Iteration and learning from the mistakes along the way @bunniestudios
Andrew ‘bunnie’ Huang is working on IRIS (Infra-Red, in-situ), a multidisciplinary project to give people a tangible reason to trust their hardware.
In applying himself, bunnie provides some tips on how iterate to come up with solutions.
This short “sidebar” post will wax philosophical and discuss my general methods for learning and exploration;
The Rule of Three
When I have no way to derive how many iterations it will take to get something right, I use the “rule of three”: generally, you can get somewhere interesting with three iterations of a methodical process.
Meta-knowledge: Knowing what You Know
When it comes to planning a big project like IRIS, a realistic self-assessment improves my ability to estimate time and resource requirements; the rule of three only works if you’re realistic about what you can achieve with every iteration.
Thus, I have developed a series of criteria to keep myself grounded, and periodically I take some time to reflect and correct my behavior if it is out of line.
Working within my Limitations
Significantly, progress past the “know it well” stage often requires me to take a several month break from doing anything with the topic or tool. During this time, all my short-term memory of the subject is lost, so I have to re-acquire the knowledge when I return to the topic. Re-learning from experience is an important step because I get a fresh look on the topic. Because I’m already somewhat familiar with things, I have the surplus cognitive capacity to put everything into context, while having the awareness to identify and break bad habits.
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