VCoLing: Learning to Learn [Lectica]

Photo by Ben White on Unsplash

Lectica’s overall approach to learning in a complex world deserves its own dedicated post, which I hope to write one day. Today, I want to focus on a smaller piece of their overall thesis — their framework for “how we learn?” because it stands on its own and is more broadly applicable, regardless of the learning goal that you’re applying it towards. 

I am mostly synthesizing content from two sources: 

Virtuous cycles of learning (VCoL) and the +7 skills

Learning in the moment: How to use micro-VCoLs to learn optimally on the fly

Lectica’s framework, called the “Virtuous Cycle of Learning” or VCoL for short consists of 4 key steps: setting a learning goal → gathering information → applying what you’ve learned → reflecting on the outcome. Sparing you my rant on the overall underappreciated importance of reflection in many other approaches to learning, this macro cycle is very similar to other progressive frameworks describing a learning process, with minor variations in the labeling of the different steps. 

When things start to get interesting, and have certainly expanded my knowledge of learning, is in the way Lectica decomposed this cycle further and in the way it is applied to real-world situations. 

The +7 skills

Lectica identified 7 key skills that support the practice of learning. Each, in turn, can be strengthened through a set of specific practices.

Source: Lectica
  1. Awareness of self, others, and the environment: observing and documenting thoughts, feelings, or behavior; self-evaluation; practicing non-judgmental openness to experience; meditation; mindfulness in everyday life; somatic practices, like yoga; coherence practices, like HeartMath
  2. Skills for making connections between ideas, information, emotions, perspectives, and evidence: brainstorming; Minto Pyramid problem solving; polarity thinking (or both / and thinking); mind mapping; causal loop diagramming (or other systems mapping approaches); building relational databases
  3. Skills for seeking and evaluating information, evidence, and perspectives: active listening; deep listening (Kramer); seeking clarification; “library” research; critical thinking; action inquiry (particularly second-person action inquiry); the scientific method
  4. Skills for applying what we know in real-world contexts: action learning; project-based learning; developing action plans or development plans; rehearsing — reducing risk by trying out new knowledge in hypothetical situations; writing or critical discourse — using new knowledge to improve an argument or message
  5. Reflectivity — a cultivated habit of reflecting on outcomes, information, emotions, or events: making sure that learning goals are “just right”; embedding learning in real life, as a part of everyday activities; not punishing learners for making mistakes — helping them see mistakes as a source of useful information; ensuring that every learning cycle, no matter how small, ends with goal setting
  6. Skills for seeking and making use of feedback: openness to feedback; awareness of your own defensiveness; feedback-seeking skills (like helping others feel comfortable providing you with feedback); skills for evaluating and incorporating feedback; second-person action inquiry; participation in focus groups; customer or employee surveys
  7. Awareness of cognitive and behavioral biases and skills for avoiding them: cultivating humility — recognizing the ubiquity of human fallibility; building critical thinking skills; regularly seeking feedback; tackling common cognitive biases, one at a time (e.g., conservation bias, bandwagon effect, stereotyping, or attribution bias)

The 7 skills are also very helpful in better triangulating where the learning cycle is weakest (or breaks down altogether) and then taking focused action to strengthen that particular skill. 


Often times we want to work on a macro skill that’s a bit too lofty, abstract or risky to pursue as a whole. Let’s say we want to improve our “collaborative capacity”, for example. It seems like a worthy goal, but where do we begin? 

We begin by decomposing the macro skill into something more tangible. For example: part of a strong collaborative capacity is having strong facilitation skills. Facilitation skills, in turn, include but are not limited to having strong active listening skills. Active listening skills can be decomposed to: identifying opportunities for listening, giving others opportunities to speak, etc. 

Now we have something in hand that we can more easily run a VCoL around and practice “in the real world” with one additional useful distinction. If we zoom back out to the crude VCoL loop: set, seek, apply, reflect — two stages in the loop, “reflect” and “seek”, are more internal, or done in consultation with a trusted coach or mentor. The other two, “seek” and “apply” is where we engage with the outside environment differently, with the learning goal in mind. And those too can be broken down into micro-VCoLs: an “awareness VCoL”, in which we either increase awareness of opportunities to practice a skill or identify individuals who are proficient in a given skill; and a “practice VCoL”, in which we build virtuosity in the particular learning goal. Examples of the two are shown below.

The next time you set a learning goal for yourself, consider using VCoL as your framework for learning. 

VCoLing: Learning to Learn [Lectica]

How we make decentralized decisions [Küblböck]

Another fantastic piece by Manuel Küblböck whose excellent work I’ve already showcased here. This time, the focus is on how decisions get made at Gini. While the majority of the post covers the mechanics of the various decision-making formats, that was the least interesting part to me, since I’ve already covered most of them, for the most part, in previous posts. What was most interesting, was how the system is structured and the following attributes in particular: 


Source: Manuel Küblböck

I’m not 100% sure where the 7-levels of delegations model originated from, but I first came across it a few years back on the Mgmt3.0 website so I will give them the credit for now. 

This fuller spectrum is being used to anchor the decision-making formats that are actually being used: 

Source: Manuel Küblböck

Again, while the mechanics of “safe-to-fail/mandate”, “group consent” and the “advice process” are outlined in the post, those are fairly standard formats of decision-making. 


This was new and exciting for me. Thinking about the process of choosing the right decision-making format more like a simple, lightweight decision-tree/escalation path with increasing levels of severity: 

Is this safe-to-fail? → Do I have an explicit mandate as part of one of my roles to make this decision? → Can the group reach consent (not consensus) about this? → Advice process. 

Specifically, thinking about the “advice process”, which is the most lengthy process of the three, as an escalation lever when the group fails to reach consent is very clever and avoids over-using this heavy process. Another interesting aspect here is seeing the escalation arc moving from the individual, to the group and back to the individual, which seems a bit counter-intuitive at first but makes a tonne of sense once you think about it.


This is another cool innovation. Defining a desired, healthy, usage distribution across the different decision-making formats. Heavily favoring and relying upon autonomous/distributed decision-making, using consent-based decision-making only when necessary, and thinking about the advice process as the exception rather than the rule. While the 90%/9%/1% should be thought of more as illustrative, order-of-magnitude guidelines rather than exact percentages, they create a healthy benchmark that can be used to trigger and support troubleshooting when the actual distribution looks significantly different. 


Not a new point but one worth emphasizing, since many, myself included, often make this mistake. When we compare the speed of various decision-making formats, we tend to compare the time it takes to reach a decision. But this is the wrong benchmark since decisions are just a means for informing a desired behavior change. So if we want to make a fair comparison on speed we need to look at “time to make a decision” + “time to change behavior” which is beautifully illustrated in this parting image: 

Source: Manuel Küblböck

Post Script: h/t Bruce Gant for pointing me to the true origin of the delegation ladder, a 1958(!) HBR piece by Robert Tannenbaum andWarren H. Schmidt called How to Choose a Leadership Pattern:

How we make decentralized decisions [Küblböck]