1. The document discusses various feedback loops, including in science, open source software, user testing, online communities, free speech, marketing, and evolution. 2. In science, a feedback loop involves forming a theory, making predictions to test it, testing through experiments, and revising the theory based on results. 3. Evolution operates through a feedback loop where an organism's fitness for the environment determines whether it lives to breed and pass on its genes.

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2. <t lk g es he e>
Since I spoke at Webstock last year, I’ve had literally twos of people
come up to me on the street and animatedly say how my talk was the
highlight of their conference experience. Specifically, it was hilarious
that I had a font goof and several letters were missing on each slide.
Font fail, if you will.

3. <talk goes here>
This year that won’t happen, sorry to disappoint. Again.
Anyway, I’m going to tell you some stories and develop a thesis that
will hopefully make you feel more comfortable about something you
don’t currently like. Your job is to see whether you can figure out
what that is before I just out and tell you. If you succeed ... well, I
apologize in advance for how boring the rest of the talk will be. HA.

4. I’m going to talk about virtuous circles, or feedback loops.

5. 0.
the best example of feedback loops is science.

6. Religion
before we had science, we had religion. in religion, things are true

7. because God said so
because God said so. So how does

8. change?
our knowledge of the world change?

9. change?
Ah, well, you see, it doesn’t. Not in any systematic way that
progressively improves our understanding of the world we’re in.

10. 1610
This guy was the first scientist. He inherited a world view that was a
thousand years old, developed by Aristotle and Ptolemy and refined by
countless others. The view was being questioned by the time he
arrived, by people like

11. 1543
Copernicus. He was an astronomer who like all astronomers of the
time made observations of the night sky using his naked eyes. He
suspected that we didn’t have a geocentric cosmos (Earth in the
middle), we had a heliocentric cosmos (Sun in the middle). He and
Kepler, though, couldn’t bring themselves to abandon all the trappings
of the old model and so threw themselves into inelegant maths to
make a theory that was both Aristotle-compatible and observation-
compatible.

12. Even Galileo began astronomy by seeing the skies through the eyes of
an Aristotelian. But Galileo, when he looked through one of these (a
“looker”, the first telescope)

13. saw more detail than anyone had ever seen before. He made detailed
maps of the moon, and tracked the motion of planets through the sky.
He even saw moons on other planets, something that hadn’t been
seen before and which definitely violated Aristotle.

14. Galileo’s observations about planetary motions were hard to explain in any
way but that the Earth and the other planets are in orbit around the Sun.
Tada! Heliocentrism overthrows geocentrism, cosmology takes a giant step
forward, science rises, enter the Enlightenment and it’s a short hop until
we’re exploring those things that Galileo saw.
Not that fast. Kepler and Copernicus had met with opposition when they
mentioned their theories. But Galileo didn’t give up. He wrote a book, in
common Italian rather than the Latin of the elites, explaining his theory.
His book had a character called Simplicus in whose mouth were put

15. the Pope’s arguments, made appropriately ridiculous. The pope used
to be his friend. Used to be. There were charges of heresy, and

16. he went before these fellows, the Inquisition. Galileo had to recant,
say “ok ok, I don’t believe that at all”, and died still under house
arrest. However, rumour has it he muttered

17. E pur si muove!
“E pur si muove” after recanting. “But still it moves”. Anyway, this
stubborn bugger is widely acknowledged to be the first scientist. He
had begun as an Aristotelian with his theories but changed them
based on evidence, and he went looking for evidence to test his
theories.

18. science = world view?
He got in such a power of strife because he was trying to change the
view of the world. We think science is the view of the world. It’s not.

19. Science = change
Science is how we change our view of the world. That’s what science
is, it’s change. Change is scary if you’re the fat rich bugger with a
slick beard and a lot of sitting on the top of the heap. Hence all that
business with the Inquisition, house arrest, etc.

20. change based on
evidence
It’s not just random change, though, it’s change based on evidence.
Scientists change their opinions based on observation.

21. In fact, there’s a nice little loop here. A feedback loop. A scientist has
a theory, which makes predictions. Well, you can design experiments
or observations to test those predictions and see whether they’re true
or not. If they’re not, then you have to formulate a new theory and
with it comes a greater predictive power and understanding of the
world around us.

22. Of course, if we just test and find it’s true, we never get o the loop.
We never get to revise and thus improve. So it’s important to, at some
point, have a test come back that shows the theory’s predictions are
wrong. In fact, that is THE most important thing. To be science,

23. Falsifiable
theories must be make predictions that you can measure and show to
be false. It took nearly 500 years after Galileo for that to be figured
out--500 years during which gravity, magnetism, electricity, atomic
theory, and even quantum theory were figured out, so obviously not
understanding what they were doing didn’t entirely stop them making
progress. This theory of falsifiability was put forward by

24. Karl Popper
1934
Karl Popper. Good book, “Logic of Scientific Discovery”, well worth
reading. Kiwi connection too--he came to Christchurch from Vienna,
fell in love with the place as a socialist haven, and only left to go to
England to Cambridge, be knighted, and die famous. He managed to
live two Kiwi stories: the creative class immigrant and the brain drain.

25. knowledge increases
when someone is
wrong
Anyway, the key point to make is this: our knowledge about the world
only increases when you find out that someone was wrong. That’s
what science is.

26. Scientists Seek Failure
All that scientists want to do is to find a failure. They’re human, of
course, so preferably it’s someone else’s failure, but they can only get
a name for themselves if they find that someone was wrong.

27. a theory with
predictions
revise test
how did it hold up?
Because that’s what the feedback loop of science needs.

28. 1. A/B Testing
Whew. Let’s look at some other feedback loops. I talked about A/B
testing at Webstock last year.

29. Amazon
Amazon do it. They show you

30. A
?B
two dierent versions of the same web page. Well, not you obviously,
they don’t show you two pages at the same time. They show 10% of
their visitors the shiny new version, with dierent ads or a bigger
Kindle picture or whatever, and the other 90% get the standard home
page. Then they see who buys more per capita--those who saw old A
or new B. If the new page gets more sales, they whack it in for
everyone.

31. Here’s that feedback loop. But I’ve written this the wrong way. It’s
actually

32. we assume that the current way of doing things is the best possible.
Then we test that by running a dierent ad. Does it result in better
sales? If so, our assumption was wrong and we have a new candidate
for The Best Way Of Doing Things. Which we test by running a
dierent ad .... This is continuous improvement, each time around the
loop makes us better.

33. 2. Open source
Or another example, Open Source software like Linux and Rails.

34. “scratch your own itch”
The guiding philosophy of open source is that you can scratch your
own itch. Whether it’s a printer driver that should mail you when you
job is done, or a new button in your mail app to unsubscribe from
mailing lists, you can add the feature if you want it.

35. Here’s the feedback loop. You use the software, if it doesn’t work for
you, you can make it better. In proprietary software, you rely on
market forces to direct the vendor to scratch your itch for you. Not
always going to happen and not always most eficient.
Notice how this isn’t refining a hypothesis, this refines software.

36. 3. User testing
Related to this is user-testing. Remember science? User-testing is
the experiment and evidence part of the loop: if you take it out,
there’s no way to go around the loop and get better! Wouldn’t it be
horrible if we lived in a world where software didn’t get better because
it was tested on users?

38. 4. Community
Another example, from web sites. Can you build feedback loops into
sites of community contributions to steer the participation in
directions you want? (e.g., away from goatse and swastikas)

39. One way is to let people tell you what’s good and what’s bad. Here’s
Digg.

40. Here’s Slashdot, with thumbs-up and thumbs-down. Slashdot’s been
in this space a long time--they have a very functional and elaborate
system for managing comment threads using “karma” points that you
give to comments you like.

41. Here’s Flickr. Information on what’s been favourited is used to bubble
up interesting images.

42. So this is the feedback loop. We show some news items or photos, we
get the user to apply critical thought and tell us whether they’re good
or not and thumbs-up/thumbs-down them. This then informs our
choice of news items and photos to show the next person.

43. homophily
The danger is that you only show people things that they like, or you
only show people things that everyone likes, and nobody is ever
surprised or discovers things they didn’t know they wanted. This
situation, where we only see more things like the things we like, is
called homophily. The opposite of homophily is

44. serendipity
serendipity. We can break our feedback loop, deliberately, to add
surprises and new things. Just because we know what’s popular and
what people like, doesn’t mean we have to show just that to them.

45. 5. Free Speech
Another feedback loop is in free speech. You see, there are two
dierent approaches to the problem of

46. “what if people say bad
things that are wrong?!”
people saying things you don’t like. The first, as exemplified

47. Germany
by Germany, is to forbid it. There are things you can’t say in Germany,
like “those Nazis were lovely chaps, just a bit misunderstood”.

48. America
In America, however, you can say almost anything. Speech,
particularly political speech, is constitutionally protected. Why?
Because the founders of the country believed in a feedback loop

49. whereby the things people said could be subjected to critical thought,
determined to be bullshit, and corrected. If people weren’t allowed to
say those things, the correction from the feedback loop could never
happen.
Of course, it all falls down because it assumes most people can bring
critical thought to bear upon bad arguments.

50. 6. Marketing
Or another example, this time from marketing.

51. iPhone vs cafe training
or
Why I’m not Steve Jobs
Here’s a simple story to show you how they work.

52. Cafe Training Web Site
• market: cafes and restaurants with unskilled
labour
• product: web site with training videos
• benefits: better staff, happier customers,
greater income
I had a brilliant idea for a web site. NZ has a lot of cafes, but high
employment. So the only wait sta are generally untrained high-
turnover people. That perhaps explains why the service is shit here.
So I thought I could run a web site with training videos for cafe sta:
the cafe owners would pay me $50 per person and the new waitron
would learn how to do it. The cafe owner would be happy, I’d be
happy.

53. My friend Marc Hedlund shot this down with one question.

54. “Will your users do
your marketing for
you?”
How do you get your users to do your marketing for you? The cafe
owner would treat my web site like a competitive edge, and wouldn’t
want to tell other cafe owners about it. Compare this to

55. the iPod. Everyone who had an iPod wanted to tell their friends about
it. Even if you didn’t flash it about like this guy advertising that you
were hip to the iPod, you had the little white ear buds and people even
bought little white ear buds so they could pretend their huckory Zune
was an iPod so they could get laid. Now that’s your customers doing
your marketing.

56. Here’s the flowchart for the iPod feedback loop. The see/share-covet
bit is where we get the growth each time through the loop. If you
replace “purchase” with “contribute”, you’ve got Flickr, Slashdot, Digg,
and so on.

57. “viral” marketing
With the iPod, one user infects ten others, and each of those infect ten
others and .... You’ve probably heard the popular term for this.

58. It’s an analogy to the spread of a disease, or the growth in a
population. You start with one happy iPod user, in this case Thomas
Hobbes.

59. They tell nine other people. Now you have ten happy iPod users. Each
of those people tells another nine.

60. Now you’ve got 100. Each of those tells nine people ...

61. And now you’ve got a thousand, and so on. Notice how with science
we have a fixed number of scientists and we’re improving the model
one bit each time through the loop, but now we’re changing the
numbers and not the model? We’re getting ten times as many
customers each time through the loop, exponential growth. These
self-reinforcing positive feedback loops are powerful things.

62. “syphilitic” marketing
but do me a favour and don’t use the term “viral marketing”. I hate
that phrase.

63. 7. Evolution
Next topic is timely, as Darwin’s 200th birthday was a week ago.
Happy Birthday to you ...

64. biomimesis
biomimetics, or biomimesis, is building devices that use designs
stolen from the natural world. For example, here’s a scuttling robot:

65. This is obviously based on the lobster. Good for getting around on
uneven surface underwater: tail pushes you down and forwards, legs
deal with bumps and holes without unbalancing the body. An
Australian biomimeticist was asked why he turned to nature. He said
“every technique you see in nature is a success. The failures have all
died o over millions of years.”

66. That’s the evolutionary feedback loop: how well you fit the
environment determines whether you live or die, and thus whether you
breed and pass your genes on.

67. ?
Question: what type of feedback loop is this? Is it a steady rate of
improvement, like science, or an exponential growth like customers?

68. M
UL
TI
PL
Y
Exponential growth: each individual makes many babies, each baby
makes many more babies. In only a few generations dramatic changes
can be seen in populations.

69. This is the light-coloured pepper moth, common in England before the
Industrial Revolution. So common, in fact, only a handful were
reported before 1850. They were an unusual mutation. When coal-
burning smokestacks started covering the landscape with soot, these
buggers were easy to see on the now-dark trees. Consequently, the
white moth’s population decreased while

70. this fellow’s numbers grew. By 1895, the dark moth was 98% of the
population.
Once coal went out of favour and trees slowly lost their carbon coat,
the ratio of dark moths in the population declined and has been
steadily declining.

71. M
UL
TI
PL
Y
This is because each surviving dark moth was able to pass on its
melanin-producing genes, and each of those dark baby moths could
make more dark moths. That’s how they drove out the light moths in
only 50 years. Exponential growth, powered by a feedback loop.

72. 8. Economics
The next feedback loop.

73. cit
efi
d
e
d
tra
GD
P
inflation
ma
rgin
al t
ax
rat
e
unemployment
e
rate at
hr
cas
You might think of economics as the source of boring phrases in the
business section of the paper.

74. “Wealth of Nations”,
Adam Smith (1776)
It’s not boring. Borrow this book from the library and read the first
few chapters. I found it electrifying: he nails, in an easy-to-
understand way, how the world works.

75. feedback loops of money
Money has feedback loops, and we’re starting to go through some of
them now as the economy contracts.

76. Businesses hire workers for money. Businesses sell things like
washing machines to workers for money.
Too many workers? Business won’t need to pay as much for them.
Those jobs that pay more will attract workers. Now businesses have to
pay more to get the supply of workers.

77. Similarly, if there are too many washing machines for sale, the price
will be low, perhaps too low to make a profit, and businesses will stop
making them until the price returns to a reasonable level. This means
they need fewer sta, so there are more sta for hire, so wage costs
go down, so perhaps the cost of making them comes down ...
And so on.

78. simulatable
The point is that money flows in a predictable way. So predictable that
you can build economic models: workers behave like this, businesses
behave like this, government behaves like this, consumers behave like
this, so the money flows like this.

79. That’s what this is: MONIAC, a simulation of the New Zealand
economy ... in water. It’s in the lobby of the Reserve Bank building,
not far from here. I’m going to see it later today. Built by a NZ
economist, money moves between reservoirs (corresponding to govt,
banks, consumers, etc.) according to rules (valves) that you can
change.

80. price = supply demand
So economics turns the mystery of money into rules. Makes it
predictable, so you can look at the world around you and figure out
what’s really going on.
The biggest rule is that supply and demand together determine prices.
Prices of washing machines, prices of food, prices of the software that
you’re building in your companies.

81. economy = b0rked
But, I hear you thinking, the economy’s crashing to pieces. Rules, my
arse!

82. But rules aren’t the same as predictability. Here’s a picture of that.
Each point on this picture is a feedback loop. You start with the (x,y)
coordinates, go through a very simple feedback loop a bunch of times
to compute a value, and colour the point based on what the value
converges to (or doesn’t converge to). What you can tell is that there
are huge variations in outcome for tiny little variations in input. Those
exponential feedback loops, like evolution and money, don’t give
predictable results. That’s chaos theory. You’ve heard about it on tele
and it sounds hard, so it must be true.

83. 9. Invention
Let’s bring it back to something that’s near and dear to Webstockians’
hearts: new stu.

84. innovation
This word is so 2005: innovation. An innovation is simply

85. innovation = invention
you can sell
an invention that you can sell. It’s easy to imagine an invention you
can’t sell (shoes made of lava, an exploding toilet, a web site to teach
French to cats). Inventions aren’t innovation. It’s the useful ones, the
ones that you can find a market for, those are the innovations that
change the world.

86. Joseph Schumpeter
(1883-1950)
this economist, Joseph Schumpeter, gave us some of the best thinking
about innovation. He coined the term

87. “creative destruction”
“creative destruction” for the curious inability of feedback to have
eect in companies. It works like this.

88. There’s a company with a product, a great product, it makes lots of
money. Think Sony and the walkman. Kids, a walkman is a portable
cassette player with headphones. Like an iPod but from the Dark
Ages. Anyway, Sony invented them and made a shitload of money
from them.

89. However, eventually a new innovation came along, the MP3 player.
Companies made those. The products weren’t as reliable, they didn’t
have all the music available that Walkmen did, they only appealed to
geeks and not the mainstream. Sony figured they were safe.

90. After all, the MP3 players were only earning a little bit of money from
their crappy devices that played only a few bits of music and that you
had to be a geek to drive. Sony focused on the Walkmen, selling
customers on the advantages of quality tape products.

91. But as time went on, MP3 players got better. More music was available
for them, and you didn’t have to be a technohead to drive them. You
could do things with them that you couldn’t with a Walkman. Apple
entered the market and ate Sony’s lunch. Sony has tried repeatedly to
enter the digital music playing market, and has failed repeatedly.

92. Microsoft Linux
Its not just Sony and MP3 players. Think Microsoft vs Linux, or

93. Word Google Docs
feature-rich Microsoft Word facing down feature-poor but free Google
Docs

94. Creative Apple
even in digital music markets, Creative had their huge market
headstart shot to pieces from the expensive iPod that was Mac-only at
first.

95. Kodak Canon
photographic film used to be how you made photos, and Kodak ruled
the roost. They’ve nearly gone under now, because digital cameras
ate away at their market and Kodak wasted its headstart and market
advantage just blathering about how much high quality film was to
digital.

96. Newspapers Web
Newspapers are being eaten by the Web. Nobody knows how it will
turn out, except that the future of print newspapers is grim.

97. Big mills mini mills
not just computers, the classic example is vertically integrated steel
mills that could do huge amounts of work being replaced by the
smaller mini mills.

98. Archery Guns
even five hundred years ago, guns replaced bows and arrows. You
might think guns are naturally better than bows and arrows, but that’s
hindsight talking. The first guns were ghastly inaccurate things. But
you didn’t need trained sta, so the archery industry withered as the
firearms industry bloomed.

99. ?
The question you should be asking is: what the fuck were these people
thinking? Why did they just sit back and let their huge profits and
huge market share evaporate?

100. “The Innovator’s
Dilemma”, Clayton
Christenson
This book tells us why this happens. Big companies are invested (financially
and emotionally) in the products that made them big. They must defend
those products against competition. They see it as stupid to adopt a new
technology product that’s crapper than the great thing they’re oering--it’d
eat away at their business, they don’t know how to reach the people who
might be interested in that new technology anyway, maybe the economics
of the new technology are so dodgy that only a small company would want
to chase the first customers. Lots of reasons why not to. They miss the big
reason: because if they don’t kill their cash cow, someone else will.

101. “I used to be afraid of a
big company stealing
my idea ....”
A friend at a large American web company said, “I used to be afraid of
a big company stealing my idea. Now I realize that I have nothing to
worry about. They can’t do anything with the ideas inside their
company, let alone the ones outside.”

102. feedback loop?
What’s the feedback loop here? Well, it should be that companies

103. constantly ask themselves whether they’re meeting every customer’s need
as best they can with the technology available, and then introduce new
products to test this hypothesis. If the hypothesis is proven false with
sales, they update the product line. The problem with this is that it’s
largely bollocks. It’s all big companies can do to breathe and service the
customers they have with the products they have. Don’t expect them to
think agile and nimbly react to new possibilities. The best they can hope
for is to buy the upstart company before the legacy product’s marketshare
drops all the way to zero.

104. 10. You
Which brings me to the end, and to the final feedback loop. It’s not
about big companies, it’s about you.

105. 9.5. S92
Guilt on accusation.
Mashups
Questions in Parliament.
Protest at Parliament today, 12-12.30
Be a protest in Auckland.
Web site blackout on Monday.
Feedback loop for government.

106. Here’s the genesis for this talk. My kids didn’t want to run around the schoolyard in PE because the other kids were
faster than them. I remembered that pain well. But what I know now, now that I’m not in school any more, is that it’s not
about racing other kids, it’s just about getting personal best times. I explained that this loop is how you get better: after
doing something, you measure to see how you did and then decide what to do to next. So you might practice more or
change your finger positions if you were learning the violin, or if you’re applying for a job and don’t get it then you might
try dressing dierent or doing your paperwork dierent. If you don’t run around the field in PE, I said, you’ll never know
whether you’re getting fitter.
It worked, a testament to my kids’ smarts rather than my motivational brilliance.
But I want you take this to heart. I want you to live your own feedback loop so you can get what you want from life. But,
you might ask, if they’re so useful why doesn’t everyone do it?

107. A Challenge!
Let me show you one reason why it’s not easy. Here’s a challenge.

108. If a card has a vowel on one
side, then it has an even
number on the other side.
A B 4 7
Let’s say someone tells you that cards with a vowel on them have an
even number on the other side. How do you test this hypothesis?
(take answers)

109. If a person is drinking beer,
then the person is over 18.
Beer Coke 22 16
Is it any easier if we change the domain to something closer to your
heart?
How would we test the hypothesis that beer drinkers are all over 18?

110. If a person is drinking beer,
then the person is over 18.
Beer Coke 22 16
We’d have to look at the Beer card to make sure the beer drinker
wasn’t under 18, and we’d have to look at the 16 card to make sure
the young person wasn’t drinking beer.

111. If a card has a vowel on one
side, then it has an even
number on the other side.
A B 4 7
The same thing is true for the vowel/number hypothesis.

112. Not Wired That Way
We humans evolved to deal well with specific situations--we learn well
from example, and we can estimate numbers well. But there are lots
of modern situations where we haven’t evolved well. Falsifying is an
example: we learn from example by enjoying confirmation. But to test
a hypothesis, we must seek out counterexamples and our brains just
aren’t good at that unless it’s a situation we’re already very familiar
with.

113. For example, that exponential growth we saw earlier--that’s
compound interest. Everyone raves at you to put your money in a
bank account with compound interest, that’s why--every dollar works
for you, even the ones you earn in interest, and they all just keep
working for you making more dollars. But we’re lousy at estimating
compounding.
Here’s another example.

114. Question
Linda is 31 years old, single, outspoken, and very bright. She
majored in philosophy. As a student, she was deeply
concerned with issues of discrimination and social justice,
and also participated in anti-nuclear demonstrations.
Which is more probable?
A. Linda is a bank teller.
B. Linda is a bank teller and active in the feminist
movement.

115. Question
Linda is 31 years old, single, outspoken, and very bright. She
majored in philosophy. As a student, she was deeply
concerned with issues of discrimination and social justice,
and also participated in anti-nuclear demonstrations.
Which is more probable?
A. Linda is a bank teller.
B. Linda is a bank teller and active in the feminist
movement.
We’re bad at dealing with probabilities and subsets. Many people will
tell you that B is more likely, because Linda sounds likely to be a
feminist. But if you look at the probabilities, fewer people are bank
tellers AND feminists so the probability of B is lower than the
probability of A.

116. Practice
Because it doesn’t come natural, practice it. Look for situations where
you can test one of your hypotheses. Think hard to make sure you’re
observing the right things!

117. the other challenge
But the real reason people don’t test their hypothesis is

118. because we, as a society, don’t understand failure. If you’re like me,
you worry that when you fail you’ll be thought less of. Maybe you’ll be
fired, maybe you’ll lose friends, maybe it’ll be harder to get the next
pay rise. We’re taught from an early age to seek success but that

119. failure = bad
failure is bad.

120. failure = bad
I say that’s rubbish.

121. failure = TEH AWESUM!
Failure is awesome! Failure is fantastic! Failure is how we learn!
You’re laughing. That’s because you’re conditioned to believe failure
is bad. Snap out of it!
Of course, failure is only good ...

122. Don’t be afraid to fail,
so long as you learn
if you learn from your mistakes. The problem is that we’re so afraid of
failure, we never inspect our failures to learn. We’ve become a Far
Side strip.

124. failure without learning
=
bad
It’s failure without learning that’s bad. You can’t succeed unless you
take risks. They’re not called risks for nothing--with any risk you take
there’s a chance of failure as well of success. But failure can teach you
things and prepare you for success.
Don’t just take my word for it:

125. “It is on our failures
that we base a new and
different and better
success.”
-Havelock Ellis

126. “Failure is instructive.
The person who really
thinks learns quite as
much from his failures
as from his successes.”
-John Dewey

127. “I’ve missed more than 9,000
shots in my career. I’ve lost
almost 300 games. 26 times
I’ve been trusted to take the
game winning shot and
missed. I’ve failed over and
over and over again in my life
and that is why I succeed.”
-Michael Jordan

128. “Experience is simply
the name we give our
mistakes.”
-Oscar Wilde

129. “It is a mistake to suppose that
men succeed through success;
they much oftener succeed
through failures. Precept,
study, advice, and example
could never have taught them
so well as failure has done.”
- Samuel Smiles

130. “I have not failed. I've
just found 10,000 ways
that won't work.”
-Thomas Alva Edison

131. “Success consists of
going from failure to
failure without loss of
enthusiasm.”
-Winston Churchill

132. The Secret
So here’s the secret to being able to do something well.

133. fail small
It’s simple: fail small. Don’t start by failing at huge things. Huge
failures have huge costs and it’s not always possible to get a
correspondingly huge amount of learning from them. Fail small: learn
a little at a time.

134. fail before it’s big
This doesn’t mean you can’t tackle big projects, just that you tackle
them small bit by small bit, and always keep your eye open for the
situation where you can say “this isn’t going to work, the project has
failed but hasn’t yet cost us a huge amount”. Learn as much as you
can for the lowest cost that you can.

135. the gate
someone recently explained it to me like this: projects go through
phases: scoping, requirements, development, testing, maintenance,
etc. At each phase, there’s a gate: we could kill it after scoping, or we
go onto requirements. We could kill it after the requirements, or we go
on to development, etc. All too often, though, we view a project as a
race through the gate: we have to make it through that gate, not get
the project killed.
That’s so backwards. The projects that fail small are wonderful! Just
ask anyone who has been on a project that failed big!

136. learn from the failures
So fail early and fail often, but always learn from the failures. That’s
my thesis. That’s the dierent approach to something unpleasant. I
want to leave you with a simple catchphrase that sums up how to build
your own personal feedback loop, three short words that I hope you
will take back and try to apply in your life, in your work, and in your
works:

137. fail forward fast
Fail
Forward
Fast

138. Thank You
fail forward fast
nathan@torkington.com
thank you

139. “Cybernetics”, by
Norbert Weiner

140. • http://xkcd.com/54/
• http://flickr.com/photos/tiredofh2o/2793907195/
• http://flickr.com/photos/wwworks/2222523486/
• http://www.norcalblogs.com/telescope/securedownload-1.jpeg
• http://en.wikipedia.org/wiki/Image:Nikolaus_Kopernikus.jpg
• http://www.onu.edu/a+s/physics/ASTROGALLERY/JupiterMoonsImg551.jpg
• http://flickr.com/photos/claudiagold/2983218687/
• http://flickr.com/photos/pindec/154726206/
• http://www.rfcc.net/the%20circular%20flow.bmp
• http://flickr.com/photos/seven13avenue/2782229153/
• http://flickr.com/photos/greenboy/416052683/sizes/o/
• http://controversy.wearscience.com/img450/geocentric.gif
• http://physics.ship.edu/~mrc/pfs/110/inside_out/vu1/Galileo/Images/Port/urban_viii1.gif
• http://hsci.ou.edu/images/jpg-100dpi-10in/17thCentury/Galileo/1610/Galileo-1610-007r.jpg
• http://abyss.uoregon.edu/~js/images/Malthus.jpg
• http://www.onr.navy.mil/media/images/gallery/hires/robots/051206-N-7676W-082a.jpg
• http://upload.wikimedia.org/wikipedia/commons/6/6c/Biston.betularia.7200.jpg
• http://en.wikipedia.org/wiki/Image:Biston.betularia.f.carbonaria.7209.jpg
• http://openparachute.files.wordpress.com/2008/06/popper-karl-01.jpg