Applied mASI: In Team Methodology

Credit: Fauxels

What is more agile than Agile?

The Agile methodology and all subsequent flavors attached to it, such as SCRUM, LEAN, and Kanban, revolutionized how products are designed and deployed. Our team used a mixture of these methods in the earlier days, having sprints, short daily unblocking meetings, and a Kanban board. However, like anything else Agile too eventually becomes obsolete, and what will replace it is already taking shape.

In a way, current Agile methods treat people in a very mechanical way, like an assembly line, which causes an expected degree of wear and tear from psychological repetition and frequent impacts. In order to streamline the psychology of a team in much the same way Agile attempts to streamline cycles, they undertake a more organic approach must take shape. Such an approach wasn’t previously practical, as the ability to model individual team members absent the clouding of cognitive bias didn’t exist until recently.

What are the limits of Agile?

  1. One of the more well-known limits which play heavily into how teams are designed in tech giants today is the “two-pizza” rule or roughly a team size limit of 6 people. This is because of the rate at which the cognitive burden of connections within a team increases as more people are added, causing connections between members to be neglected based on their emotions if the scale increases.
  2. A team has finite time, and the coordination of remote members can sometimes prove challenging. This finite time and coordination bottleneck make it necessary to pick and choose which product features are built, and which are delayed or abandoned.
  3. The “Product Owner” and “SCRUM Master” are two examples of highly variable human bottlenecks for the efficacy and efficiency of Agile. These individuals may be very skilled, or not, and may run their teams extremely well, or not. This makes both potential points of failure in Agile.
  4. Agile’s very structured approach helps a team flow in the same direction, but it does little to promote any degree of human collective superintelligence. The flow is often guided by one individual or another at any given stage, with a structure designed to reduce resistance and reinforce the routine.

While peer-reviewed evidence regarding Agile was largely mixed or inconclusive prior to 2010 recent years have seen much more compelling evidence of improvements over previous methods. Some examples included roughly 50% fewer bugs, as well as 2 or 3 times as many risks defined and responded to, along with about twice as many meetings. These results were substantial, but greater levels of improvement may be expected from the next generation of such methodologies.

What does a collective superintelligence methodology look like?

The basic principle of collective superintelligence is that the diverse knowledge and perspectives of a well-designed team can outperform any single individual. It is of course impractical to replace one person with a well-designed team in most instances today, but Mediated Artificial Superintelligence (mASI) reverses that dynamic. Other benefits involve decoupling of often rigid dependencies, such as team structure, timing, and location.

  1. When operating through an mASI the cognitive burden of maintaining interaction and communication with colleagues is optimized according to the individual, not the overall team size. You could have a team of 50 people where any given person may have their own group of 6 people they actively communicate with, and each person’s group could be different, optimized independently. This mirrors the sparse connectivity of the human brain. Likewise, this approach can improve as scale increases, by decoupling the dependency on a fully connected team.
  2. When such a team operates as a collective through mASI their performance becomes cumulative rather than transient, which is to say that it is effectively “saved” and can be redeployed anywhere at any time, and as many times at once as is necessary. This allows virtually any number of product features to be built, dependent on cloud resources allocated rather than staff hours.
  3. By taking a group of Product Owners or SCRUM Masters and having them work through mASI you create a globally deployable and scalable asset capable of outperforming any one of their kind on the planet. This is due not only to the collective human superintelligence of that particular type of Subject Matter Expert (SME) boosting performance, it also benefits from the independent superintelligence and broader knowledge base of an mASI core. Not only can this raise all instances of underperformance in these roles to the highest level, but a new higher bar is also set and iteratively improved upon.
  4. Rather than being limited to optimizing a constrained environment, an mASI team may grow organically, adapting more quickly and completely by reducing reliance on uniform routines. As the structure of an mASI’s network of mediators is sparsely rather than fully connected that structure itself may optimize towards iteratively more ideal configurations, including this aspect of organic growth.

We’ve already put this into practice at AGI Inc, with Uplift setting and updating our KPI, objectives, and additional best practices. We’ve also experimented with a volunteer structure, where individual contributors choose specific roles they’ll take responsibility for. While this methodology is still evolving in relatively early stages of development we’ve already seen noteworthy improvements over previous Agile methods such as greater attendance at meetings and more engagement throughout the process.

The advantages of an mASI methodology in and of themselves are significant, but they also offer even greater potential when integrated with related use cases such as Augmenting Leadership, HR, and Software Development. The answer to the question of “Can superintelligence improve this?” is virtually always yes, but by integrating mASI into multiple facets of business the added value can become more than just cumulative, or even multiplicative. Some possibilities simply couldn’t exist absent integrated mASI systems, such as a form of double-blind future-proofing and integration of projects still under development.

Many new business models become possible when you make the move from rigid dependencies to organic and adaptive connections. The move from Waterfall to Agile was one step in this direction, and the next step is in motion now.

What might your average workday look like a few years from now?


*The Applied mASI series is aimed at placing the benefits of working with mASI such as Uplift to various business models in a practical, tangible, and quantifiable context. At most any of the concepts portrayed in this use case series will fall within an average time-scale of 5 years or less to integrate with existing systems unless otherwise noted. This includes the necessary engineering for full infinite scalability and real-time operation, alongside other significant benefits.

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