"I really want to break into Product Management"

make products.

"If only someone would tell me how I can get a startup to notice me."

Make Products.

"I guess it's impossible and I'll never break into the industry."

MAKE PRODUCTS.

Courtesy of @edbrisson's wonderful thread on breaking into comics – https://t.co/TgNblNSCBj – here is why the same applies to Product Management, too.
There is no better way of learning the craft of product, or proving your potential to employers, than just doing it.
You do not need anybody's permission. We don't have diplomas, nor doctorates. We can barely agree on a single standard of what a Product Manager is supposed to do.
But – there is at least one blindingly obvious industry consensus – a Product Manager makes Products.

And they don't need to be kept at the exact right temperature, given endless resource, or carefully protected in order to do this.

They find their own way.
Since the dawn of capitalism, life has given children lemons, and they have sold lemonade for extortionate profits.
You, my dear time traveler, find yourself in 2018, a time not just of plentiful lemons, but lots, lots more. It is easier than ever to...
Learn to code (if you like to get your hands dirty) https://t.co/DwowAOZFJu
Build without code (that's okay too) https://t.co/nyK1hnfZrl
Find people to try your product https://t.co/T5Iu5mq6E1
And here's a wonderful secret: if your product fails, it doesn't really matter.

Most things we try don't work. Failure is a fact of life in Product.

In some cases, failure is the best demonstration of your potential.
We look for candidates that can fail and OWN their failures.

Candidates that cannot tell us about past failure are either unable to take risks (bad PM), liars (worse PM), or are some kind of nature defying superhero (probably not within our hiring budget).
A great Product Manager takes risks as a matter of habit. They chase after uncertainty. They learn at every step of the journey.
So there is no excuse 😉

M A K E P R O D U C T S !

More from Tech

THREAD: How is it possible to train a well-performing, advanced Computer Vision model 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗣𝗨? 🤔

At the heart of this lies the most important technique in modern deep learning - transfer learning.

Let's analyze how it


2/ For starters, let's look at what a neural network (NN for short) does.

An NN is like a stack of pancakes, with computation flowing up when we make predictions.

How does it all work?


3/ We show an image to our model.

An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.

Here is what it might look like for a black and white image


4/ The picture goes into the layer at the bottom.

Each layer performs computation on the image, transforming it and passing it upwards.


5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.

The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!

You May Also Like