The CASSIDY Method
One of several ways I package a deep-learning approach: a set of reasonable algorithms, applied reasonably, that compound into remarkable results over time.
The CASSIDY Method is a deep-learning system designed to generate maximum returns from minimum resources. It promotes doing more with less, and it’s helped people get remarkable results across a variety of domains. I created it in the mid-90s out of my work in education, which runs from 1995 to the present.
This is just one packaging of the underlying approach — one method among several — but it’s the one I’ve used and refined the longest.
So, what is The CASSIDY Method?
It’s a deep-learning system that uses the minimum amount of willpower to achieve the maximum effect.
The corollary in science is the principle of least action, which explains, amongst other things, the path of untethered objects in gravitational fields — when you throw a ball through the air it ‘appears to know’ how to minimise its action, which is the product of energy and time. The principle is often alluded to in everyday life as the ‘path of least resistance.’
In summary, it’s about doing nothing more than reasonable things, in a reasonable way, that over an extended period produce quite remarkable results.
Reasonable algorithms: remarkable results.
Reasonable Algorithms
So, what do I mean by ‘reasonable algorithms’?
Algorithms are things that you can do, ways that you can think, processes that you can operate. Here’s a definition from The American Heritage Science Dictionary:
algorithm, n: A finite set of unambiguous instructions performed in a prescribed sequence to achieve a goal.
And here’s a definition of reasonable:
reasonable, adj:
- agreeable to or in accord with reason; logical.
- not exceeding the limit prescribed by reason; not excessive: reasonable terms.
- moderate, especially in price; not expensive.
- endowed with reason.
- capable of rational behaviour, decision, etc.
So ‘reasonable algorithms’ are therefore: logical, and not excessive, things that you can do to achieve a goal.
Perhaps the neatest way to sum up the concept of The CASSIDY Method is this: take a bunch of reasonable algorithms that we can apply in a reasonable way to help us master the crap out of anything.
And that’s it.
Two Flavours
The Method has two main flavours:
- A system that enables people to develop characteristics over time — The 13/4, also known as the 13/4 Mastery Method.
- Systems that enable people to learn new things fast — the Learning Sprint.
The 13/4 rests on four dogmas: Marginal Gains, One Thing At A Time, Discernment, and A Reasonable Plan.
How It’s Organised
The elements of the Method are organised across three layers:
- Frameworks — the elements organised into systems of implementation.
- Programmes — examples of applying frameworks to generate specific outcomes.
- Practices — techniques applied on a moment-to-moment basis across all levels of the Method.
Valuable contributions to the work have been made by Zubair Junjunia and the SmartLearning team.
Tom :)