How to Absorb the News Like a Cyborg

You have zero time to fool around reading important news. Here’s a story on how you can hack news consumption.

I start with email as I like to manage things from there. I wake up and have the following 3 emails in my inbox:

1. aggregated information:

These are the top recommended articles based on what my network is sharing on Twitter.

2. LinkedIn daily Pulse

The top recommended articles based on what my extended network is publishing on LinkedIn.

(set this up from the LinkedIn email frequency settings)

3. Birdhouse Twitter aggregator:

Summary of all the tweets from people on my Twitter VIP list (folks like Funnelholic, SaaStr, and Mark Suster). Most of these contain article links.

Here’s what the three emails look like:

Now I have a bunch of article links. But I’m not going to read them, I’m going to¬†rapidly absorb them into my brain. Here’s how:

a. Open the link and add to pocket

But I don’t even use pocket, this just auto sends the article to my Rapid app.

b. Open Rapid and hit play

The second I hit play, the words fly off the page at a rate of 475 words / minute. It uses Spritz and the screenshot on the right is static snap of what happens. This app speed reads the article at extremely faster rates than I can read on my own.

Here’s a video to show more.

So, want to know the most important articles from my LinkedIn network? Check. The most important links from Twitter? Check. The top articles from influencers? Check.

Set it up once and execute.
All in a few clicks and less time than it takes in a trip to Starbucks.

*** here is the tech used***

Moneyball For Seed Investments

When I heard Billy Beane speak about how baseball teams used to pick their players it was overly wrapped around the concept of looks….

Is he tall, was he the high school captain, homecoming king, is he fast, with a low strike out rate? Did he hit the game winning home run when the scouts visited? And more…

It was vanity stuff.

Then the industry switched to data, and a short, slow, overweight, ugly guy who had a monster on base percentage became a winner.

Seed investors and especially accelerators put too much weight on looks as well.

Did he go to Stanford? Work at Google? Does she have a pretty github account, or can she spit off quotes from the lean startup? Do they live in San Francisco and can they name drop really well? Basically, does this person fit the startup look?

Granted we have less startup data, but it is starting to change. We need to find the startup world’s on base percentage.

I don’t have the answers right now but I think they will emerge. Could there be some sort of personality analysis we can glean from their social media accounts? Could they produce product market fit data? Hell, we may find that being from San Francisco is a difference maker…there’s something in there I just don’t know what it is.

There are people working on this. One is Daniell Morrill. I recommend following her if you’re interested in the topic.

I’m excited to see how data for startups evolves over time and interested in making data driven investment decisions in the future.