Introduction

Good evening everybody, my name is David Della Pena and tonight I will be presenting Mr. Georgios Fredelos' Honey Badger Management Framework, which is an innovative framework that focuses on agility, adaptation and compliance to ESG, which means environment, social and governance, as well as overall adaptability.

Agenda Overview

So this is the agenda for tonight's presentation on my part.

So to speak briefly about myself, this is my third time attending MindStone, and this is my first time speaking here as well. So by background, I come from a professional and educational background of technology and international relations.

And the past few years, I've noticed how much AI has been evolving and shaping the way in which we work.

So in effect, there's now this discourse as to what extent is AI starting to take over most jobs, or to what extent are individuals beginning to integrate some form of artificial intelligence, whether it's generative or otherwise.

Core Concepts of the Honey Badger Framework

So here, it will be the core principles, the team roles, the communication and sprints, AI integration and ESG, environmental, social, and governance, performance and financial impact, concluding statements, and then a Q&A.

But let's continue.

Philosophy and Design

So the Honey Badger is all about a framework made for humans and by humans for the AI era, which is designed for resiliency, transparency, and agility, as well as leadership. It's built for humans, and it's operated both by humans and machines.

It's a framework by Mr. Fredelos that emphasizes that AI is, despite all its usefulness, is still just a tool, and that humans have a lot of power over it. So this is especially useful for business cases in order to maximize productivity and to maximize overall growth and to maximize profit.

So the following principles comprise of agility under leadership, a clear role delineation, intuitive hybrid organization, Now, the last three points are very vital.

Principles and Adherence

Knowledge transfer, which is very transparent. It's very robust. All members of a team within the Honey Badger management framework have access to this knowledge.

And the baseline for said knowledge transfer is transparent. It's a transparent baseline.

However, most importantly, Honey Badger must be adhered to 100% for this framework to fully work.

If this framework is not followed step by step or altogether, it can't be done partially. If it is not followed through 100%, then any prospective gains or productivity will be diminished, potentially, or any projected growth.

Pillars of the Honey Badger Framework

So looking here, here are the pillars that make up Honey Badger. There's ESG, environmental, social, and governance. There is leadership. There is transparency. There is priority, otherwise known as C-level priority.

This is a term used for business cases in corporate settings. There's the agility of the framework in that sprints are very short, they're very concise, and as much as possible, sprints are done fast as to mitigate any potential stressors for the team. And then there's AI knowledge.

Of course, for these pillars to work, Honey Badger must be adhered to 100% and fully.

So moving on.

Operational Practice

For operational practice, I'll go over this briefly.

Sprints happen over a period of seven days three times a month. If possible, sprints can be redone. But typically, it would be much more preferable to avoid that scenario, as a sprint being redone or canceled would imply that there is something wrong with the business case or that there's an underlying flaw that needs to be addressed.

Roles and Responsibilities

There are clear roles in the Honey Badger management framework, which include the manager, the guru, the AI assistant, the specialists, and the senior management.

As I mentioned earlier, knowledge transfer is very structured and mandatory, and it is done through a transparent baseline.

There is one AI assistant and there are two specialists who cover, they're usually typically a pair of specialist teams who cover different fields, depending on the business case.

There are also communication events that happen regularly. So the entire team within the Honey Badger management framework setting can discuss where their projects are at the moment.

And of course, there's also the ESG focus, which is sustainable, transparent, and is very energy efficient.

Team Composition Overview

So first will be a brief overview of the team composition. So the management, so the manager oversees everything. They are accountable for everything that goes on within the team.

Task delegation and resource control is handed over to them. Then we have the guru who can manage multiple small teams who act as the apex enforcers of the framework's compliance, oversight and expertise. And they will typically report back to the manager.

Then there's a specialist who, of course, they act as the drivers of innovation. They could specialize in software development, financial analysis, or perhaps carrying out general research.

And then the AI assistant provides knowledge support, baseline and error checking. The AI assistant is one of the key people who the manager will go to besides the guru.

Focus on the Manager Role

So first, I'll briefly discuss the manager. They are accountable for everything in terms of oversight. They have the authority over the other bodies, which includes the guru and the AI assistant. And this will be important later, but they use whatever same AI program that the AI assistant is using.

And this is key. They oversee the dashboard designs periodic communications for team updates, and they also evaluate resources.

That means how much electricity or how much energy the team might be using, whether through tasks or whether through tasks done by them or through an AI program. Energy will be significant for resource evaluation, especially when complying with ESG.

Importance of the Guru

So the guru is one of the important key players for the Honey Badger management framework. They are the top enforcers of ensuring that the Honey Badger framework is fully adhered to.

As I've mentioned earlier, the Honey Badger management framework must be 100% adhered to or any projected growth gains or productivity will fall short. They can also hold other members of the team through a legal framework, through legal liability to follow that framework.

They also provide compliance feedback. The gurus monitor team progress. And as such, they also report back to the manager.

And they can serve multiple teams. The gurus are very important because, as I've mentioned, the key enforcers to ensuring that this framework is followed through and that they provide important communication between different members of the teams, including management.

Well, it's not quite. This doesn't quite adhere to a specific AI program. This is scalable and adaptable to either Grok, ChatGPT, or anything else. This is more about a framework that focuses on a combination of individuals and AI.

I think the question was, To some extent, but it focuses more on the context of AI. That's what the guru is there for, because the guru is the one who has the most knowledge on this specific framework.

So it can be, perhaps, comparable to a Scrum Master, but it's more so comparable to this. Yes?

Role of the Specialist

OK, so next we have the specialist. The specialists are the drivers of innovation in this team.

Typically, there are two teams of specialists who compete amongst each other within the same team. But simultaneously, they also harmonize depending on the task.

So for example, there may be one team of specialists who focus on software development. Another team of specialists may also focus on financial analysis or carrying out general research.

They execute tasks. And in short, they also coordinate with the AI assistants and the gurus.

And the gurus will also periodically check on the progress updates of the specialists in the communications phase.

The AI Assistant's Function

the other important key player is the ai assistant they are the base of knowledge reference for the entire team as i've mentioned earlier the manager and the ai assistant are both using the same ai program typically in the business case and this is key because this is very vital for triangulation and they can help process data rapidly so to provide an example A software specialist from the specialist team reports back to the manager that there's a problem or that there's a new development regarding the status of their project or during a particular sprint. The manager has the same AI as the AI assistant, and they can go back and triangulate and confirm their findings with the AI assistant. So now the manager has no excuse for lack of oversight, as the framework ensures full transparency. and full visibility for the status of any given project.

Senior Management's Role

Next, we have the senior management. I'll just go over this briefly. They have higher levels of decision and strategy. They have access to the AI assistant's information or to the status of the AI assistant. And they frequently welcome feedback from the guru. So if the guru will report to them if there is a problem with a lack of adherence or if there's something going on among the team or among the specialists, they will share information with the guru and with the management.

Communication and Sprints

So I'll go over the communication now. The project initiation will last for four hours. This will be a full definition of the business case.

Following that will be a daily status update that will last for 20 minutes each day. Sprint preparations will take three hours. This is typically the assignment of tasks and overall planning. Afterwards will be a post-sprint discussion that goes on for two hours, which includes retrospective and feedback.

For extraordinary events, those may last for three hours, but that varies. And then afterwards will be presentation to stakeholders when applicable for a business case. and afterwards is a structured knowledge transfer, which happens 60 minutes per day. And these can happen like during the sprints, during these seven day sprints. So structured knowledge transfer, which is at the hands of the AI system, have to happen like one hour a day, and they are often reactive. So schedules, they often, they're tailored to the situation of the business case.

Sprint Cycle Explained

So now, discussing the sprint cycle, there are a maximum of three sprints per month, and each sprint lasts for seven days.

On day one, the dashboard, subproducts, MVPs will be set up, so communication lines and updates and means of communication will be fully set up on the first day.

As mentioned earlier, the sprints will be executed in a period of seven days with a one-day retrospective and adjustment period.

Dashboard Usage

So for the dashboards, this is the transparent baseline of knowledge. It is updated three times a day. There is visual tracking of tasks, progress, and flags.

The purpose of this dashboard as well is to help mitigate whatever stress team members may feel, which is part of the social aspect of ESG compliance. and it is transparent as it is accessible to the entire organization.

So there would be no reason for anybody to be behind this kind of framework.

So the dashboard is updated that many times and it's accessible.

ESG Compliance

So to move on to ESG compliance, as mentioned previously, E stands for environment, S stands for social, and G stands for governance.

For the energy consumption aspects, The framework will make it so that there will be a projected consumption of energy that will be one-third less than what would usually be consumed. Energy consumption for the Honey Badger framework aims to ensure that energy is consumed in a way that minimizes costs but bolsters productivity in the business case.

As for the social aspects, the short sprint cycles within the Honey Badger framework are made to help mitigate any potential stress, complication, or confusion amongst team members. This is where the social aspect comes from. And that the teams coordinate and act harmoniously under the notion of agility and under the notion of agility and transparency that Honey Badger promotes.

And finally, that is what governance also covers. Because the governance of Honey Badger is focused on its overall transparency, which in effect leads to effective communication between the manager, the guru, and the AI specialists and the AI assistants.

Comparison with Existing Frameworks

So next, I'm going to briefly compare how Honey Badger compares to different frameworks. So to go over them briefly, PMP, or Project Managed Professional, is a globally recognized framework in addition to projects in controlled environments. Both of these use low AI integration, or if ever they have low AI integration.

The same goes for the scaled agile framework, which doesn't use any explicit AI integration, but it has high scalability. PMP, PRINCE2, and SAFE2 and SAFE are all reputable frameworks used by different, and they're globally recognized by different management firms worldwide. However, Honey Badger compares to them because as high AI integration, high ESG compliance is fully scalable.

So you could say that Honey Badger is helping implement the best of what PMP, PRINCE2, and SAFe has to offer. Because SAFe, it's known for its high scalability. PRINCE2 has moderate scalability, but it has lower ESG compliance and lower AI integration versus that of Honey Badger. And Project Management Professional has low integration ESG compliance, but it is potentially scalable.

Hence, Honey Badger can help offer higher projections in terms of scalability and ESG compliance.

Project and Corporate Benefits

So next, here are the projected project benefits. I will discuss this briefly. But team productivity and deliverable quality, as well as completion time, are projected to be the highest stats for the Honey Badger management framework.

However, keep in mind that these are projected project benefits. There aren't any specific concrete numbers, but these are projected.

These projections are based off the internal research and the literature research carried out by Mr. Fidelos himself. So at the time being, these are the projected results for any prospective business case.

Projected Corporate Benefits

Next, we'll go into the projected corporate benefits. So innovation rate is high, and so is ESG scores.

The projected ESG scores are especially high because Mr. Fidelos designed Honey Badger in a way that maximizes environment, social, and governance, as discussed previously. So the projection for that is high as a whole.

Next is the empowered leadership of the Honey Badger framework. Honey Badger creates an agile culture that has a very clear hierarchy and does reinforce through the communication and the dashboards.

So the entire team is united in productivity, agility and transparency. And there's always continuous feedback.

Risk Mitigation

Next is risk mitigation. So human checks mitigate AI hallucinations, this can come in the form of the AI assistant and the guru.

The AI assistant, as I mentioned previously, has a very knowledgeable baseline and it can help inhibit human derailment. The structured reviews also ensure accuracy.

However, risk mitigation mostly comes due to the combined efforts of the guru, the specialists, and the AI assistants, as well as the manager having full oversight during any particular business case.

Scalability and Coordination

Finally, let's discuss scalability and coordination. So as I may have mentioned previously, the gurus can help manage multiple teams. Small teams with shared gurus is designed to scale beyond Dunbar's number.

So to provide some context, Dunbar's number refers to the fact that human beings can maintain a maximum of 150 stable relationships and connections. With the scalability granted by the gurus of the Honey Badger management framework teams, they can help scale beyond Dunbar's number.

So maximizing productivity, maximizing communication, and expanding on transparency as well, in addition to full oversight for the manager. And last and most of all, it is continuous in its evolution.

That means whether it is Grok, a newer version of ChatGPT, or any other AI program, Honey Badger is scalable and adaptive and is innovative. It is an immediate adapter of updated AI. So whatever may come after ChatGPT+, or the successor to Grok, or any of our new up and coming technologies, Honey Badger has a future proof management framework that can help different kinds of teams in all sorts of business cases adapt to different AI programs so that agility, productivity, and transparency are maintained.

Conclusion

So I thank you very much for listening to me tonight.

Here are the QR codes to my profile as well as my email and my LinkedIn. If you would like to contact Mr. Fardelos himself and learn more about the Honey Badger Management Framework, you can follow his links here or scan the QR code.

Q&A Session

So let's move on to questions of the Q&A. Yes? What kind of projects or initiatives is this being tried out on?

So far, it hasn't been tried out on anything. This is mostly a projected framework written by Mr. Fidelos. Hence why the results I showed previously were projected. And they're based off existing literature.

So they're based off two things, these projections. Internal research and literature research carried out by Mr. Fidelos himself. So for the time being, this is a framework. It's still in the early stages.

But yeah, that's about it. What would that apply to best? What kind of projects?

It could be with different types of business case projects. Including AI. Is it the focal point is how it includes or at least how it, is it the AI part? Because it seems quite similar to a certain aspect to other project management techniques. Is it the AI element that makes it different?

It's not so much the AI element as much as it's the emphasis on how we use the AI. Because like I mentioned, you can use different AI programs on this. Grok, ChatGPT, any in-house AI program or any open source.

But the robust aspect of the framework focuses on how human beings engage with the AI. So that means maintaining transparency, making sure the manager is fully up to date with everything, making sure that the framework is fully adhered to, ensuring that specialists adhere to the framework. So it's more so a mix of both as both an AI and a human element. but I'm sure they

For the Honey Badger management framework, AI is seen as a tool, a vital component, but it's not seen as the face, if that makes sense. Or specifically, it's the guru and the AI specialists. Together. Yes. Of course, they all work in tandem together.

So the manager oversees everything. and then the specialists they're the innovation drivers so they're the leading players of say a particular business case whether it's through market research or software development but the main focal point of the honey badger framework is also its short sprints its agility and and as mentioned there will always be an overseeing manager even if the system is agile So it focuses on energy efficiency, mitigating any stress or complications through an agile and efficient framework.

By agile, I mean the manner in which tasks and deliverables are carried out in a timely manner without much delay, while also maintaining transparency and airtight communication. So this would mean it applies also to non? want to say technical teams like more business teams yes because in in development i think it's by almost by default structured around sprints now and in agile uh yes it can also be used even for like non a for non-it contacts yeah so as long as like but however this framework would assume that there is some kind of ai being used what breaks that if you don't use ai in this

if AI isn't used, well, then the framework wouldn't be applicable because this framework is specifically aimed at business cases that are equipping some kind of AI. So because for the Honey Badger framework, there are two components, like the AI part and the communication and transparency part between the different team members. If there's no AI being used, then the Honey Badger framework probably wouldn't apply then. Why not? Well, because again, there's the gurus, there's the AI specialists, and then there's the gurus.

The gurus who can manage multiple teams and ensure that... So the guru is basically the AI specialist, specifically? Well, no, it's more so there's the AI assistant, and then there's the guru. The guru ensures that the framework is fully adhered to, but they also communicate with the AI assistants. Yeah, much like the scrum master.

Yeah, I get it. So yeah, you are right in certain aspects that there are similarities of our frameworks, but this framework specifically puts not AI as a focal point, but rather puts people who effectively master AI as a focal point. Because as I've demonstrated, specialists in different teams, some may use AI, some may not.

But the AI specialists, and there will always be one in every team, they will always use it. However, Both the manager and the AI specialist or assistant need to have the same AI in use. That way, you know, triangulation is effective. Otherwise, you know, say, for example, a software specialist approaches the manager and they'll say there's a problem with this and you need to do that. They will need to triangulate that with the AI assistant. So they know because they have the same program and everything.

They have all the data. And as mentioned previously, the dashboard and the line of communication, in addition to the fast sprints, makes it so that everybody is up to date as much as possible. So the short answer is it's not so much an AI-focused framework as much as it is a human effectively using AI-focused framework, if that makes sense. It makes sense, but it's or in a management environment, how they should interact with AI or integrate it?

It's more so how humans should both interact with AI and how they should interact with each other while using the AI. And I feel like that's maybe the thing that to me personally, maybe when it got to communication, it did, but didn't translate. It's not a feedback, it's really, I feel like that's the interesting part of that, man. It puts back the idea of humans' accountability or at least roles in it.

But I feel like that was the interesting part of the framework. That's kind of like... What's interesting to translate about it, I would say. Yeah, it's the human-driven aspects.

Because like I've mentioned, any AI program can be used for this. But it focuses more so on how teams and how different individuals in a business case take accountability, how they help relay information, how they adhere to the framework, and how they adhere to regulation, basically. Yeah. I was curious about it when you suggested that topic, but I realize it's many managers, many organizations looking to change the way they work. They might have to also rethink because of ESG also.

Yes. It's not just a dream. It's also an organization.

Yeah. And that's the reason why I chose to present this specific framework, because I found it both intriguing, and because even as we're speaking right now, the AI is still evolving very fast.

And we have people in meeting rooms thinking about, OK, who are we going to have to cut off from the team? What are we going to have to take away to maintain ESG? And I do believe that the Honey Badger framework is a good step into really looking into this discourse.

And it's like you mentioned, it's a good point that you mentioned, Reggie, is the nuance of it. So it's not just fully human. It's not human or AI-oriented as much as it's very coordination-oriented. It's a framework that focuses, that is made for humans.

and were both human, that's made by humans, and where both humans and machines work in tandem. But also, humans and machines working in tandem with other humans and machines. Because again, there's the guru. On a specific business case. Yes.

And of course, it is scalable depending on the business case and depending on the type of sector that a team is working within. Any other questions? All right.

Once more, once again, thank you very much for listening.