#07 Brace for Change: Have an ACE up Your Sleeve (2nd Ed)

Dear Readers,

Got 10 minutes? Grab a coffee and enjoy this read. Or give this page a right-click and turn it into a podcast using your browser's "read out loud" function. We'll start with a quick recap since we're at the midpoint of both my six-month journey and this 12-part newsletter series.

Today, let's explore a fundamental truth of life and business: change is inevitable. Everything around us, from personal relationships to professional environments, is subject to constant change and disorder.

This chaos, also referred to as entropy, means that without active efforts to maintain order, things naturally tend to fall apart. In this post, I’ll discuss designing for change, for all of you who want to make a dent in the world.

Let’s dive in!

Salvi

PS: I've called it 2nd edition, as I lost my entire first edition to a LinkedIn system hick-up. Damn you, technology! ;-)

1 A quick recap

If you haven’t read my previous posts, here's a quick recap, the others can jump ahead to the next section.

1.1 Recap on the business/economics side

As traditional employment becomes increasingly difficult to sustain, and relying solely on income from capital investments isn't viable unless one is already rich, the need for discussions about universal basic income and universal basic services has become urgent. These economic solutions are crucial for helping people manage financially from month to month, which is a challenge primarily for governments and econometrists to tackle.

However, as a technologist—and indeed as a worried human being—my primary concern extends beyond just making ends meet money-wise; it's about ensuring we thrive purpose-wise. For decades, our sense of purpose has been closely tied to 'productivity'. But now, I believe we need to shift our focus towards 'creativity' and 'ingenuity'. This shift should be part of a broader transition from a shareholder to a stakeholder economy, emphasizing well-being over mere welfare.

I'm worried that many people might become depressed, which would dampen their creativity just when we need it most—to tap into what I like to call our 'heroic potential.' This is about bringing to life the big ideas that have always seemed just out of reach. Right now, big businesses hold the keys to groundbreaking capabilities of the Fourth Industrial Revolution (4IR), but it's crucial that everyone gets access to these capabilities.

This is exactly why we need to make entrepreneurship more straightforward. After all, at its core, entrepreneurship simply means "to undertake something".

1.2 Recap on the tech side

The capabilities offered by Fourth Industrial Revolution (4IR) simplify the process of starting something new, practically offering everyone with the drive and talent a ready-to-go opportunity to become an entrepreneur.

In my last two newsletters, I covered the two most relevant capabilities in the AI subspace:

• The capability to use your own data, information, and knowledge, or to cleverly combine publicly available sources:

• The capability to set up a digital workforce, through multi-agent systems:

Note how I am using the word "capability" and not tool. Right now, we have RAG tools and agent tools, but eventually, large language models like GPTx, Claude X, and Gemini will offer these same capabilities. It's... inevitable.

Alright school, recap's done! Let’s dive into today’s topic: how change can be a real trickster. But will the organizations of the future face the same problems? Not on my watch!

2 Organizations today

2.1 The Challenge of Change in Organizations

In the corporate world, anticipating and managing change is a critical task for upper management. They continuously tweak organizational structures, shuffle teams, and sometimes create entirely new roles to adapt to evolving conditions, such as the creation of end-to-end process lead roles to whom other people have a dotted line reporting relationship.

The eternal conundrum, putting people with the same skills together, or those supporting the same process, which is great for flow, but not for skill development. I can imagine that you just cringed while reading the words “dotted line”, you will not have been the only one.

Another tactic is the common division between operations ("ops") and projects within companies. These divisions often compete for the limited time of process experts, who ironically enough often are on the IT side of the company. Because guess who needs to know exactly how the process works end-to-end: those who have to design the software that runs your company.

Observe this constant balancing act between robustness and relevance: All adjustments to stay relevant in the market should also aim to remain aligned with the company's vision, mission, and purpose, while also – in some magical way - not causing disarray, entropy.

This continuous process of implementing new things into the BAU, the Business As Usual, my university professors described as the "innovation-continuity bicycle”, a concept I've previously mentioned in a personal article on LinkedIn, to which I will link at the end of this post.

However, we are entering a new industrial revolution with shifts in the environment so seismic, so paradigmatic, that the business model of the company might be rendered obsolete, just because of what 4IR/AI technology can do.

Data-centric organizations, like those in education, consulting, and software development, should gather their brightest minds with AI experts to innovate before competitors do. Or you can ignore the clouds and let Microsoft Copilot make you even more “productive”, a faster horse in the era of cars type scenario.

I’ll issue the same warning to bankers and notaries once blockchain gets out of its dip in the hype cycle. I’ll issue the same warning soon for anyone who thinks robots can’t handle tasks that require high dexterity, a soft touch. But, I went on a ranting tangent here. We were talking about change, and the entropy it creates.

2.2 Entropy in Software Systems

The battle against entropy extends to the software systems that support these businesses. According to Conway's Law, the communication structures within an organization will naturally be mirrored in its software architecture. Therefore, managing software involves anticipating potential changes and implementing them swiftly and flawlessly to avoid disrupting stability.

This balancing act between constant innovation and maintaining operational stability was termed the “functional-constructive gap" by my professors, another concept I've previously mentioned in a personal article on LinkedIn, to which I will link at the end of this post.

2.3 Thinking in Systems and Resistance to Change

“We will solve the problem when it presents itself.”- Jean-Luc Dehaene, former PM of Belgium

Furthermore, it's good to keep in mind that an organization is a system with highly complex actors (also known as "us"), which means there are systemic gaps like, just to name a few:

1. not everyone having access to the same information;
2. delays between cause and effect;
3. and well-intended solutions with unintended up to paradoxical side-effects.

These gaps often make it challenging to convince others of the urgency of problems or the effectiveness of solutions. That is why we'll have to work on climate change once Antwerp turns into a coastal region.

Moreover, any system that reaches a state of equilibrium, a local optimum, will develop mechanisms to actively resist change. In business, these are often rooted in the personal interests, biases and resulting office politics of its members.

While we generally appreciate change, we resist being changed ourselves, especially if it doesn’t benefit us directly. Don’t blame yourself for distrusting change: the free market is a rough place, well-paid functions are limited, and human labor is the biggest possible cost center. Most of us work in a shareholder-driven company, you do the math.

3 4IR/AI-powered Entrepreneurship

3.1 The Role of Entrepreneurship in Addressing Our Challenges

Not everyone must become an entrepreneur, but many of the world’s systems remain suboptimal and ripe for improvement. There lies a unique opportunity to harness the collective intelligence of millions who are exiting the traditional "productivity rat race".

Let’s turn victims into heroes. Let’s tap into our own potential to address significant issues, whether it’s combating climate change or solving loneliness in your local community.

While an entrepreneurial idea doesn't need to be extraordinarily grand, it should be the best possible idea one can come up with, and ideally, one should think of several great ideas. The critical next step is finding a mechanism to turn that idea into reality.

3.2 Introducing Autonomous Enterprise Design

This is where Autonomous Enterprise Design comes into play. Picture this as both an accelerator program and a comprehensive operating system for nurturing your ideas. This platform connects like-minded individuals, leveraging advanced AI to streamline the process of bringing an idea to life.

Autonomous Enterprise Design is structured in three main stages, each supported by sophisticated AI systems to navigate common pitfalls and maintain focus on the entrepreneurial vision:

1. Idea Validation and Development: The first stage involves refining your idea’s core mission, vision, and value proposition. This includes practical steps like engaging with potential customers and crafting a business model. AI, equipped with the collective expertise equivalent to a thousand strategy consultants, assists in this process. If an idea proves non-viable, the AI provides data-driven feedback, making the letdown less personal and more constructive.
2. Uniting and Improving the Masterminds: The second stage involves finding likeminded people with either overlapping or complementary skill sets, that are as passionate about the same idea as you are and have shown to have the same vision on how to make it a reality in the first stage. But also expect a ruthless self-assessment to be part of this stage. Knowing your blind spots allows you to address them. It allows the AI to assemble a team that will “click”.
3. Enterprise Operation: The third stage focuses on starting, scaling and protecting the enterprise from – you guessed it - entropy. The founders will observe a hybrid organization taking shape, consisting of AI agents, robots, and human employees. The system guides you through scaling your business and enforces governance best practices, useful especially if you're new to running an enterprise. You should stay focused on the business, not get dragged into the business. That is what entrepreneurs do.

So what does Autonomous Enterprise Design produce in the end? A new kind of company.

3.3 The Blueprint for a New Company

In previous posts, I introduced the concept of infusing proprietary knowledge into AI systems and discussed agents and multi-agent systems. The next step up is small architectures to let them achieve goals with that knowledge, and dive into the current implementation frameworks.

So I could expand into patterns such as the reasoning-action pattern, or technical tools such as AutoGen, platforms such as CrewAI… which regulate agents or multi-agent collaboration. But you are not a technical audience, and my post would be obsolete in no time.

I want to talk to you about a capability architecture that incorporates all aspects of what anything that is autonomous and cognitive should care about. So, a future robot falls under that definition, you currently fall under that definition, but I want you to think of it as a full company blueprint, an architecture that could govern your future AI-driven company.

Imagine a virtual multi-floor building owned by your new company where each level is populated by AI agents specializing in a distinct aspect of what the floor represents.

3.4 The ACE Framework

Developed by David Shapiro et al., the ACE framework is designed as a highly structured yet dynamic system that facilitates a low-entropy operational environment.

Operating a real company with a comparable level of specialization and coordination, or managing such complexity as an individual or small team, is impractical. Entropy would go through the roof!

Here's how an ACE-based architecture revolutionizes the corporate structure:

1. Comprehensive Layers: The framework is divided into six layers, each addressing a different facet of company operations. This structured approach ensures that all necessary aspects of business management are considered, from the ground up. And for the sake of completeness: there’s a basement where all the connections with the outside world are handled, and you can have the imaginary penthouse on the roof.
2. Ethical Foundation: Morality, ethics, and mission are prioritized at the topmost layer, ensuring that no viable strategy can proceed if it conflicts with these foundational principles. This design embeds predictability and trust within the architecture.
3. Constant Environmental Monitoring: The base layer, vividly represented in grass green, is tasked with continuously monitoring external changes. This allows the company to stay responsive to any relevant shifts in the external environment.
4. Controlled Decision Flow: Decisions in ACE are structured to flow downwards, integrating insights from each successive layer. This ensures that decisions are well-informed and comprehensive.
5. Feedback Loops: Feedback, both from successes and failures, travels upwards through the layers, facilitating operational, tactical, and strategic improvements.
6. Dynamic AI Agents: AI agents in the ACE model are designed without self-interest. They can be dynamically created, reassigned, or deprecated as needed, ensuring optimal resource allocation at all times.
7. Transparency: The system maintains full transparency, which is crucial for trust and efficiency in such a highly autonomous setup.

4 Conclusion

In my upcoming posts, I will explore each layer of the Autonomous Cognitive Entity (ACE) framework in detail. For now, imagine how a company that combines rigorous structure with adaptable flexibility could revolutionize today’s business landscape, establishing new benchmarks for operational efficiency and ethical practices.

Reflecting on the concerns I voiced earlier in this article about change, entropy, and the problematic issues of information imbalances and delays, it’s compelling to see how these challenges are addressed by the ACE framework. With its forward-looking and inward-looking mechanisms, such systemic flaws are not just reduced but potentially eliminated. This represents a significant leap towards creating business environments that are not only more efficient but also inherently stable and fair.

Wouldn’t it be exciting to have an ACE system turn-key your most innovative idea into a fully operational, auto-adaptive business? I certainly find the prospect thrilling. And to existing, inert businesses, I wish you good luck competing with a company that was built from the ground up to be an ACE.

References

The personal article in which I mentioned the innovation-continuity bicycle:

The personal article in which I mentioned the functional-constructive gap:

The repository with the academic paper on the ACE framework and related papers (and implementation examples):

https://github.com/daveshap/ACE_Framework/tree/main/publications

And as always, the Manifesto: