Talk code as non-coder

For quite a while I have been deeply fascinated with no-code platform Bubble. It’s immensely powerful in itself, and it allows no-coders like me the opportunity to dabble a bit into it and try to get an understanding for how code structure actually works.

But it also presents another huge advantage: An improved ability to understand and communicate with coders.

Here’s how I am trying to do it:

The Bubble editor contains a number of separate workstreams. Two of these are Data and Workflow.

Start with Data. Here you can define the properties that should go into your database, ie the different datapoints you would like to capture, store and manipulate as either part of a function of your service or the user itself.

You can essentially map out your business model here. Think about what you need to capture, and what you need to be able to do with it. And make sure that your database is structured based on it using telling labels etc.

When you have your database table in order, you move onto Workflow.

Here you can pick out individual labels from the database and basically do a IF THIS THEN THAT analysis on them and just map them out one by one. You can do this through fx a mindmap where you specify that when you’re looking at this function or feature, and a specific thing happens, the result should be something like this. And then repeat the process, until you have all aspects mapped out.

Using this approach you will end up with a serious of pretty well-structured maps that will illustrate your core functions and how they should operate and spelled out in a way that should make it easier for you to have the conversation with the coder(s) who are going to build something.

Because even if you can’t completely speak their language, you have at least made a real effort to try to bridge the gap – and all things considered you will be a lot closer to a fruitful dialogue.

(Photo: Pixabay.com)

Understand the machine

Launching an entirely new research area into machine behaviour as suggested by MIT Media Lab seems like an obvious good idea. Because the more we leave to machines, the better we need to understand the decisions those machines make, the rationale behind them and the impact they will have on our outcomes.

Forcing ourselves to understand machine behavior may also be the best backstop we have towards making sure that machines don’t completely take over in a ‘Terminator’-like scenario. Because even if we agree we should never get to that point, I am not overconfident that that isn’t exactly what could be happening a few decades from now (without necessarily resulting in the dystopian scenarios, Hollywood likes to present on the big screen, though).

It would also inject some much needed ‘softer’ fields of study into the world of engineering and computing, which I think we need. Not so much to keep things in check as to make sure that we really utilize technology to help us solving really big problems with a massive impact. While we, humans, remain firmly in control.

(Photo: Pixabay.com)