Collaborative Systems

The THREDD Development Paradigm - The Ascendency Principle

3/18/2026Robert Toshiyuki Morrell
THREDD Development Model

Continuous learning is non-negotiable in tech. The Ascendency Principle dedicates 18% of the workday to cross-training and knowledge growth, recovering hidden productivity losses.

Our first look into the THREDD AI principles as applied to software development begins with the Ascendency Principle in the knowledge acquisition domain. The key action guiding us in achieving this principle state is 'TRAIN'. Working in any modern technology focused organization can over time feel like a race just to stay in place on a down escalator. It's great that you have brought all of these various skills to your job, but that is just the start. As your tenure increases you will become more deeply engrained in your company's products and services, technology stack, and innovation, but how did you learn all of this? You certainly didn't sit in classes, you most likely picked up that information on your own, which means you spent time doing it. Time not calculated into your day. How often did you sit with a fellow co-worker and learn from their experience? How often do you find yourself investigating code written by others only to misunderstand why it was written in a particular way and afterwards still sit with them for clarification? Add in the time you go to your teams resident specialist in a particular concept, feature, dev process or just to get their approval. The point is, this time is virtually uncalculatable because it typically doesn't include the other individuals time and we often don't realize when we are doing it. In cross-functional teams bottlenecks can quickly arise, but so can periods of idling.

Formalizing this often misunderstood dynamic into periods of fruitful training is a first step in recovering lost productivity. You can expect an engineer to code for 4 hours straight at most before diminishing returns begin to set in. Instead of viewing this as a negative, take it as an opportunity for your team members to reset by engaging in other activity.

As in any machine learning algorithm, its training defines its effectiveness and its ability to continuously incorporate new information becomes the foundation of the teams ability to deliver a quality product. There is no other way to keep your team relevant.

Most managers look at productivity as an equation where they are starting from point A and trying to get to point B, when the obvious solution is just to do B and ignore the assumptions of A in the first place. As I mentioned earlier we know there is incalculable time wasted throughout the day. Lets take a step towards being able to quantify it and work from there.

The Ascendency Principle states that we must continuously seek to achieve a better state of knowledge required to achieve our goals. A value wherein we always seek to improve ourselves. The rule of thumb here is the 18% Rule. This is the amount of time in the day that must be devoted to the improvement of knowledge. For cross-functional teams this is especially important as members typically move from a specialist to a generalist role. Yes, you read that correctly. 18% of your day equates to 1 and a half hours out of an 8 hour shift devoted to cross-training and knowledge acquisition. If you don't think your team has this time to spare then I will boldly state that you just aren't aware of it and this time is already being accounted for in their workload estimations. But, don't take my word for it. If you can, take a closer look at your team. Try and identify any moments where unanswered questions cause even slight delays.

The Ascendency Principle is limited by the time afforded to it and benefits the Connectivity Principle.

In other words the ability to 'TRAIN' is limited by the time afforded to it and facilitates the ability to 'HARMONIZE'.

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