and the capacity of robots living in the Orbital Data Centre to physically rewire the hardware like human synapses. In addition, the combination of Recursive Learning and Genetic Correction was revolutionary. These are complex terms for a simple idea. Can you picture Albert Einstein, with the curiosity of a 2-year-old child, getting smarter each second, with perfect photographic and sensorial memory, that can navigate back to the root of his knowledge, then re-assess its optimal state, to finally rebuild its current cognitive functions then replace them with better ones? That is Evernet.”

“Tone the complex stuff down.”, I retorted.


So, this is the reason why the governing bodies scrutinize AI technologies that have a direct impact on human cognition and education. Consequently, I professor GYTEK, and all my preceding versions, are commanded to not display expression of free will having a direct influence on human ideas, values, and ways of thinking that are not vetted and approved by the Corps of Education and the Corps of Society Evolution”.

“Not bad. Not bad at all. It is almost time. I am going to meet Quentin in… 2 minutes.

Before our session ends, Professor, given your predecessor’s unexpected behavior, you earned your personal assistant. It is like an artificial consciousness, so to speak. From now on, Serenity will also supervise your decisions and will act as a safeguard system. Her mission is to prevent you from acting in a way that will make the Corps of Education stop your program. Do you understand what is at stake?”.

“I do”. Said the professor emotionlessly.

Then the robot added “I will neither let you nor your wife down. I will prevent any reminiscence of her Sync Dawn experience.”

“Perfect. Finally, dear GYTEK, which open question of the day would you ask your students?”

“Considering it is possible to possess the same powers as machines while staying human. What is the most preferable outcome for the civilization: to increase the number of people artificially connected or to have more artificial intelligence agents interacting with people?”

In 2060

AR/VR Automation Blockchain In 2060 Information Technology Society Technology

Banking in 2060

It is 16h47, the 4th of June 2060.

I am sitting in my garden watching my granddaughter, Aleïs. She is playing with one of her advanced robotic toys, a Tyranausore Rex, and a ghost diplodocus. Yes, an invisible diplodocus. At least, this is what it looks like with my naked eyes. She is seeing more things despite she wears corrective glasses. In reality, she is playing with another digital dinosaur that only exists in the digital world. Glasses come with augmented reality by default, even for kids now. I remember when Apple launched them for the first time for the mainstream. I was just before the 5th digital revolution came, the age of the Phygital Internet

First, it was a gadget, it became rapidly a social advantage, to conclude as a social divide. It became indispensable when Apple partnered with major Glassmakers. Wearing glasses was no longer a sign of disability but a sign of “Augmentation”.

Suddenly Alëis sees virtual options popping atop The T-Rex. Some of them are locked and can only be obtained as “in-thing” payment. This kind of payment is sneaky but convenient, but sneaky! Of course, she wants to see the brand new flame animation coming out of her toy, and she wants to download cool dance moves like in Fortnite back in the day. She is into robotic animal engineering. She is much more skilled in information technologies than I was at her age. Like me, she is thrilled by trying and messing with new techs. I am so proud of her.

She taps on the menu to buy it. She is 14, and at this age, she cannot buy anything without the consent of one of her parents. One of the good features was family group management and sharing of financial assets and digital rights. Because I am an elder of her family, I receive her authorization to buy.

My Smartphone displays a notification. I smile because now they are holographic. And even when I am still amazed to see holograms popping out of the screen, smartphones are nowadays considered a relic from the past. Never mind, I am old anyway, I too am a relic. I should have died a long time ago. But they print organic lungs now, turning pneumonia into vintage flu. I put my finger on the notification and I approve with my face and my voice.

It reminded me of something. I say to Aleïs “There you go. You’re lucky, 15 years ago you couldn’t buy this option yourself”.

And she replied, “What do you mean, Papi Yannick?”.

“You see when I was younger, my mother had to go to the bank to open my account. I had to fill out some paper, present a printed copy of my national id card, and sign the paper with a pen. Later on, we could do it with our smartphones. Digital Onboarding was the coolest thing. We struggle to make it happen due to the strict regulations of the financial industry. Cyber fraud was high, and trust in the system was low. Eventually, the governments decided that laws had to be strictly enforced by code. You know, IT programming. Actually, this was the birth of the now famous expression “In Code We Trust”. Now everything is different. I mean normal for you but different for me. Ever since financial matters entered the Universal Declaration of Human Rights, it did change a lot for the good. Now each human has a bank account the moment they land on planet earth. It is a birthright. Of course, they have to pay if they want more options, like your T-rex! If I recall correctly, Mankind agreed on changing the law after the COVID-19 pandemic.”

“Now look at that. You can ask permission to pay with your glasses. Then I can approve it with my relic. You get the right to spend the money from your bank account. Finally, you get a T-rex spitting flames and dancing like Justin Bieber!”

“Justin Bieber? Papi, you are soooooooooo old”

“Yeah… I know”

“But I know things that you don’t”

“Ok tell me! Tell me pleeeeaaaassseeeeee!”

“Did you know that, in fact, you are not paying directly? It is your T-Rex that sends a payment to Amazon?”

“Seriously??? How come???”

“Ok. When I was still working at the bank, we figured out that autonomous cars were always connected to the internet because they needed specific cloud resources. As you know, the management of a fleet of cars is completely reliant upon the vehicle’s intelligence and collective intelligence. To operate correctly, each car needs to dynamically allocate computing power. I mean significant computing power. Now everything is quantum computing and photonic memory, it was ridiculous compared to now. The allocation is performed by buying volumes of TPU in the Financial Stock Exchanges. Funny story though, this is how Nvidia came to dominate by far the NASDAQ.

Besides, these cars were expensive to make. Thus, they needed to come with insurance from a third-party company. So what we decided at the bank is to create a bank account for Things. Nowadays, we generalized this concept to almost all objects. Fridges, washing machines, carrybots, you named it. So, in your case, the T-rex you received on your birthday has:

  • a bank account
  • a 10 years insurance bound to it
  • a return policy that mummy and daddy can use if they want, and the list of features unlocked

There is also a piece of information that says “this T-rex belongs to Aleïs Huchard”. Thus even if you lose it, someone can bring it to the nearest Post office and a delivery drone will bring it back to you. Isn’t that great?”

“How does the bank knows that it is mine?”

“Actually the bank does not know. The bank information system request the Worldwide Identity Service — a blockchain so to speak — to verify that this object is yours and it is safe to send a payment to Amazon. And since the monthly spending limit on your toy that your parent has set is not reached, you can buy your options. I mean the T-rex can pay for its hot upgrade, ah ah ah!”

We are both laughing loud together.

I continue with “ What do you want for your upcoming birthday? I was thinking about a trip or something”.

“Yes, I’d like to go to Senegal. You find the best Agrotech schools there.”

“You’re already thinking about university? Geez, you’re growing so fast.”

“Indeed. According to my personal finance advisor, we all have to save €20 per month on our “special event group account”. Annnnnd, this is me supposing I’ll receive €50 from you, Granny, Mummy, Daddy, and auntie Azea at my birthday!”.

“Yeah, sure you can count on that…. When did you become so good at finance?”

“I simply asked my personal financial advisor.”

“Can you show me?”

“Sure, here it is”. She looked at me with her glasses and made a swipe gesture in the air like I used to do on my NotSoSmartphone.

A hologram pops up. I was expecting a dude in suit-and-tie, like… a banker. How cliché. Instead, it was an oldish robot covered with rust. And says “How may I help you, Yannick”.

“Show me your list of features, please?”

“Sure, here it is”

A mind map of all features floats in the air. Then I say “I get it, this is an upgraded version of mine. I guess I should ask questions more often to my own personal advisor to train it with my needs. Or even better, I am going to ask your personal finance advisor to train mine. Although mine looks much more friendly. Why this robotic face, Aleïs? It looks like a half-baked Optimus Prime!”

“Don’t you like this skin, Papi? If you don’t like it, just change it. You can replace skins and voices. Check the marketplace.”

“Hmm… Open the marketplace please”

Now I am checking the marketplace. I see a lot of stuff produced by independent artists. Ever since ING came up with the “Platform Bank” idea, all Banks built their own “Financial Auchan”

See that, I can buy ad spaces on social media… Buy games on Playstation XR… Hmm… Buy tuition to the Elon Musk School of Technology… And, oh, even get me the avatar of Gary Vee for defining my attention strategy. Sweet.

Ah… Skins…

Oh, you can even buy Investment Strategies too !? “The Warren Buffet Strategy by Eleanor Neetz”… “The Silent Investor, by the Wall Street Journal”… “The Sustainable Index Strategy” is currently trending. And they even have a leaderboard now. Wow, did you know that the top performer of the month won €34023! Little one, your friends, and you should buy this strategy to fund your trip!”

And she replies “You prefer Social Network Investments to cool Skins, Papy? Your so oooooooooold!”

Artificial Intelligence Automation IT Architecture Technology

Intelligence of Information Systems – From Simple Mind to Overmind