Always good to read someone else's story on starting up and making money...

7 Lessons We Learned Going from Zero to $30k/Month in Under a Year

Alex Turnbull

Oct 17, 2013

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After some early wins and epic fails, Groove launched to the public. We’ve come a long way, but not without some hurdles...

In the weeks after Groove’s public launch, we saw our user acquisition numbers grow slowly but steadily. And while any growth is good, slow and steady isn’t always enough when you have mounting bills and a team that depends on you to keep the paychecks coming.

Over the next several months, I learned more than I ever have in such a short period. We tested dozens of strategies and hacks, and explored hundreds of approaches to try and find the “magic bullet” to business growth.

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This is what I need - a window that stops sound but not air

Redesigned Window Stops Sound But Not Air, Say Materials Scientists

Emerging Technology From the arXiv

July 8, 2013

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..the notion of creating a barrier that absorbs sound while allowing the free of passage of air seems, at first thought, entirely impossible....

Noise pollution is one of the bugbears of modern life. The sound of machinery, engines, neighbours and the like can seriously affect our quality of life and that of the other creatures that share this planet.

But insulating against sound is a difficult and expensive business. Soundproofing generally works on the principle of transferring sound from the air into another medium which absorbs and attenuates it.

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Steve Jobs: The Next Insanely Great Thing - wired article before his second coming to Apple

Wired article with on Steve Jobs - before his second coming to Apple

The Wired Interview

By Gary Wolf, February 1996

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Steve Jobs has been right twice. The first time we got Apple. The second time we got NeXT. The Macintosh ruled. NeXT tanked. Still, Jobs was right both times.

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Enterprise Sales Tips for Hackers

Useful to know when you are starting out and trying to sell to enterprise

Brandon’s posthaven

Brandon, 8 Aug , 2013

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When my co-founder and I were starting out, we came from an engineering background and thought of sales as black magic. Divine the customer's deepest desires, howl a few bewitching incantations, and then—abracadabra—a contract would be conjured. Magic!

Two years of selling served as a painful exorcism. There's no magic to enterprise sales, but there's a hell of a lot of zoology. LTV, field sales, inside sales, CAC, prospects, leads, consumerization, channel sales, … the array of terms is bewildering and there's no textbook that explains how it all fits together.

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Steve Jobs The Lost Interview (Full Film) 2012

This is a great interview with Steve Jobs in 1995 just before he re-joined Apple.

Uploaded by Ivaylo Todorov
Oct 7, 2012

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Clearly he knows what he is talking about and the thought process is super lucid. In his first stint at Apple he was very good. After NeXT he became great.
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Business Analysis Using User Stories

This is a great summary with succinct elaboration of what User Stories are in Agile software development.

BAEXPERTS
Nov 8, 2012

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User Stories are a great addition to our repertoire of ways of expressing stakeholder requirements.

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Google Analytics - Multi-armed Bandit Experiments

Multi-armed Bandit Experiments - no wonder my A-B stats look like they do...

Steven L. Scott, PhD, Sr. Economic Analyst, Google
January 23, 2013 | 9:40 AM

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This article describes the statistical engine behind Google Analytics Content Experiments. Google Analytics uses a multi-armed bandit approach to managing online experiments. A multi-armed bandit is a type of experiment where:

• The goal is to find the best or most profitable action
• The randomization distribution can be updated as the experiment progresses

The name "multi-armed bandit" describes a hypothetical experiment where you face several slot machines ("one-armed bandits") with potentially different expected payouts. You want to find the slot machine with the best payout rate, but you also want to maximize your winnings. The fundamental tension is between "exploiting" arms that have performed well in the past and "exploring" new or seemingly inferior arms in case they might perform even better. There are highly developed mathematical models for managing the bandit problem, which we use in Google Analytics content experiments.

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